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An international open access peer-reviewed journal published by the Czech Academy of Agricultural Sciences and financed by the Ministry of Agriculture of the Czech Republic. Published since 1954 (by 1999 under the title Zemědělská technika)

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• Published: 09 September 2021

Advancing agricultural research using machine learning algorithms

• Spyridon Mourtzinis 1 ,
• Paul D. Esker 2 ,
• James E. Specht 3 &
• Shawn P. Conley 4  

Scientific Reports volume  11 , Article number:  17879 ( 2021 ) Cite this article

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• Agroecology

Rising global population and climate change realities dictate that agricultural productivity must be accelerated. Results from current traditional research approaches are difficult to extrapolate to all possible fields because they are dependent on specific soil types, weather conditions, and background management combinations that are not applicable nor translatable to all farms. A method that accurately evaluates the effectiveness of infinite cropping system interactions (involving multiple management practices) to increase maize and soybean yield across the US does not exist. Here, we utilize extensive databases and artificial intelligence algorithms and show that complex interactions, which cannot be evaluated in replicated trials, are associated with large crop yield variability and thus, potential for substantial yield increases. Our approach can accelerate agricultural research, identify sustainable practices, and help overcome future food demands.

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Introduction.

Increasing food demand will challenge the agricultural sector globally over the next decades 1 . A sustainable solution to this challenge is to increase crop yield without massive cropland area expansion. This can be achieved by identifying and adopting best management practices. To do so requires a more detailed understanding of how crop yield is impacted by climate change 2 , 3 and growing-season weather variability 4 . Even with that knowledge, prediction is challenging because various factors interact with each other. For example, variability in soil type can interact with weather conditions and mitigate or aggravate climate-related impacts on crop yield 5 , 6 . Additionally, seed genetics (G) and crop management decisions (M), interact with the effect of environment (E: soil and in-season weather conditions), thereby resulting in a near infinite number of combinations of G × E × M that can impact crop yield.

Substantial variability in crop yield arises from the wide range of optimal to sub-optimal management observed in soybean farmers’ fields 7 , 8 . Reducing the frequency of lowest vs . highest yields has been proposed as an effective means to increase food production in existing crop land 9 . In that regard, replicated field experiments have been used to identify best management practices for several decades. Most commonly, the effectiveness of up to three management factors and their interactions are evaluated in a single location due to practical constraints (e.g., cost, logistics). By holding the background management constant, causal relationships are identified, and the effectiveness of the examined management practice/s is assessed. It is assumed that background management practices are optimal or at least relevant to what most farmers use in the region, which in fact may not be realistic for many farmers.

Multi-year-site performance trials that account for large environmental and background management variability is another common practice in agricultural research. Such trials usually estimate an average effect across environments and background cropping systems. Inevitably, the measured yield response magnitude and sign may not apply to all farms in the examined region. Other research approaches involve analysis of producer self-reported data 7 , 8 , which can capture yield trends attributable to producer management choice across large regions, but such studies lack sufficient power relative to establishing causality and evaluating complex high-order G × E × M interactions.

Process-based models have been extensively used to evaluate the effect of weather 10 and management 11 , 12 on crop yield. However, to obtain accurate estimates, the models require extensive calibration, which is not a trivial task due to the large number of parameters. Specifically, it has been shown that management is an important source of uncertainty in process-based models, which can lead to substantial and varying degree of bias in yield estimates across the US, even when using harmonized parameters 13 .

Given all the well-known deficiencies of current agricultural research methods, we argue that a method that allows environment-specific identification of unique cropping systems with the greatest yield potential is essential to meet future food demand. Here, by utilizing maize and soybean yield and management data from publicly available performance tests, plus associated weather data, and by leveraging the power of machine learning (ML) algorithms, we developed a method that can evaluate myriads of potential crop management systems and thereby identify those with the greatest yield potential in specific environments across the US.

Results and discussion

Two databases including yield, management, and weather data for maize (n = 17,013) and soybean (n = 24,848) involving US crop performance trials conducted in 28 states between 2016 to 2018 for maize and between 2014 to 2018 for soybean, were developed (Fig.  1 ). Crop yield and management data were obtained from publicly available variety performance trials which are typically performed yearly in several locations across each state ( see methods for more information ). Final databases were separated in training (80% of database) and testing (20% of database) datasets using stratified sampling by year, use of irrigation, and soil type. For each crop, an extreme gradient boosting (XGBoost, see methods for more information ) algorithm to estimate yield based on soil type and weather conditions (E), seed traits (G) and management practices (M) was developed (see variables listed in Tables S1 and S2 for maize and soybean, respectively, and data science workflow in Fig. S1 ).

Locations where maize and soybean trials were performed during the examined period. The map was developed in ArcGIS Pro 2.8.0 ( https://www.esri.com ).

The developed algorithms exhibited a high degree of accuracy when estimating yield in independent datasets (test dataset not used for model calibration) (Fig.  2 ). For maize, the root mean square error (RMSE) and mean absolute error (MAE) was a respective 4.7 and 3.6% of the dataset average yield (13,340 kg/ha). For soybean, the respective RMSE and MAE was 6.4 and 4.9% of the dataset average yield (4153 kg/ha). As is evident in the graphs (Fig.  2 ), estimated yields exhibited a high degree of correlation with actual yields for both algorithms in the independent datasets. For maize and soybean, 72.3 and 60% of cases in the test dataset deviated less than 5% from actual yields, respectively. Maximum deviation for maize and soybean reached 43 and 70%, respectively. Data points with deviations greater than 15% from actual yield were 1.5% in maize and 3.6% in soybean databases. These results suggest that the developed algorithms can accurately estimate maize and soybean yields utilizing database-generated information involving reported environmental, seed genetic, and crop management variables.

Actual versus algorithm-derived maize (left) and soybean (right) yield in test datasets. Black solid line indicates y = x, red short-dashed lines, black dashed lines, and red long-dashed lines indicate ± 5, 10, and 15% deviation from the y = x line. RMSE, root mean square error; MAE, mean absolute error; r 2 , coefficient of determination; n = number of observations. Each observation corresponds to a yield of an individual cropping system in a specific environment (location-year).

In contrast to statistical models, ML algorithms can be complex, and the effect of single independent variables may not obvious. However, accumulated local effects (ALE) plots 14 can aid the understanding and visualization of important and possibly correlated features in ML algorithms. For both crops, indicatively important variables included sowing date, seeding rate, nitrogen fertilizer (for maize), row spacing (for soybean) and June to September cumulative precipitation (Fig.  3 ). Across the entire region and for both crops, the algorithm-derived trends suggest that above average yields occur in late April to early May sowing dates, but sharply decrease thereafter. Similar responses have been observed in many regional studies across the US for both, maize 15 , 16 , 17 , 18 and soybean 19 . Similarly, simulated yield curves due to increasing seeding rate are in close agreement with previous maize 20 , 21 and soybean 22 studies. The maize algorithm has captured the increasing yield due to increasing N fertilizer rate. The soybean algorithm suggests that narrower row spacing resulted in above average yield compared to wider spacing. Such response has been observed in many regions across the US 23 . Season cumulative precipitation between 400 and 700 mm resulted in above average yields for both crops.

Accumulated local effect plots for maize sowing date ( A ), seeding rate ( B ), Nitrogen fertilizer rate ( C ), and cumulative precipitation between June and September (mm) ( D ), and soybean sowing date ( E ), seeding rate ( F ), row spacing ( G ), and cumulative precipitation between June and September (mm) ( H ).

The responses in the ALE plots (Fig.  3 ) suggest that these algorithms have captured the general expected average responses for important single features. Nevertheless, our databases include hundreds of locations with diverse environments across the US and site-specific crop responses which may vary due to components of the G × E × M interaction. We argue that, instead of examining a single or low-order management interactions, site-specific evaluation of complex high order interactions (a.k.a. cropping systems) can reveal yield differences that current research approaches cannot fully explore and quantify. For example, sowing date exerts a well-known impact on maize and soybean yield. For each crop separately, by creating a hypothetical cropping system (a single combination of all management and traits in Tables S1 and S2 ) in a randomly chosen field in south central Wisconsin (latitude = 43.34, longitude = -89.38), and by applying the developed algorithms, we can generate estimates of maize and soybean yield. For that specific field and cropping system (out of the vast number of management combinations a farmer can choose from), maize yield with May 1st sowing was 711 kg/ha greater (6% increase) than June sowing (Fig.  4 A). By creating scenarios with 256 background cropping system choices (Table S3 ), the resultant algorithm-derived yield estimate difference for the same sowing date contrast (averaged across varying cropping systems) was smaller but still positive (3% increase), although the range of possible yield differences was wider (Fig.  4 B). However, when comparing, instead of averaging, the estimated yield potential among the simulated cropping systems, a 2903 kg/ha yield difference (25% difference) was observed (Fig.  4 C). Interestingly, when focusing on the early sown fields that were expected to exhibit the greatest yield, the same yield difference was observed (Fig.  4 D). This result shows that sub-optimal background management can mitigate the beneficial effect of early sowing (Table S4 ).

Maize yield difference (in kg/ha and percentage) due to sowing date (May 1st vs. June 1st) for a single identical background cropping system ( A ), maize yield difference due to sowing date when averaged across 256 (3 years × 256 cropping systems = 768 year-specific yields) ( B ), maize yield variability in each of the 256 cropping systems ( C ), and maize yield variability in each of the 128 cropping systems with early sowing ( D ). Soybean yield difference due to sowing date (May 1st vs June 1st) for a single identical background cropping system ( E ), soybean yield difference due to sowing date when averaged across 128 (5 years × 128 cropping systems = 640 year-specific yields) ( F ), soybean yield in each of the 128 cropping systems ( G ) and soybean yield variability due in each of the 64 cropping systems with early sowing ( H ). Within each panel, the horizontal red and grey lines indicate the boxplot with maximum and minimum yield, respectively. In the left four panels, boxes delimit first and third quartiles; solid lines inside boxes indicate median and green triangles indicate means. Upper and lower whiskers extend to maximum and minimum yields. Each maize and soybean cropping system is a respective 8-way and a 7-way interaction of management practices in a randomly chosen field in Wisconsin, USA (Table S3 and S5 , respectively).

In the case of soybean, a May 1st sowing resulted in greater yield (588 kg/ha; a 14% increase) than a June 1st in the single background cropping system (Fig.  4 E). The result was consistent when yield differences due to sowing date were averaged across 128 background cropping system choices (Table S5 ) (Fig.  4 F). Similar to what was observed in maize, among all cropping systems, yield varied by 1704 kg/ha (44% difference) (Fig.  4 G). When focusing only on the early sown fields, a 1181 kg/ha yield difference (27% yield increase) was observed (Fig.  4 H). In agreement with maize, this result highlights the importance of accounting for sub-optimal background management which can mitigate the beneficial effect of early sowing (Table S6 ).

We note here the ability of farmers to change management practices can be limited due to an equipment constraint (e.g., change planter unit row width) or simply impossible (e.g., change the previous year’s crop). Thus, recommended management practices that were evaluated in studies that used specific background management may not be applicable in some instances. The benefits of the foregoing approach, which involves extensive up-to-date agronomic datasets and high-level computational programing, can have important and immediate implications in future agricultural trials. Our approach allows for more precise examination of complex management interactions in specific environments (soil type and growing season weather) across the US (region covered in Fig.  1 ). The ability to extract single management practice information (even across cropping systems) is also possible by utilizing ALE plots, or by calculation of the frequency at which a given level/rate of a management practice appeared among the highest yielding cropping systems (Tables S4 and S6 ).

Among all available 30-d weather variables, many were strongly correlated in both crop databases (Figs. S2 and S3 for maize and soybean, respectively). Models using all 30-d interval variables with r < 0.7 (Tables S8 and S9 ) showed minimal to no performance gain compared to the final more parsimonious models that included season-long weather variables (Fig. S4 ). Thus, we consider the length of periods we chose to represent well the approximate successive 60-d pre-sowing, 120-d in-season, and 60-d post-harvest segments of growing season in the US (Fig. S7 ). Season-long weather conditions have been used in previous studies 13 , 24 , and it has been shown that choice of growing season does not affect climate-related effects on crop yield 25 , 26 .

As an additional sensitivity analysis, we developed ALE plots for the algorithms using the aforementioned 30-d weather variables (Fig. S8 ). For major management practices, there were no differences in simulated responses between the algorithms that used multiple 30-d weather variables and the final chosen algorithms that used longer intervals (Fig.  3 ). Repeating the analysis for the same hypothetical cropping system in the same Wisconsin location using the algorithms developed with the 30-d weather conditions, the observed trends were consistent with the season-long weather algorithms, although the simulated yields were numerical different (Fig. S9 ). Nevertheless, across all representations of weather conditions (algorithms with 30-d intervals and season-long), the levels/rates of management practices in the 5% highest and lowest yielding maize and 5% highest soybean cropping systems with early sowing date were identical, apart from manure use in maize. Based on these results, we consider the algorithm-derived yield estimates robust to different representations of seasonal weather variability.

It appears that several different cropping systems can result in similar high yield for both crops (Fig.  4 C,D,G,H). This is in agreement with other agricultural decision maker tools 27 . Moreover, it is common for neighboring farms to attain similar crop yield despite the use of a different cropping system, suggesting that a single optimal solution does not necessarily exist and that different combinations of management practices, when they interact with environment, can still result in similar high yields. Since the effect of environment is ever-changing, the high level of complexity of synergies between G × E × M suggests that long-term optimization of single management factor may not be possible 28 , which further highlights the importance of accounting for the effect of the entire cropping system at the field level.

The approach we present here should not be considered as a crop yield forecasting exercise. There have been several attempts to forecast crop yields using deep neural network methods (e.g., 29 , 30 ). In contrast, the algorithms we present here can generate hypothetical experimental data that can be used to rapidly examine G × E × M interaction for both maize and soybean across the US. Of the millions of possible G × E × M combinations, our ML algorithms can identify hidden complex patterns between G × E × M combinations for yield optimization that may be non-obvious, but once identified, worthy of field test confirmation. Farmers can use the algorithms to gain insights about optimum management interactions in their location-specific environment (known soil type × expected weather conditions), and to identify farm factors that may be too costly to alter without a priori reason (generated by the model) for doing so. Researchers can compare expected yield across thousands of hypothetical cropping systems and use the results as a guide to design more efficient future field-based crop management practice evaluation experiments.

We note that this approach should not be considered as a substitute of replicated trials. To the contrary, replicated field trials performed by Universities are continually needed to serve as an excellent source of high-quality unbiased data which can be used to train even more comprehensive algorithms. The major issue with current performance trial data is that a great amount of management information is not reported. Usually, only information relevant to the examined management factors in each trial are reported, which inevitably results in missing values (Tables S1 and S2 ), or even in absence of important variables (e.g., number and dates of split fertilizer application). As we have highlighted here, the high order and complex background management interactions should not be considered as irrelevant.

Conclusions

Agricultural experiments repeated every year in hundreds of locations across the US generate a vast amount of crop yield and management datasets which are useful for broad inferences (average effect of a management practice across a range of environments). Such datasets have, to date, remained disconnected from each other, and are difficult to combine, standardize, and properly analyze. In the presented work, we overcame these issues by developing large databases and by leveraging the power of ML algorithms. We argue that our algorithms can advance agricultural research and aid in revealing a currently hidden yield potential in each individual farm across the US.

Crop yield and management data were obtained from publicly available variety performance trials which are typically performed yearly in several locations across each state 31 . Recorded, trial-specific, management practices for maize included use of irrigation, tillage practice, seeding rate, row spacing, sowing date, previous crop, fertilizer (N, P, and K), use of manure, cultivar’s maturity, insecticide traits and use of seed treatments (Table S1 ). For soybean, use of irrigation, foliar fungicide, tillage practice, seeding rate, row spacing, sowing date, previous crop, and cultivar maturity were recorded (Table S2 ).

Since data were collected from different states and years, it was assumed that reported management practices (general categories) were consistent across all locations. Additionally, the type and application method of fertilizer was rarely reported. Similarly, there was a lack of information on the active ingredient and rates of seed treatments and foliar applied products. We acknowledge that this lack of information, as we state in the discussion section, is a limitation of our databases and our assumption, that the way different management practices are reported across different states is consistent, may have contributed to the observed unexplained variability.

For both databases, data entry was performed manually. Additionally, for both crops, soil type was recorded and weather data (Table S7 ) were retrieved from the DAYMET 32 database for each year and set of coordinates. DAYMET daily data are reasonably accurate when means or totals are calculated over extended periods 33 . Therefore, means and sums for three periods (90–150, 151–270, and 271–330 days of year) (Tables S1 and S2 ) and 30-d periods (Tables S8 and S9 ) were calculated. The different sets of weather variables were used in different models to assess their impact in model accuracy.

The exact coordinates for each site were not reported in the trial reports. Therefore, approximate coordinates, based on the nearest reported city, were used for each unreported site. When unmanageable production adversities were reported (e.g., hail, damage due to deer etc.), the associated data were not used. Missing values were present in almost all management-related variables in both databases (Tables S1 and S2 ). Since the data were derived from designed experiments, levels of management were not a result of response to external factors (e.g., weather conditions) but were researcher’s decisions to answer specific research questions (e.g., crop yield response to different sowing dates or maturity ratings), no missing data imputation was performed.

The first step before data analysis was to examine correlations among the weather variables. Due to their strong collinearity (Figs. S3 and S4 for maize and soybean, respectively), only those with Pearson r < 0.7 were retained for subsequent analyses. The final maize database included seven weather variables (Table S1 ) and the final soybean database included eight weather variables (Table S2 ). Categorical variables were one-hot encoded and then databases were separated in training (80% of database) and testing (20% of database) datasets. To ensure adequate representation of growing environments in both, the training and testing portions of the data, stratified sampling was performed by year, use of irrigation, and soil type. For each crop, an extreme gradient boosting (XGBoost) algorithm 34 was trained to predict final yield as a response of the aforementioned weather and management variables listed in Tables S1 and S2 . The hyperparameters were optimized using the training dataset and included number of estimators, tree depth, number of leaves, minimum sum of instance weight in node, learning rate, subsample percentage, column sample by tree and by level, gamma, alpha and lambda parameters. To efficiently tune the hypermeters, Bayesian optimization was performed using “hyperopt” in Python 3.6.9 with tenfold cross validation. The combination of the hypermeters that resulted in the lowest root mean square error (RMSE) in the tenfold cross validations was chosen as the final model which was further evaluated on the test portion of the data (Fig.  2 in main document).

Accumulated local effects (ALE) plots 14 , which are robust to correlation among independent variables, were developed for indicative and important variables using 1000 Monte Carlo simulations. These plots are useful to visualize how individual features influence the predictions of the developed “black-box” algorithms. To perform the evaluation for the “what if” scenarios, the final algorithms were applied on hypothetical cropping systems in a randomly chosen field in south central Wisconsin (latitude = 43.34, longitude =  − 89.38) and weather conditions in 2016–2018 for maize and 2014–2018 for soybean. Boxplots were used to visually evaluate the results.

Data and code availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Godfray, H. C. J. et al. Food security: The challenge of feeding 9 billion people. Science 327 , 812–818 (2010).

Article   ADS   CAS   Google Scholar  

Schlenker, W. & Lobell, D. B. Robust negative impacts of climate change on African agriculture. Environ. Res. Lett. 5 , 014010 (2010).

Article   ADS   Google Scholar  

Mourtzinis, S. et al. Climate-induced reduction in US-wide soybean yields underpinned by region- and in-season specific responses. Nat. Plants 1 , 14026 (2015).

Article   Google Scholar  

Hoffman, L. A., Kemanian, A. R. & Forest, C. E. The response of maize, sorghum, and soybean yield to growing-phase climate revealed with machine learning. Environ. Res. Lett. 15 , 094013 (2020).

Folberth, C. et al. Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations. Nat. Commun. https://doi.org/10.1038/ncomms11872 (2016).

Article   PubMed   PubMed Central   Google Scholar  

Makinen, H., Kaseva, J., Virkajarvi, P. & Kahiluoto, H. Shifts in soil–climate combination deserve attention. Agric. For. Meteorol. 234 , 236–246 (2017).

Rattalino Edreira, J. I. et al. Assessing causes of yield gaps in agricultural areas with diversity in climate and soils. Agric For Meteorol 247 , 170–180 (2017).

Mourtzinis, S. et al. Sifting and winnowing: analysis of farmer field data for soybean in the US North-Central region. Field Crops Res. 221 , 130–141 (2018).

Pradhan, P., Lüdeke, M. K. B., Reusser, D. E. & Kropp, J. P. Food self-sufficiency across scales: How local can we go?. Environ. Sci. Technol. 48 , 9463–9470 (2014).

Frieler, K. et al. Understanding the weather signal in national crop-yield variability. Earths Fut. 5 , 605–616 (2017).

Puntel, L. A. et al. Modeling long-term corn yield response to nitrogen rate and crop rotation. Front. Plant Sci. 7 , 1630 (2016).

Rong, J. et al. Exploring management strategies to improve maize yield and nitrogen use efficiency in northeast China using the DNDC and DSSAT models. Comput. Electron. Agric. 166 , 104988 (2019).

Leng, G. & Hall, J. W. Predicting spatial and temporal variability in crop yields: an inter-comparison of machine learning, regression and process-based models. Environ. Res. Lett. 15 , 044027 (2020).

Apley, D. W. & Zhu, J. Visualizing the effects of predictor variables in black box supervised learning models. arXiv:1612.08468v2 (2016).

Swanson, S. P. & Wilhelm, W. W. Planting date and residue rate effects on growth, partitioning, and yield of corn. Agron. J. 88 , 205–210 (1996).

Wiatrak, P. J. & Wright, D. Corn hybrids for late planting in the Southeast. Agron. J. 96 , 1118–1124 (2004).

Bruns, H. A. & Abbas, H. K. Planting date effects on Bt and non-Bt corn in the mid-south USA. Agron. J. 98 , 100–106 (2006).

Long, N. V., Assefa, Y., Schwalbert, R. & Ciampitti, I. A. Maize yield and planting date relationship: A synthesis-analysis for US high-yielding contest-winner and field research data. Front. Plant Sci. 8 , 2106 (2017).

Mourtzinis, S., Specht, J. E. & Conley, S. P. Defining optimal soybean sowing dates across the US. Sci. Rep. 9 , 2800 (2019).

Assefa, Y. et al. Yield responses to planting density for US modern corn hybrids: A synthesis-analysis. Crop Sci. 56 , 2802–2817 (2016).

Article   CAS   Google Scholar  

Light, M. A., Lenssen, A. W. & Elmore, R. W. Corn (Zea mays L.) seeding rate optimization in Iowa, USA. Precis. Agric. 18 , 452–469 (2016).

Gaspar, A. et al . Defining optimal soybean seeding rates and associated risk across North America. Agron. J. 1–12 (2020).

Andrade, J. et al. Assessing the influence of row spacing on soybean yield using experimental and producer survey data. Field Crops Res. 230 , 98–106 (2019).

Lobell, D. B. et al. The critical role of extreme heat for maize production in the United States. Nat. Clim. Change 3 , 497–501 (2013).

Lobell, D. B. & Field, C. B. Global scale climate–crop yield relationships and the impacts of recent warming. Environ. Res. Lett. 2 , 014002 (2007).

Schlenker, W. & Roberts, M. J. Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc. Natl. Acad. Sci. 106 , 15594–15598 (2009).

Hochman, Z. et al. Re-inventing model-based decision support with Australian dryland farmers. 4. Yield prophet (R) helps farmers monitor and manage crops in a variable climate. Crop Pasture Sci. 60 , 1057–1070 (2009).

Sadras, V. O. & Densison, R. F. Neither crop genetics nor crop management can be optimized. Field Crops Res. 189 , 75–83 (2016).

Khaki, S. & Wang, L. Crop yield prediction using deep neural networks. Front. Plant Sci. 10 , 621 (2019).

Khaki, S., Wang, L. & Archontoulis, S. V. A CNN-RNN framework for crop yield prediction. Front. Plant Sci. 10 , 1750 (2020).

Websites for each state-specific university variety trial can be found in Table S10 in supplementary material.

Thornton, P.E. et al. Daymet: Daily surface weather data on a 1-km grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1328 (2016).

Mourtzinis, S., Rattalino Edreira, J. I., Conley, S. P. & Grassini, P. From grid to field: assessing quality of gridded weather data for agricultural applications. Eur. J. Agron. 82 , 163–172 (2017).

Chen, T. & Guestrin, C. XGBoost: A Scalable tree boosting system. arXiv:1603.02754v3 (2016).

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Acknowledgements

The authors thank Adam Roth and multiple students for their help in database development and John Gaska for constructing Fig. 1 . This research was funded in part by the Wisconsin Soybean Marketing Board, The North Central Soybean Research Program (S.P. Conley), and the USDA National Institute of Food and Federal Appropriations under Project PEN04660 and Accession number 1016474 (P.D. Esker).

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Spyridon Mourtzinis

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Paul D. Esker

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S.M. conceived the idea, analyzed the data, and wrote the paper. P.D.E and J.E.S. contributed to idea development, reviewed results, and provided revisions for improvement of the manuscript. S.P.C. contributed to the data set and idea development, reviewed results, and commented on the manuscript.

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Mourtzinis, S., Esker, P.D., Specht, J.E. et al. Advancing agricultural research using machine learning algorithms. Sci Rep 11 , 17879 (2021). https://doi.org/10.1038/s41598-021-97380-7

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• JCR Impact Factor: 11.8 , Top 4% (SCI Q1) CiteScore: 17.6 , Top 3% (Q1) Google Scholar h5-index: 77， TOP 5

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

Doi:  10.1109/jas.2021.1003925.

• Othmane Friha 1 ,  , 
• Mohamed Amine Ferrag 2 ,  , 
• Lei Shu 3, 4 ,  ,  , 
• Leandros Maglaras 5 ,  , 
• Xiaochan Wang 6 , 

Networks and Systems Laboratory, University of Badji Mokhtar-Annaba, Annaba 23000, Algeria

Department of Computer Science, Guelma University, Gulema 24000, Algeria

College of Engineering, Nanjing Agricultural University, Nanjing 210095, China

School of Engineering, University of Lincoln, Lincoln LN67TS, UK

School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK

Department of Electrical Engineering, Nanjing Agricultural University, Nanjing 210095, China

Othmane Friha received the master degree in computer science from Badji Mokhtar-Annaba University, Algeria, in 2018. He is currently working toward the Ph.D. degree in the University of Badji Mokhtar-Annaba, Algeria. His current research interests include network and computer security, internet of things (IoT), and applied cryptography

Mohamed Amine Ferrag received the bachelor degree (June, 2008), master degree (June, 2010), Ph.D. degree (June, 2014), HDR degree (April, 2019) from Badji Mokhtar-Annaba University, Algeria, all in computer science. Since October 2014, he is a Senior Lecturer at the Department of Computer Science, Guelma University, Algeria. Since July 2019, he is a Visiting Senior Researcher, NAULincoln Joint Research Center of Intelligent Engineering, Nanjing Agricultural University. His research interests include wireless network security, network coding security, and applied cryptography. He is featured in Stanford University’s list of the world’s Top 2% Scientists for the year 2019. He has been conducting several research projects with international collaborations on these topics. He has published more than 60 papers in international journals and conferences in the above areas. Some of his research findings are published in top-cited journals, such as the IEEE Communications Surveys and Tutorials , IEEE Internet of Things Journal , IEEE Transactions on Engineering Management , IEEE Access , Journal of Information Security and Applications (Elsevier), Transactions on Emerging Telecommunications Technologies (Wiley), Telecommunication Systems (Springer), International Journal of Communication Systems (Wiley), Sustainable Cities and Society (Elsevier), Security and Communication Networks (Wiley), and Journal of Network and Computer Applications (Elsevier). He has participated in many international conferences worldwide, and has been granted short-term research visitor internships to many renowned universities including, De Montfort University, UK, and Istanbul Technical University, Turkey. He is currently serving on various editorial positions such as Editorial Board Member in Journals (Indexed SCI and Scopus) such as, IET Networks and International Journal of Internet Technology and Secured Transactions (Inderscience Publishers)

Lei Shu (M’07–SM’15) received the B.S. degree in computer science from South Central University for Nationalities in 2002, and the M.S. degree in computer engineering from Kyung Hee University, South Korea, in 2005, and the Ph.D. degree from the Digital Enterprise Research Institute, National University of Ireland, Ireland, in 2010. Until 2012, he was a Specially Assigned Researcher with the Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University, Japan. He is currently a Distinguished Professor with Nanjing Agricultural University and a Lincoln Professor with the University of Lincoln, U.K. He is also the Director of the NAU-Lincoln Joint Research Center of Intelligent Engineering. He has published over 400 papers in related conferences, journals, and books in the areas of sensor networks and internet of things (IoT). His current H-index is 54 and i10-index is 197 in Google Scholar Citation. His current research interests include wireless sensor networks and IoT. He has also served as a TPC Member for more than 150 conferences, such as ICDCS, DCOSS, MASS, ICC, GLOBECOM, ICCCN, WCNC, and ISCC. He was a Recipient of the 2014 Top Level Talents in Sailing Plan of Guangdong Province, China, the 2015 Outstanding Young Professor of Guangdong Province, and the GLOBECOM 2010, ICC 2013, ComManTel 2014, WICON 2016, SigTelCom 2017 Best Paper Awards, the 2017 and 2018 IEEE Systems Journal Best Paper Awards, the 2017 Journal of Network and Computer Applications Best Research Paper Award, and the Outstanding Associate Editor Award of 2017, and the 2018 IEEE ACCESS. He has also served over 50 various Co-Chair for international conferences/workshops, such as IWCMC, ICC, ISCC, ICNC, Chinacom, especially the Symposium Co-Chair for IWCMC 2012, ICC 2012, the General Co-Chair for Chinacom 2014, Qshine 2015, Collaboratecom 2017, DependSys 2018, and SCI 2019, the TPC Chair for InisCom 2015, NCCA 2015, WICON 2016, NCCA 2016, Chinacom 2017, InisCom 2017, WMNC 2017, and NCCA 2018

Leandros Maglaras (SM’15) received the B.Sc. degree from Aristotle University of Thessaloniki, Greece, in 1998, M.Sc. in industrial production and management from University of Thessaly in 2004, and M.Sc. and Ph.D. degrees in electrical & computer engineering from University of Volos in 2008 and 2014, respectively. He is the Head of the National Cyber Security Authority of Greece and a Visiting Lecturer in the School of Computer Science and Informatics at the De Montfort University, U.K. He serves on the Editorial Board of several International peer-reviewed journals such as IEEE Access , Wiley Journal on Security & Communication Networks , EAI Transactions on e-Learning and EAI Transactions on Industrial Networks and Intelligent Systems . He is an author of more than 80 papers in scientific magazines and conferences and is a Senior Member of IEEE. His research interests include wireless sensor networks and vehicular ad hoc networks

Xiaochan Wang is currently a Professor in the Department of Electrical Engineering at Nanjing Agricultural University. His main research fields include intelligent equipment for horticulture and intelligent measurement and control. He is an ASABE Member, and the Vice Director of CSAM (Chinese Society for Agricultural Machinery), and also the Senior Member of Chinese Society of Agricultural Engineering. He was awarded the Second Prize of Science and Technology Invention by the Ministry of Education (2016) and the Advanced Worker for Chinese Society of Agricultural Engineering (2012), and he also gotten the “Blue Project” in Jiangsu province young and middle-aged academic leaders (2010)

• Corresponding author: Lei Shu, e-mail: [email protected]
• Revised Date: 2020-11-25
• Accepted Date: 2020-12-30
• Agricultural internet of things (IoT) , 
• internet of things (IoT) , 
• smart agriculture , 
• smart farming , 
• sustainable agriculture

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通讯作者: 陈斌, [email protected].

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• We provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs.
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• Figure 1. The four agricultural revolutions
• Figure 2. Survey structure
• Figure 3. IoT-connected smart agriculture sensors enable the IoT
• Figure 4. The architecture of a typical IoT sensor node
• Figure 5. Fog computing-based agricultural IoT
• Figure 6. SDN/NFV architecture for smart agriculture
• Figure 7. Classification of IoT applications for smart agriculture
• Figure 8. Greenhouse system [ 101 ]
• Figure 9. Aerial-ground robotics system [ 67 ]
• Figure 10. Photovoltaic agri-IoT schematic diagram [ 251 ]
• Figure 11. Smart dairy farming system [ 254 ]
• Figure 12. IoT-based solar insecticidal lamp [ 256 ], [ 257 ]

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Department of Electrical and Electronic Engineering

Electronic engineering for agriculture

Integrating sensors, electronics, control, power systems and ICT engineering into agriculture is a key enabler for delivering improved food supply and sustainable energy production without increased burden on the limited fertile land-bank.

Key researchers

• Bruce Grieve  (Theme Leader)
• Richard Bardgett
• Helen Downie
• Patrick Gaydecki
• David Johnson
• Giles Johnson
• Peter Martin
• Clare Mills
• Michael O'Toole
• Krikor Ozanyan
• James Winterburn

This exploitation of non-traditional technologies to improve global farming is particularly timely given the projected growth in the world population.

The introduction of electronics in agriculture technologies into Agri-Food research, products and services requires new academic partnerships to be fostered across the University and elsewhere.

The activity is managed by a cross-disciplinary, industry and academic steering team that will also be tasked with delivering the longer term e-Agri strategy.

We are currently part of the following major projects:

• The N8 AgriFood programme
• The Global Food Security 'IKnowFood' project
• The STFC Food Network+

Key research topics

• Sensing above the crop: Hyper-weeding - on tractor hyperspectral sensors for high-speed detection and eradication of weeds
• Sensing below the roots: Low-cost networked soil moisture sensors to dynamically map the fluxes in moisture across field
• Sensing post harvest: The science behind 'sell by dates' - plastic electronic thermal sensors for printable RFIDs to track the perishable goods in the supply chain.

About e-Agri Manchester

This theme has the strategic aim of informing the electronics community of the needs of modern agronomy and food science to enable engineering of new systems and 'e'-devices for reducing waste, increasing yields and improving nutrition. Achievements include the establishment of the Syngenta University Innovation Centre, contribution to the Sustainable Agri-Food panel (Westminster, June 2011) and, with Syngenta and the BBSRC Rothamsted Research Centre, the first-ever successful demonstration in 2013 of a viable wireless sensor for fungal pathogens including Sclerotinia sclerotiorum - the most economically significant monocyclic crop disease in northern Europe.

Integrating sensors, electronics, control, power systems and ICT engineering into agriculture is a key enabler for delivering improved food supply and sustainable energy production without increased burden on the limited fertile land-bank. This exploitation of non-traditional technologies to improve global farming is extremely timely. In addition to climate change and overpopulation, the westernisation of world diets is producing even greater pressure on agriculture - approximately seven kg of grain is required to produce one kg of meat. Many of the benefits of fertilisation, irrigation and seed selection have already been realised and a new impetus is required to deliver the necessary yield improvements.

We believe that this impetus will come from sensor and ICT based control processes applied to agricultural processes. Electronics in agriculture research addresses the needs and problems of all stakeholders in the agriculture sector, from the farm to the shop: farmers and growers, seed and chemical providers, food logistics providers, agricultural machinery and equipment providers, food processors, suppliers and wholesalers and retailers. For each of these stakeholder groups, sensing and ICTs offer benefits to improve practices, raise yields, reduce costs, raise profit margins, secure food supplies and address the sustainability of the sector.

The vision of e-Agri is to look at the basics of farming and to understand what we actually need to be doing in order to deliver some solutions to the farming and food supply chain community.

We communicate with the farmers, plant scientists and genetics scientists to understand what they are trying to achieve and then re-engineer the basic devices. Therefore our intention is not to make some piece of equipment that sits in the lab doing detailed analysis; instead we hope to achieve a very different way of sensing directly in the fields. As sensing or controlling directly in the fields provides less specific and a much wider range of data, it tells more information about the fields and we believe this is the key to solve the growing food demand.

We partner up with all the enabling disciplines in the physical sciences band to get in-depth knowledge of a system.

We then as electronic engineers perform the work of an integrator - so basically putting together smart technologies together, be it a control system for robotics units that go around the field harvesting or a smart sensor built inside the smartphones that can pick up crop features/disease. The mission is to produce disruptive technologies - that is, the technologies that will actually make a difference in addressing the global challenges and assist the developing economies, especially the smallholder famers.

Coffee from advanced fermentation, engineering and sensing

Coffee production is of great economic importance in Colombia, and particularly in the Department of Huila. In 2013 over 77,000 families in the Department were registered as coffee 'micro-entrepreneurs' producing higher-added value specialty-coffees, principally for export. As a consequence, one in 14 of the total Huila population is currently directly reliant on specialty coffee production. Still there is vast unemployment, particularly among young people who have been inordinately affected by violence in the region over the past decades. Opportunities for talented young people to become coffee entrepreneurs and further improve the region's coffee-producing capabilities could provide a lifeline out of poverty and illegal activities.

Project aims

The coffee from advanced fermentation, engineering and sensing (CAFES) project identified parts of the coffee production system that could be improved by implementing evidence based monitoring and control. The fermentation of coffee cherries and subsequent drying of the coffee beans is often carried out by farmers and little was known about how the fermentation period might affect the taste and quality of the final product. The Institutional Links collaboration bringing together the agronomy and instrumentation engineering disciplines within Universidad SurColombiana and Universidad de los Andes, with the agri-sensor systems, analytical and process engineering capabilities in The University of Manchester allowed us to investigate how controlling on-farm fermentation affects the final coffee taste. This knowledge will help to produce low-cost sensors, basic equipment and training materials that could be used on farms to improve the quality of the final product, reduce waste and increase profit.

Future work

We are working to continue the development of the local coffee research centre and to advance the skills of local coffee farmers. The eventual aim is to achieve a fully transparent, traceable coffee supply chain from crop to cup, providing specialty, high-quality coffee to the emerging artisan coffee market in a way that empowers the producers.

Crop disease detection for smallholder farmers

E-agri in developing countries.

This concerns applying close-proximity hyperspectral imaging of the early onset of crop diseases to minimise preventable losses in emerging food production via the application of contemporary concepts into a new low-cost mobile attachment.

There is a significant yield gap for agricultural crops in developing countries versus those in the west, where mechanisation and agricultural technologies have a far greater adoption. Pest and fungal disease can have a significant impact on these yields and overall profitability, resulting in many cases to adversely affected livelihoods due to poor decision making in the lack of effective knowledge.

Paired with a rising uptake of new inexpensive smartphones in the developing market, due to availability and farming trade information access, this makes for an exceptional framework on which to develop new technologies to better manage fungal and bacterial diseases that may reduce future harvests.

The challenges

It can be very difficult to correctly identify the infiltration and spread of a fungal pathogen in time to prevent major economic impact. Given the scale and diversity of crops, varieties and diseases, even the most experienced of farmers can incorrectly diagnose. This typically results in one of two negative outcomes:

• scheduled pesticide spraying where it is not needed;
• late spraying to minimise yield loss.

With an automated diagnosis compared against a growing database of known pests/pathogens, this problem could be resolved. However, it would be impracticable to develop the breadth of data in laboratories to be able to effectively diagnose in the field. Therefore initial trials using a data mining version would be necessary, both initially and periodically, to update the results.

Smartphone to fight crop disease

Supported by EPSRC, the Department of Electrical and Electronic Engineering is partnering with a small Anglo-Indian company, Barefoot Lightning Ltd (BfL) , to develop a very low-cost sensor system for close-proximity hyperspectral imaging of the early onset of crop diseases.

It is closely linked with the work done in conjunction with the University of Bonn, where we managed to replicate results by replacing a high-cost spectrometer with low-cost narrow band emitters.

How it works

A low-cost tool will be able to scan for disease signatures, ie spectral and spatial signals, and the results compared against known values.

In the field it can be put in the hands of field extension workers, semi-technical staff employed by agronomy companies, NGOs and/or regional government bodies.

Extension workers may then scan plants for disease signals already stored in BfL's libraries or, where new disease signals are found, they can be added to the libraries, thus enabling BfL to build up the database and simultaneously providing an early warning system.

BfL will also make use of the same technology to look for plant disorders such as nutrient deficiencies, so creating a high-value dataset relating crop-stress to hyperspectral data, which may then be exploited further by academic groups and/or marketed to agronomy companies.

Other applications

Disease signals expanded libraries can also then be used in the simpler 'farmer versions' to allow them to search for early warning signs of disease in their fields.

BfL will also make use of the same technology to look for plant disorders such as nutrient deficiencies, so creating a high-value dataset relating crop-stress to hyperspectral image data. The latter may then be exploited further by academic groups and/or marketed to agronomy companies.

Future development

Although the pilot market is in India due to existing industrial infrastructure, the smartphone based technology has the potential to impact global farming communities, food supply and even animal wellbeing.

In particular the e-Agri team is looking into extending the sensors for use in plant virus control in Sub-Saharan African cassava farming, alongside colleagues in the University of Greenwich and the Bill and Melinda Gates Foundation.

Broader implications for animal and human health assessment are also being developed, notably with the University of Liverpool and the University of Leeds. In the longer term there are plans to bring the technology into the hands of growers in the UK to help the growing community of home producers of food.

The opportunities are very broad and the team is always working on new ideas.

The E-Agri Sensors Centre

Since its formation in November 2000 from the merger of the AstraZeneca and Novartis crop science businesses, the e-Agri Sensors Centre has significantly refocused its research activities to meet the projected needs of agriculture and food supply. In light of this a number of strategic enabling technologies have been identified that can facilitate innovative new approaches to crop growth and non-mammalian biotechnology. Sensor science is one of these technologies identified as having the capacity to create a paradigm shift in the future of the sector. To realise this potential the e-Agri Sensors Centre model has been developed.

The Centre has been strategically domiciled within a university environment so as to nurture and translate the underpinning sciences (from across the physical and life-sciences interfaces) that will be required to deliver future agricultural products and services. The Centre is based within the Department of Electrical and Electronic Engineering in the Faculty of Science and Engineering, but is necessarily multidisciplinary owing to the nature of the techniques being researched.

Research aims

The e-Agri Sensors Centre is researching sensing systems and information communications technologies for agriculture and farming, but with a central focus on sensors and knowledge-based approaches to support agriculture and farming of the future. Within this remit, the Centre is working in several areas, including:

• new sensing technologies;
• wireless sensor network;
• energy harvesting;
• information and knowledge management.

The Centre has a strategic interest in defining the ICT infrastructure and platforms for farming and agriculture, and identifying the actions and research necessary to bring about the realisation of this ICT infrastructure. The Centre is also interested in the farm-to-fork supply chain and how the technologies of interest can help to improve food quality and reduce environmental burdens.

Significant achievements

• Delivered the first commercial networked crop-disease biosensor
• Created the e-Agri brand and hosted the landscaping event, led by the UK Chief Government Scientist

Early clubroot identification

Clubroot (Plasmodiophora brassicae) is an important pathogen of Brassica crops including oil seed rape (OSR), both in the UK and worldwide. Clubroot infection occurs via root hair penetration (primary infection) and root cortex invasion (secondary infection), and leads into typical above and below-ground disease symptoms.

Infected plants develop large galls in the root system while above-ground symptoms include wilting, stunting, chlorosis, premature senescence and, in severe cases, death. All symptoms are caused through gradual changes in primary and secondary host metabolism, alterations in cambial stem cell maintenance and differentiation, and perturbations of vascular development with reduction in xylogenesis.

The aim of the project is to use EIT to directly measure below-ground responses as a complementary method of identifying quantitative resistance to clubroot infection in Brassica crops. Infection leads to an inhibition of lateral root formation, repression of xylogenesis, a localised induction of vascular cambium activity leading to gall formation and altered water relationships, all of which can potentially be measured and quantified using EIT.

Project applications

The existing technology is to take X-ray images of the roots. This technology is fairly accurate, however it is very expensive and out of reach for most farmers. Thus the idea is to build a technology that is relatively cheap, thereby allowing all the dominions of the farming community to tap into this technology and detect/eliminate club roots at an earlier stage.

Polymer sensors for remote nutrient detection in agriculture

Project aim.

The aim of the research is to produce biomimetic polymer sensors that can be used in a remote monitoring system to quickly and selectively detect the concentration of in-field macronutrients (such as phosphates and nitrates) in soils and aqueous growth media.

Research applications

This is of significant interest within the food and agriculture sector as it has the potential to provide agronomists with a rapid, simple-to-use and cost-effective alternative to traditional laboratory techniques for the precise measurement of nutrient concentrations in growth media and soils.

The research at The University of Manchester is focusing on producing a novel sensor system for use in hydroponics, so as to provide a measurement and feedback system. This aims to carefully monitor and control the dosing of nutrients into the growth media, and thus provide the conditions for an optimal crop yield.

Future works

The polymer material is being continuously optimised to suit the target analyte, and the reusability and robustness of the synthetic films is of significant interest. Producing a reversible polymer sensor that can produce multiple readings would be of significant interest, allowing for further automation of a monitoring system.

Reusable nutrient sensors in commercial hydroponic farming

Nutrient sensors are used to control phosphates and nitrates levels; molecularly imprinted polymer sensors for the detection of macronutrients in agriculture.

The polymer material is being continuously optimised to suit the target analyte, and the reusability and robustness of the synthetic films is of significant interest.

Producing a reversible polymer sensor that can produce multiple readings would be of significant interest, allowing for further automation of a monitoring system.

Applications

Industrial partners.

• Saturn Bioponics

A series of videos explaining the research we carry out is available on the e-Agri YouTube channel  and more information is available through our Agrifood Twitter  account.

Areas of expertise

Autonomous systems

We develop innovative scientific methods that lead to technologies requiring minimal human intervention.

Communications

We work on multidisciplinary approaches to problems in highly mobile communications, cognitive radio, RF and more.

Control systems

Our work focuses on the development of control design methods and process monitoring and diagnostics.

Digital signal processing

We make sensor instrumentation and algorithms for extracting information from raw data.

Electronic devices

Our work spans the modelling and synthesis of atomic layer thin films using Molecular Beam Epitaxy.

Mechatronics

We specialise in electromechanical technologies for renewable energy systems and electric vehicles.

Our researchers work across all areas of photonics, including the development of new advanced materials.

Sensors and sensing systems

Our work includes developing new sensors and designing systems and integration tools.

Systems integration

We work on systems integration across all levels, from low-power applications to high voltage systems.

Our facilities

Our research benefits from the Department's excellent range of modern facilities.

Research outputs

Find our recent publications in the University's database.

See the PhD research opportunities we have across the Department.

UKnowledge > Martin-Gatton College of Agriculture, Food and Environment > Biosystems and Agricultural Engineering > Theses & Dissertations

Theses and Dissertations--Biosystems and Agricultural Engineering

Theses/dissertations from 2024 2024.

Precision Application of Water to Equine Racing Surfaces , Sydney Rae Cannon

Implications of Nanopesticides on Downstream Wetland Ecosystems , Kiley Power

WETLAND TREATMENT SYSTEMS FOR MUNICIPAL WASTEWATER AT A BOURBON DISTILLERY AND POTENTIAL VALUE OF INCORPORATING STILLAGE FOR WATER TREATMENT ENHANCEMENT , Katherine J. Ristola

The Characterization, Assessment, and Shear Strength of Turfgrass Soil in North American Thoroughbred Racing , Peter Schmitt

Development of Lignin Derived Hydrophobic Deep Eutectic Solvents as Sustainable Solvents and Their Applications , Yuxuan Zhang

Theses/Dissertations from 2023 2023

LIFE CYCLE ASSESSMENT OF AIR CLASSIFICATION AS A SULFUR MITIGATION TECHNOLOGY IN PINE RESIDUE FEEDSTOCKS , Ashlee Edmonson

IMPACT OF PHYSICOCHEMICAL CHARACTERISTICS AND DISTILLATION PARAMETERS ON THE BIOMETHANE POTENTIAL OF BOURBON STILLAGE , Danielle Hockensmith

APPLYING HERMETIC STORAGE AND MULTIPLE ABIOTIC-STRESSED GERMINATIONS TO ACTUATE DESIRABLE EFFECTS IN WHEAT PHYTOCHEMISTRY, FOOD, AND BIOLOGICAL FUNCTIONALITIES , Bababode Kehinde

UNMANNED AIRCRAFT SYSTEMS FOR PRECISION METEOROLOGY: AN ANALYSIS OF GNSS POSITION MEASUREMENT ERROR AND EMBEDDED SENSOR DEVELOPMENT , Karla S. Ladino

A PROCESS INTENSIFICATION APPROACH TO IMPROVE VOLATILE FATTY ACIDS PRODUCTION, EXTRACTION, AND VALORIZATION , Can Liu

Densification of Hemp Floral Biomass Pre and Post-Extraction: Determination of Pellet Physical Characteristics , Gary Lopez

Improving Indoor Arenas for the Equine Industry , Staci McGill

Nanopesticide Influence on Nitrogen Cycling in Soils , Jacob Richardson

FATE AND TRANSPORT OF NANOPESTICIDES IN AGRICULTURAL FIELD PLOTS IN CENTRAL KENTUCKY , William D. Rud

Fate and Transport of Emerging Contaminants Entering, Leaving, and Flowing Past Wastewater Treatment Plants in Central Kentucky , Kyra Sigler

Microalgae Immobilization with Filamentous Fungi: Process Development for Sustainable Food Systems , Suvro Talukdar

Theses/Dissertations from 2022 2022

The Response of Beef Cattle to Disturbances from Unmanned Aerial Vehicles (UAVs) , Gabriel Abdulai

EXPLORATION OF LIGNIN-BASED SUPERABSORBENT POLYMERS (HYDROGELS) FOR SOIL WATER MANAGEMENT AND AS A CARRIER FOR DELIVERING RHIZOBIUM SPP. , Toby Adjuik

Classifying and Mapping Aquatic Vegetation in Heterogeneous Stream Ecosystems Using Visible and Multispectral UAV Imagery , Rozalia Agioutanti

USING STREAM RESTORATION TO MITIGATE STORMWATER RUNOFF IN AN URBAN WATERSHED: A CASE STUDY , Jonathan M. Brantley

SEDIMENT NITROGEN DYNAMICS IN BACKWATER WETLAND CONFLUENCES OF A REGULATED RIVER , Gina DeGraves

Nondestructive Multivariate Classification of Codling Moth Infested Apples Using Machine Learning and Sensor Fusion , Nader Ekramirad

Assessing Machine Learning Utility in Predicting Hydrologic and Nitrate Dynamics in Karst Agroecosystems , Timothy McGill

LIGNIN VALORIZATION VIA REDUCTIVE DEPOLYMERIZATION USING PROMOTED NICKEL CATALYSTS AND SUB- AND SUPERCRITICAL METHANOL , Julia Parker

IMPLICATIONS TO TAP AND STREAM WATER CHEMISTRY DUE TO VARIATIONS IN SAMPLING LOCATIONS AND WATERSHED LAND USE , Dayana Rodriguez

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130 Agriculture Research Topics To Write An Excellent Paper

The preparation of an agriculture research paper involves several nuances and complexities. The first aspect is technical requirements, such as text formatting, structure, and source list. It's also important to choose those agriculture topics that you can analyze and find expert material. Any research paper is based on theses and statements, which are supported by evidence and factual information.

This is especially important when you tend to choose agricultural controversial topics. Then you need to find studies with verified information and prepare arguments for your paper. The whole process of work requires meticulous data collection and analysis of alternative sources. Then choosing any agricultural essay topics won't seem like a heady decision.

Your academic paper may relate to environmental factors, the economic feasibility of starting a farm, or the nuances of breeding. The main plus is that you can choose any of the agricultural related topics for research preparation. Here are 130 options for you.

Fisheries And Aquaculture

Such agricultural research paper topics allow revealing the topic of fishery and agricultural procurement. Students can concentrate on many aspects of the payback of farms and fisheries. The topics are quite extensive, and you can find a lot of research on the Internet for choosing trust sources.

• Trout breeding in freshwaters.
• Effect of algae on oxygen levels in fish rates.
• Seasonal spawning of oceanic fish.
• Prohibited fishing waters in the United States.
• Exploration of the Pacific Ocean.
• The impact of cyclones on fishing.
• Poisonous fish and the reasons for their breeding in North America.
• Seasonal diseases of trout.
• Sea horse: A case study.
• Risk analysis of water quality in aquaculture.

Plant Science And Crop Production

Crop Production agricultural research topics and plant science are not the easiest, but they contain a ton of information on the Internet. It is not a problem to find research by leading scientists and create your own research paper based on their statistics. The plus is that you don't have to start from scratch.

• Innovative plant breeding.
• Reclamation as a method of increasing yields.
• Hybrid plants of Montana.
• Citrus growing methods.
• Technical cannabis and plantations in the USA.
• Analysis of the yield of leguminous crops.
• Method for creating genetically modified plants.
• Field analysis of wheat for pesticides.
• New plants and methods of growing them.
• Hybrids and cold-resistant plants.

Topics in Agricultural Science

Agriculture essay topics like this allow you to select a specific aspect to research. You can concentrate on vegetation breeding or high tech greenhouse methodology. A large amount of research is a definite plus because you can build your theses on the basis of available data, criticizing or supporting research by scientists.

• Harvesting robots.
• Methodology for improving agricultural performance.
• The influence of technology on the growth of grain crops.
• How important is the timely irrigation of fields?
• Climatic changes and impact on yield.
• Breeding earthworms.
• Hydroponic gardening.
• Genetically modified organisms and their distribution.
• Starting a garden.
• How can we make medicine from plants?

Topics in Agronomy

Agronomy agriculture projects for students allow you to consider the aspects of growing crops in conditions with a specific soil type and natural characteristics. You can base your claims on statistics with the ability to draw on facts from other research. For example, this is relevant for papers examining the fertility of the topsoil.

• Choosing the type of soil for the cornfield.
• Innovative land reclamation.
• New branches in agronomy.
• Phosphate-free fertilizers.
• Hydroponics and greenhouses.
• Hybrid yield analysis.
• Methodology for assessing agronomic losses.
• Stages of preparing a field for harvesting.
• The role of GMOs in the fight against insect pests.
• Cultivation of technical hemp and soil fertilization methods.

Topics in Animal Breeding And Genetics

Agriculture related topics are interesting because you can touch on aspects of genetics and breeding. Students can concentrate on specific aspects of species modification and animal rearing. The research paper will look more convincing when there are references to real scientific papers with statistics and experimental results.

• Breeding new types of sheep.
• Breeding bulls and genetic engineering.
• The influence of selection on the growth of the animal population.
• Proper nutrition for livestock in winter.
• Vitamin complexes for animals.
• Genetic changes in chickens for resistance to cold.
• Nuances of animal genetic modifications.
• Stages of caring for newborn kittens.
• What is a negative selection?
• Basic methods of genetic experiments on animals.

Topics in Animal Production And Health

Such agriculture research paper topics are especially interesting because you can write about farming aspects in the context of raising animals, vegetables, and various crops. It is broad enough, so you will not be limited by narrow boundaries and will be able to consider many aspects of your research paper.

• Environmental threats to the oversupply of the sheep population.
• The role of livestock in marginal areas.
• Livestock digitalization.
• Animal selection for meat preparation.
• Analysis of livestock farms.
• Animal production evaluation technique.
• Cow health during calving.
• The importance of animal vaccination.
• Technical aspects of the medical treatment of animals.
• Environmental aspects of animal husbandry.

Topics in Ecotourism And Wildlife

Ecotourism is gaining momentum all over the world. The new trend is aimed at bringing people closer to nature and exploring the beauty of different countries. This issue will be of interest to those who want to talk about wildlife and nature reserves. The topic is quite extensive, so students will not have problems with preparing a research paper.

• Minnesota and Eco-Tourism.
• The influence of wolves on the formation of the local ecosystem.
• Recreational tourism in the USA.
• Methods for preparing resorts for eco-tourism.
• Lakes and environmental factors.
• A technique for preserving wildlife in its original form.
• Classic models of eco-tourism.
• Stages of creating ecological reserves.
• The role of tourism in the restoration of the ecological environment.
• The main factors of wildlife conservation.
• The legislative framework for wildlife protection.
• The nuances of creating a farm in reserve.
• Consolidation of resources for the development of a livestock farm.

Topics in Farm Management

Managing a farm can be a complex and multifaceted process. Many students may choose this topic to talk about aspects of breeding and breeding pets or crops. The topic is quite extensive and allows you to touch on any aspect of the farmer's activities related to the production and sale of products.

• Farm methods to improve performance.
• Stages of creating a livestock farm.
• Farm success analysis forms.
• Management of the process of planting crops.
• The role of modern equipment in cow milking.
• Farm reporting and profitability analysis.
• Breeding exotic animals.
• Rabbit population management.
• Statistical methodology for farm control.
• Stages of the animal population control on the farm.

Topics in Fisheries And Aquaculture

A similar topic is associated with fish farming, introductory aquaculture, and general aquaculture. Quite a few students can prepare a good research paper if they turn to other people's research and use it as a basis to prove or disprove their own claims and theories. It is also a good opportunity to select food related research topics as you can touch upon the aspect of fish farming and marketing.

• Creation and management of a fish rate.
• Sturgeon breeding and distribution.
• Methods for improving the ecological state of water bodies.
• Planting plants in reservoirs for liquid purification.
• Fish spawning control.
• The aquaculture aspect and social trends.
• Methods for increasing fish resources.
• Breeding in the fishing industry.
• Methods for creating a fish farm.
• River resource monitoring and digitalization.

Topics in Agric Business And Financial Management

Control of a livestock or vegetable enterprise depends on many factors, so such a topic's choice will be extremely relevant. The student's most important task is to bring only proven facts and arguments of his own judgments. These agriculture topics for students include an overview of many business processes and farm management.

• The farm cost reduction methodology.
• US agricultural financing sector.
• Agricultural business practices.
• Data analysis and farming development.
• Financial management of small livestock farms.
• Impact of drought on yield.
• Cost and payback of farms.
• Selecting a region for creating a farm.
• A method for analyzing animal resources on a farm.
• Management of automated farming enterprises.
• Local farming business.
• Key factors of farm management.
• Farm reports and breeding work.

Topics in Agric Meteorology And Water Management

Meteorological aspects are very important for the management of a company or agricultural enterprises. Another aspect of this topic is water management, which may also be interesting for those who are going to reveal the nuances of fish farming in local waters. The topic will be especially interesting for those who want to connect their lives with agronomy and a similar field.

• Cattle breeding methodology.
• Pig breeding methods.
• Water management to maximize profits.
• The choice of a reservoir for growing fish.
• Analysis of the ecological situation in water bodies.
• Farm equipment management techniques.
• Water supply for farm households.
• Analysis and selection of a farm development methodology.
• Finding the right methods for creating protected reservoirs.
• Stages of development of a water farm.

Other Agric Topics

Sometimes choosing a specific topic can be difficult. This is because students are not quite sure which study to base their paper on. You can take a neutral topic that has no specific relation to breeding, meteorology, or farming aspects in such cases.

• Innovative farming methods.
• Choosing the right water farm management model.
• The nuances of trout breeding.
• Population control and livestock farm development plan.
• Financial analytics and purchase of farm animals.
• The self-sufficiency period of the fish farm.
• How to create fish spawning tanks?
• Selection of breeds of cows for farming.
• Methodology for calculating farm risks.
• Time management and selection of plants for the plantation.
• Features of the legal registration of a farm household.
• Modern agricultural drones.
• The difference between Ayn Rand's anthem and George Orwell's animal farm.
• Animal rights vs. animal welfare.

How to Write a Good Agriculture Research Paper?

One of the main life hacks for getting a high mark is choosing controversial agricultural topics. Choosing this option allows students to consider an interesting statement and back it up with real facts. A paper-based on real statistics with proof of student work is valued above all else.

But even when choosing a good topic, you still need to prepare the right outline for writing your research paper. The introduction should be of the highest quality as well as the final paragraph since these are the main parts that affect the assessment. Real facts and statistics must support all the statements above if you are talking about specific figures. Many colleges and universities have their own paper requirements as well as the nuances of the design of research work. You must consider each parameter in order to get the best result.

If it is difficult to find controversial topics in agriculture and write a high-quality research paper, we can help you with this issue. Our  best essay writing service has been in operation for many years and provides writing assistance for many types of essays, research papers, and theses. We will help you synchronize your preparation process and create an expert paper that gets high marks. You can switch to other tasks and get the opportunity to free up some time to study other disciplines.

An Inspiration List:

• Agricultural Research
• Current Agriculture Research Journal
• Agricultural Research & Technology
• Journal of Agriculture and Food Research
• Advances in Plants & Agriculture Research
• Journal of Bioscience and Agriculture Research
• Middle East Journal of Agriculture Research

Thesis Helpers

Find the best tips and advice to improve your writing. Or, have a top expert write your paper.

156 Hot Agriculture Research Topics For High Scoring Thesis

Are you preparing an agriculture research paper or dissertation on agriculture but stuck trying to pick the right topic? The title is very important because it determines how easy or otherwise the process of writing the thesis will be. However, this is never easy for many students, but you should not give up because we are here to offer some assistance. This post is a comprehensive list of the best 156 topics for agriculture projects for students. We will also outline what every part of a thesis should include. Keep reading and identify an interesting agriculture topic to use for your thesis paper. You can use the topics on agriculture as they are or change them a bit to suit your project preference.

What Is Agriculture?

Also referred to as farming, agriculture is the practice of growing crops and raising livestock. Agriculture extends to processing plants and animal products, their distribution and use. It is an essential part of local and global economies because it helps to feed people and supply raw materials for different industries.

The concept of agriculture is evolving pretty fast, with modern agronomy extending to complex technology. For example, plant breeding, agrochemicals, genetics, and relationship to emerging disasters, such as global warming, are also part of agriculture. For students studying agriculture, the diversity of the subject is a good thing, but it can also make selecting the right research paper, thesis, or dissertation topics a big challenge.

How To Write A Great Thesis: What Should You Include In Each Section?

If you are working on a thesis, it is prudent to start by understanding the main structure. In some cases, your college/ university professor or the department might provide a structure for it, but if it doesn’t, here is an outline:

• Thesis Topic This is the title of your paper, and it is important to pick something that is interesting. It should also have ample material for research.
• Introduction This takes the first chapter of a thesis paper, and you should use it to set the stage for the rest of the paper. This is the place to bring out the objective of the study, justification, and research problem. You also have to bring out your thesis statement.
• Literature Review This is the second chapter of a thesis statement and is used to demonstrate that you have comprehensively looked at what other scholars have done. You have to survey different resources, from books to journals and policy papers, on the topic under consideration.
• Methodology This chapter requires you to explain the methodology that was used for the study. It is crucial because the reader wants to know how you arrived at the results. You can opt to use qualitative, quantitative, or both methods.
• Results This chapter presents the results that you got after doing your study. Make sure to use different strategies, such as tables and graphs, to make it easy for readers to understand.
• Discussion This chapter evaluates the results gathered from the study. It helps the researcher to answer the main questions that he/she outlined in the first chapter. In some cases, the discussion can be merged with the results chapter.
• Conclusion This is the summary of the research paper. It demonstrates what the thesis contributed to the field of study. It also helps to approve or nullify the thesis adopted at the start of the paper.

Interesting Agriculture Related Topics

This list includes all the interesting topics in agriculture. You can take any topic and get it free:

• Food safety: Why is it a major policy issue for agriculture on the planet today?
• European agriculture in the period 1800-1900.
• What are the main food safety issues in modern agriculture? A case study of Asia.
• Comparing agri-related problems between Latin America and the United States.
• A closer look at the freedom in the countryside and impact on agriculture: A case study of Texas, United States.
• What are the impacts of globalisation on sustainable agriculture on the planet?
• European colonisation and impact on agriculture in Asia and Africa.
• A review of the top five agriculture technologies used in Israel to increase production.
• Water saving strategies and their impacts on agriculture.
• Homeland security: How is it related to agriculture in the United States?
• The impact of good agricultural practices on the health of a community.
• What are the main benefits of biotechnology?
• The Mayan society resilience: what was the role of agriculture?

Sustainable Agricultural Research Topics For Research

The list of topics for sustainable agriculture essays has been compiled by our editors and writers. This will impress any professor. Start writing now by choosing one of these topics:

• Cover cropping and its impact on agriculture.
• Agritourism in modern agriculture.
• review of the application of agroforestry in Europe.
• Comparing the impact of traditional agricultural practices on human health.
• Comparing equity in agriculture: A case study of Asia and Africa.
• What are the humane methods employed in pest management in Europe?
• A review of water management methods used in sustainable agriculture.
• Are the current methods used in agricultural production sufficient to feed the rapidly growing population?
• A review of crop rotation and its effects in countering pests in farming.
• Using sustainable agriculture to reduce soil erosion in agricultural fields.
• Comparing the use of organic and biological pesticides in increasing agricultural productivity.
• Transforming deserts into agricultural lands: A case study of Israel.
• The importance of maintaining healthy ecosystems in raising crop productivity.
• The role of agriculture in countering the problem of climate change.

Unique Agriculture Research Topics For Students

If students want to receive a high grade, they should choose topics with a more complicated nature.This list contains a variety of unique topics that can be used. You can choose from one of these options right now:

• Why large-scale farming is shifting to organic agriculture.
• What are the implications of groundwater pollution on agriculture?
• What are the pros and cons of raising factory farm chickens?
• Is it possible to optimise food production without using organic fertilisers?
• A review of the causes of declining agricultural productivity in African fields.
• The role of small-scale farming in promoting food sufficiency.
• The best eco-strategies for improving the productivity of land in Asia.
• Emerging concerns about agricultural production.
• The importance of insurance in countering crop failure in modern agriculture.
• Comparing agricultural policies for sustainable agriculture in China and India.
• Is agricultural technology advancing rapidly enough to feed the rapidly growing population?
• Reviewing the impact of culture on agricultural production: A case study of rice farming in Bangladesh.

Fun Agricultural Topics For Your Essay

This list has all the agricultural topics you won’t find anywhere else. It contains fun ideas for essay topics on agriculture that professors may find fascinating:

• Managing farm dams to support modern agriculture: What are the best practices?
• Native Americans’ history and agriculture.
• Agricultural methods used in Abu Dhabi.
• The history of agriculture: A closer look at the American West.
• What impacts do antibiotics have on farm animals?
• Should we promote organic food to increase food production?
• Analysing the impact of fish farming on agriculture: A case study of Japan.
• Smart farming in Germany: The impact of using drones in crop management.
• Comparing the farming regulations in California and Texas.
• Economics of pig farming for country farmers in the United States.
• Using solar energy in farming to reduce carbon footprint.
• Analysing the effectiveness of standards used to confine farm animals.

Technology And Agricultural Related Topics

As you can see, technology plays a significant role in agriculture today.You can now write about any of these technology-related topics in agriculture:

• A review of technology transformation in modern agriculture.
• Why digital technology is a game changer in agriculture.
• The impact of automation in modern agriculture.
• Data analysis and biology application in modern agriculture.
• Opportunities and challenges in food processing.
• Should artificial intelligence be made mandatory in all farms?
• Advanced food processing technologies in agriculture.
• What is the future of genetic engineering of agricultural crops?
• Is fertiliser a must-have for success in farming?
• Agricultural robots offer new hope for enhanced productivity.
• Gene editing in agriculture: Is it a benefit or harmful?
• Identify and trace the history of a specific technology and its application in agriculture today.
• What transformations were prompted by COVID-19 in the agricultural sector?
• Reviewing the best practices for pest management in agriculture.
• Analysing the impacts of different standards and policies for pest management in two countries of your choice on the globe.

Easy Agriculture Research Paper Topics

You may not want to spend too much time writing the paper. You have other things to accomplish. Look at this list of topics that are easy to write about in agriculture:

• Agricultural modernization and its impacts in third world countries.
• The role of human development in agriculture today.
• The use of foreign aid and its impacts on agriculture in Mozambique.
• The effect of hydroponics in agriculture.
• Comparing agriculture in the 20th and 21st centuries.
• Is it possible to engage in farming without water?
• Livestock owners should use farming methods that will not destroy forests.
• Subsistence farming versus commercial farming.
• Comparing the pros and cons of sustainable and organic agriculture.
• Is intensive farming the same as sustainable agriculture?
• A review of the leading agricultural practices in Latin America.
• Mechanisation of agriculture in Eastern Europe: A case study of Ukraine.
• Challenges facing livestock farming in Australia.
• Looking ahead: What is the future of livestock production for protein supply?

Emerging Agriculture Essay Topics

Emerging agriculture is an important part of modern life. Why not write an essay or research paper about one of these emerging agriculture topics?

• Does agriculture help in addressing inequality in society?
• Agricultural electric tractors: Is this a good idea?
• What ways can be employed to help Africa improve its agricultural productivity?
• Is education related to productivity in small-scale farming?
• Genome editing in agriculture: Discuss the pros and cons.
• Is group affiliation important in raising productivity in Centre Europe? A case study of Ukraine.
• The use of Agri-Nutrition programs to change gender norms.
• Mega-Farms: Are they the future of agriculture?
• Changes in agriculture in the next ten years: What should we anticipate?
• A review of the application of DNA fingerprinting in agriculture.
• Global market of agricultural products: Are non-exporters locked out of foreign markets for low productivity?
• Are production technologies related to agri-environmental programs more eco-efficient?
• Can agriculture support greenhouse mitigation?

Controversial Agricultural Project For Students

Our team of experts has searched for the most controversial topics in agriculture to write a thesis on. These topics are all original, so you’re already on your way towards getting bonus points from professors. However, the process of writing is sometimes not as easy as it seems, so dissertation writers for hire will help you to solve all the problems.

• Comparing the mechanisms of US and China agricultural markets: Which is better?
• Should we ban GMO in agriculture?
• Is vivisection a good application or a necessary evil?
• Agriculture is the backbone of modern Egypt.
• Should the use of harmful chemicals in agriculture be considered biological terror?
• How the health of our planet impacts the food supply networks.
• People should buy food that is only produced using sustainable methods.
• What are the benefits of using subsidies in agriculture? A case study of the United States.
• The agrarian protests: What were the main causes and impacts?
• What impact would a policy requiring 2/3 of a country to invest in agriculture have?
• Analysing the changes in agriculture over time: Why is feeding the world population today a challenge?

Persuasive Agriculture Project Topics

If you have difficulty writing a persuasive agricultural project and don’t know where to start, we can help. Here are some topics that will convince you to do a persuasive project on agriculture:

• What is the extent of the problem of soil degradation in the US?
• Comparing the rates of soil degradation in the United States and Africa.
• Employment in the agricultural sector: Can it be a major employer as the population grows?
• The process of genetic improvement for seeds: A case study of agriculture in Germany.
• The importance of potatoes in people’s diet today.
• Comparing sweet potato production in the US to China.
• What is the impact of corn production for ethanol production on food supply chains?
• A review of sustainable grazing methods used in the United States.
• Does urban proximity help improve efficiency in agriculture?
• Does agriculture create economic spillovers for local economies?
• Analysing the use of sprinkle drones in agriculture.
• The impact of e-commerce development on agriculture.
• Reviewing the agricultural policy in Italy.
• Climate change: What does it mean for agriculture in developed nations?

Advanced Agriculture Project Topics

A more difficult topic can help you impress your professor. It can earn you bonus points. Check out the latest list of advanced agricultural project topics:

• Analysing agricultural exposure to toxic metals: The case study of arsenic.
• Identifying the main areas for reforms in agriculture in the United States.
• Are developed countries obligated to help starving countries with food?
• World trade adjustments to emerging agricultural dynamics and climate change.
• Weather tracking and impacts on agriculture.
• Pesticides ban by EU and its impacts on agriculture in Asia and Africa.
• Traditional farming methods used to feed communities in winter: A case study of Mongolia.
• Comparing the agricultural policy of the EU to that of China.
• China grew faster after shifting from an agro to an industrial-based economy: Should more countries move away from agriculture to grow?
• What methods can be used to make agriculture more profitable in Africa?
• A comprehensive comparison of migratory and non-migratory crops.
• What are the impacts of mechanical weeding on soil structure and fertility?
• A review of the best strategies for restoring lost soil fertility in agricultural farmlands: A case study of Germany.

Engaging Agriculture Related Research Topics

When it comes to agriculture’s importance, there is so much to discuss. These engaging topics can help you get started in your research on agriculture:

• Agronomy versus horticultural crops: What are the main differences?
• Analysing the impact of climate change on the food supply networks.
• Meat processing laws in Germany.
• Plant parasites and their impacts in agri-production: A case study of India.
• Milk processing laws in Brazil.
• What is the extent of post-harvest losses on farming profits?
• Agri-supply chains and local food production: What is the relationship?
• Can insects help improve agriculture instead of harming it?
• The application of terraculture in agriculture: What are the main benefits?
• Vertical indoor farms.
• Should we be worried about the declining population of bees?
• Is organic food better than standard food?
• What are the benefits of taking fresh fruits and veggies?
• The impacts of over-farming on sustainability and soil quality.

Persuasive Research Topics in Agriculture

Do you need to write a paper on agriculture? Perfect! Here are the absolute best persuasive research topics in agriculture:

• Buying coffee produced by poor farmers to support them.
• The latest advances in drip irrigation application.
• GMO corn in North America.
• Global economic crises and impact on agriculture.
• Analysis of controversies on the use of chemical fertilisers.
• What challenges are facing modern agriculture in France?
• What are the negative impacts of cattle farms?
• A closer look at the economics behind sheep farming in New Zealand.
• The changing price of energy: How important is it for the local farms in the UK?
• A review of the changing demand for quality food in Europe.
• Wages for people working in agriculture.

Work With Experts To Get High Quality Thesis Paper

Once you pick the preferred topic of research, it is time to get down and start working on your thesis paper. If writing the paper is a challenge, do not hesitate to seek thesis help from our experts. We work with ENL writers who are educated in top universities. Therefore, you can trust them to carry out comprehensive research on your paper and deliver quality work to impress your supervisor. Students who come to us for assistance give a high rating to our writers after scoring top grades or emerging top in class. Our trustworthy experts can also help with other school assignments, thesis editing, and proofreading. We have simplified the process of placing orders so that every student can get assistance quickly and affordably. You only need to navigate to the ordering page to buy a custom thesis paper online.

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200+ Best Engineering Research Paper Topics in 2022

Team Desklib

Published: 2022-10-13

Since the dawn of humanity, there have been  engineering issues   and a need to solve them. Without technological understanding, ancient civilizations would not have been feasible because even then, enormous cities were being constructed with the aid of engineering principles.

This list of research issues aims to familiarise anyone interested in real-world engineering with specific scenarios that occur during practically any sort of professional activity of an engineer and call for ethical problem-level solutions.

You should first define the direction of engineering before beginning your research. You can locate an intriguing research topic in a variety of areas and subtopics. Students interested in history can learn more about engineering anthropology and comprehend this field's numerous phenomena and growth.

Genetic engineering might be a topic for those that enjoy biology. Additionally, any student is free to approach the teacher for suggestions on the most delicate subject matter.

You can choose the topic that will help you find a lot of useful technical information with the assistance of someone with years of experience.

There are many intriguing  engineering research paper   themes available in today's technologically advanced world. However, their diversity can also be an issue because it might be difficult to choose the proper one if you want to present high-quality work.

In this post, we provide a list of intriguing research paper topics for engineering students that are both simple to investigate and enjoyable to write about.

But before suggesting you some good engineering research topics we want to teach you how to choose engineering topics for your research paper.

The following procedures and advice will assist you in selecting the appropriate option from the list of options:

• If there isn't a list of suggested subjects, brainstorm ideas to come up with engaging engineering research topics that are pertinent to both your project and the industry as a whole.  
• Select a topic that you are familiar with because engineering topics can get very difficult; moreover, ensure that the topic you select is one that you can understand.  
• Ensure there are enough resources available on the topics; while writing an essay on a specialized subject can produce intriguing content, it can become too difficult if there aren't good information sources available.  
• Be open-minded while making your choice; instead of limiting yourself to topics you are familiar with, consider what will make your essay compelling and leave an impression on the grader.

The application of scientific principles is a  direct concern of engineering . Because of this, this field has several unique  characteristics that you cannot find elsewhere.

These are the engineering subjects that touch on them:

• Engineering education issues and suggestions for improvement
• The idea of engineering optimization
• Engineering, quality assurance
• Engineering measurement and data analysis specifics
• Utilizing optical techniques for engineering analysis
• Corrosion's impact on engineering
• Nanotechnology applications in contemporary engineering
• Value engineering and analysis
• AI and machine learning applications in engineering
• Engineering modeling techniques
• Engineering and upkeep
• Micromanufacturing and engineering
• Engineering advancements in Western culture
• Technical economy
• Engineering's theoretical underpinnings and their connection to science
• Engineering material specifics
• The design and administration of complex systems
• Reliability's significance in engineering
• Complex nuclear engineering issues
• The function of statistics and probability in engineering
• Trends in the creation of agricultural technology equipment.
• Technology in the food sector conserves energy and resources.
• Innovations in the food business that produces little or no waste.
• Food industry engineering in small businesses.
• The modern technosphere's high level of complexity and its extensive integration into societal life.
• Apparatus for heating up food bulk.
• Hardware for filling and presenting finished goods.
• Automation and mechanization of technological procedures in the food sector.
• Food industry construction products.
• Food industry production lines.
• Approaches to systems engineering.
• Theories for making an engineering-related career decision.
• Professional analysis of an engineer's education and activity.
• Professional competency is formed and developed during training.
• An engineer's design and engineering tasks.
• Engineering organization and management tasks.
• Engineering production and technological activities.
• Engineers and inventors from the United States and Europe (in the field of food production).
• Types of programs for engineering education.
• American and international engineering training systems integration

Top 8 Engineering Branches and Research Topics

• Engineering ethics-related research paper topics
• Genetic engineering research paper topics
• Biomedical engineering research paper topics
• Electrical engineering research paper topics
• Security engineering research paper topics
• Software engineering research paper topics
• Mechanical engineering research paper topics
• Civil engineering research paper topics

20 Best Engineering Ethics-related Research Paper Topics

• A set of moral guidelines that engineers use in their work.
• How might a moral engineer benefit society more?
• What moral ideals ought to guide engineering practice and research?
• What moral considerations ought every engineer to make before beginning their professional development?
• The conception of a product in accordance with all moral principles.
• Problems with ethics in the test and design areas.
• Ethical problems with goods and services. How can they be fixed?
• Moral dilemmas in leadership and collaboration.
• Obeying the law and ethical principles.
• What are the most crucial moral principles for engineers?
• How can an engineer maintain morality?
• Phases of a personality's growth professionally in engineering.
• Engineering ethics: What is it?
• How may engineering ethics be followed?
• The primary functions of engineering psychology and ergonomics.
• Why is a strong work ethic necessary in an organization?
• How does a strong work ethic help a company avoid many issues?
• Humanitarian knowledge's integration into engineering methods.
• How may human knowledge be related in many ways to technical thinking?
• The fundamentals of engineering ethics.

20 Best Genetic Engineering Research Paper Topics

• Genetic engineering and morality
• Genetic engineering's significance in modern agriculture
• Using genetic engineering to increase the production of biofuel
• One of the key tools for genetic engineering is CRISPR-Cas.
• Manufacture of antibiotics with genetic engineering
• The global politics of genetic engineering
• Genetic engineering: Myths and actual risks
• Genetic modification and organic food production
• Possibilities of combining conventional breeding with genetic engineering
• Utilizing genetic engineering to combat pollution
• Gene therapy in genetic engineering.
• How much of our genetic makeup is under our control, and when do we stop being human?
• What are the benefits of genetically modified organisms?
• Describe the advantages and disadvantages of genetic testing.
• What are epigenetics and its value?
• How to label food with genetically modified organisms?
• Use of genetically modified organisms in future farming.
• How can we involve nursing in genomics?
• Explain the genetic characteristics in humans having different traits like homosexuality.
• Food safety and guidelines for using genetically modified food products.

Top 20 Interesting Biomedical Engineering Research Paper Topics

• Research On Blood Resistivity-Based Blood Glucose Measurement
• Using Finite Element Analysis, A Hybrid Artificial Hip Joint Was Designed.
• Design Of A Clinical Engineering Department's Management Program With a Real-Time Planning System for Recognizing Heart Sounds
• Design of a Programmed Oxygen Delivery System Improvement: Adaptive Techniques for Cardiac Arrhythmia Detection Using Artificial Neural Networks By looking for a suitable activation function short message technique in health level 7, U-Net for MRI brain tumor segmentation (HL7)
• A Study of the Optical and Thermal Effects of Gold Nanoparticles for Magnetic Resonance Noise Reduction Image
• Analysis of Heart Rate Variability Using Statistical Techniques
• Reflexology for the Early Detection of Stomach Pain
• Central Medical Waste Treatment Facility Developing an Internet-Based Tele-Pediatric System
• Conducting polymers are used in biomedical engineering.
• The greatest successes in contemporary biomedical engineering
• IoT applications for biomedical engineering
• Engineering in biomedicine and 3D printing
• Carbon-based nanomaterials' significance for biomedical engineering
• Tactile sensing techniques and technologies
• Techniques for repairing damaged nerves with biomedical engineering
• Biomedical engineering uses X-rays, terahertz imaging, and spectrography for medical imaging.
• Potential of biological materials in biomedical engineering
• Piezoelectricity in systems for biomedical engineering
• Breast cancer can be detected by using artificial neural networks.
• Medical waste treatment equipment.

Best 30 Electrical Engineering Research Paper Topics

• Can general relativity affect the techniques used in electrical engineering?
• Electrical engineering and computer science integration
• Methods for electronic control in mechanical engineering
• Electrical engineering ideas of energy and information
• Engineering in electrical nonlinear optimization
• Dielectric materials that work best for electrical engineering
• Electrical engineering's differential progression
• Electrical circuits and quantum electrodynamics
• Optimization's advantages in electrical engineering
• Electrical engineering uses polymers and nanoparticles
• High-speed, high-power PM machines.
• Active voltage equalization using li-ion and supercapacitor cells connected in series.
• Direct drive in-wheel motor design choice.
• Inertia Motors.
• Nanoelectronics.
• Interaction engineering at the atomic level.
• Using silicon carbide, graphene, and photovoltaics.
• Ferroelectricity and piezoelectricity.
• Analyzing behavior using computer modeling.
• Computational research on novel materials and technologies.
• Powerful electronic devices and tools.
• Motors for electric vehicles and their redesign.
• Networks of energy and the mathematics supporting them.
• Engineering for electrical systems using computers.
• Monitoring for smart grids.
• Composites made of soft magnets.
• Gearboxes and motors for electric vehicles.
• Loss detection of grid events in distributed generating systems using pattern recognition
• Autonomous power system difficulties
• Hybrid electric aerospace.

Top 30 Security Engineering Research Paper Topics

• Patterns used in security engineering
• Cloud security engineering specifics
• Security design for distributed or complicated systems
• Engineering for privacy and security
• Security requirements analysis's significance
• Engineering security in the automobile sector
• Modeling and testing for security analysis
• A financial viewpoint on security engineering
• Flexible security measures
• Using attack graph models to improve network security
• the development of ransomware in the field of cybersecurity.
• Digital device denial-of-service attacks.
• the foundation of the global cybersecurity strategy.
• Network intrusion detection and remedies.
• How should the government deal with cybersecurity?
• A firewall's function in securing networks.
• the most typical closed weaknesses.
• After a data breach, what to do?
• Widespread spectrum sharing for communications in public safety.
• Digital security and downloaded materials
• How to efficiently use the Internet.
• Modern virus encryption technology.
• Investigating the importance of algorithm encryption.
• What is digital piracy?
• How to navigate the efficiency of the internet?
• Where do the vulnerabilities come from in a wireless mobile data exchange?
• Describe the evolution of Android malware.
• How to detect mobile phone hacking?
• Privacy and security issues come in chatbots.
• Cybersecurity and malware connection.

20 Interesting Software Engineering Research Paper Topics

• Software engineering economics
• Experimental software engineering techniques
• There are significant disparities between software engineering theory and practice.
• Software engineering role models
• Software engineering for industry
• Testing's significance in software engineering
• Collaborating when developing software
• Security through software engineering
• Problems with embedded software engineering
• Managerial techniques in software engineering
• Describe the distribution of anti-virus software.
• Suggest some software tools for qualitative research.
• Software development by data scientists.
• What is an agile software development process?
• The Capabilities of Compiere Software and How Well It Fits Into Different Industries.
• WBS completion and software project management.
• International Software Development's Ethical Challenges: User-Useful Software
• People with visual impairments face difficulties using assistive application software.
• Getting to the Ideal Process. Application Development
• Development of Software with IPR Violations.

Top 25 Mechanical Engineering Research Paper Topics

• Nonlinear oscillations and mechanical engineering
• Mechanical engineering education through gaming Techniques for dependable and sustainable design
• How can the design development cycle for mechanical engineering designs be shortened?
• appropriate material selection's significance in mechanical engineering
• Mechanical engineering's use of mechatronics and microcontrollers
• German mechanical engineering is a benchmark worldwide
• Modern mechanical engineering techniques for modeling and prototyping
• System design using numerical calculation techniques
• What effects has the growth of mechanical engineering had on Western culture?
•  Machine learning approaches for quality assurance in a manufacturing setting
• Using a variable speed drive with supervisory control and data acquisition to control an induction motor.
• Biomechanics.
• Energy and combustion systems.
• Fluid mechanics and aerodynamics.
• Fluid-structure interactions, acoustic, and vibrations.
• Food industry category for quality.
• Food industry physical and mechanical procedures.
• The food sector uses thermal procedures.
• Food industry physical and chemical processes.
• Processes of mass transfer in the food business.
• Food industry biochemical and microbiological processes.
• the significance of technological chemical regulation in the food sector.
• Process engineers and mechanical engineers have different jobs in the food industry.
• Tools for preparing raw materials for the main technical procedures.
• Equipment for processing food bulk mechanically.

Best 20 Civil Engineering Research Paper Topics

• Civil engineering's effect on how we live our daily lives
• Neural networks' use in civil engineering
• Engineering and vegetation
• Techniques for inspecting civil engineering components
• various composite materials' micromechanics in civil engineering
• Uncertainty's relevance in civil engineering modeling
• IR thermography's application to civil engineering
• In civil engineering, cutting-edge materials and adhesives are employed.
• Risk assessment's significance in civil engineering
• Sustainability and civil engineering
• Techniques for enhancing plants' ability to withstand water stress.
• The most pressing issues in civil engineering and solutions.
• Building quality is in jeopardy due to a lack of certified professionals.
• Economics in transportation engineering is significant.
• Protection at building sites.
• Modern developments in civil engineering.
• How can the entropy theory be applied in real life?
• How can I discover a suitable job offer and how much is civil engineering worth?
• How can issues in seismically active areas be resolved?
• What opportunities does civil engineering have?

A theoretical inquiry is part of the  engineering discipline's control task . You must independently choose the pertinent scientific data, process it, and accurately present it in a sequential manner for your answer to be effective.

Scientific research is still a challenging procedure, especially for students who are unable to balance work and school.

You may always get in touch with our business to conduct the study if you find yourself in such a predicament.  Professional artists   create each work particularly for each client, making each piece unique.

Additionally, they can offer planning advice, suggest study topics, and explain the nuances of research methodology.

Get more about research and research topics down here -

• Top Trending 150+ Accounting Research Topics
• 130+ Marketing Research Topics for Marketing Students
• Top 140+ Research Topics for Journalism Students
• 120 Hot Research Topics for Nursing Students
• Top 50+ Research Topics for High School Students in 2022
• A Thorough Analysis of Market Research
• Research for Psychology and Personality Disorder
• Mental Health Research Topics for Students in 2022
• 4 Tips on How to Find Homework Answers Quickly  
• How to Write Different Types of Research Paper?
• How to Choose a Research Topic?
• Step-by-step Guide For How to Write a Dissertation?
• Scope of Career in Research and Development

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May 13, 2024

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

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written by researcher(s)

AI-assisted writing is quietly booming in academic journals—here's why that's OK

by Julian Koplin, The Conversation

If you search Google Scholar for the phrase " as an AI language model ," you'll find plenty of AI research literature and also some rather suspicious results. For example, one paper on agricultural technology says,

"As an AI language model, I don't have direct access to current research articles or studies. However, I can provide you with an overview of some recent trends and advancements …"

Obvious gaffes like this aren't the only signs that researchers are increasingly turning to generative AI tools when writing up their research. A recent study examined the frequency of certain words in academic writing (such as "commendable," "meticulously" and "intricate"), and found they became far more common after the launch of ChatGPT—so much so that 1% of all journal articles published in 2023 may have contained AI-generated text.

(Why do AI models overuse these words? There is speculation it's because they are more common in English as spoken in Nigeria, where key elements of model training often occur.)

The aforementioned study also looks at preliminary data from 2024, which indicates that AI writing assistance is only becoming more common. Is this a crisis for modern scholarship, or a boon for academic productivity?

Who should take credit for AI writing?

Many people are worried by the use of AI in academic papers. Indeed, the practice has been described as " contaminating " scholarly literature.

Some argue that using AI output amounts to plagiarism. If your ideas are copy-pasted from ChatGPT, it is questionable whether you really deserve credit for them.

But there are important differences between "plagiarizing" text authored by humans and text authored by AI. Those who plagiarize humans' work receive credit for ideas that ought to have gone to the original author.

By contrast, it is debatable whether AI systems like ChatGPT can have ideas, let alone deserve credit for them. An AI tool is more like your phone's autocomplete function than a human researcher.

The question of bias

Another worry is that AI outputs might be biased in ways that could seep into the scholarly record. Infamously, older language models tended to portray people who are female, black and/or gay in distinctly unflattering ways, compared with people who are male, white and/or straight.

This kind of bias is less pronounced in the current version of ChatGPT.

However, other studies have found a different kind of bias in ChatGPT and other large language models : a tendency to reflect a left-liberal political ideology.

Any such bias could subtly distort scholarly writing produced using these tools.

The hallucination problem

The most serious worry relates to a well-known limitation of generative AI systems: that they often make serious mistakes.

For example, when I asked ChatGPT-4 to generate an ASCII image of a mushroom, it provided me with the following output.

It then confidently told me I could use this image of a "mushroom" for my own purposes.

These kinds of overconfident mistakes have been referred to as "AI hallucinations" and " AI bullshit ." While it is easy to spot that the above ASCII image looks nothing like a mushroom (and quite a bit like a snail), it may be much harder to identify any mistakes ChatGPT makes when surveying scientific literature or describing the state of a philosophical debate.

Unlike (most) humans, AI systems are fundamentally unconcerned with the truth of what they say. If used carelessly, their hallucinations could corrupt the scholarly record.

Should AI-produced text be banned?

One response to the rise of text generators has been to ban them outright. For example, Science—one of the world's most influential academic journals—disallows any use of AI-generated text .

I see two problems with this approach.

The first problem is a practical one: current tools for detecting AI-generated text are highly unreliable. This includes the detector created by ChatGPT's own developers, which was taken offline after it was found to have only a 26% accuracy rate (and a 9% false positive rate ). Humans also make mistakes when assessing whether something was written by AI.

It is also possible to circumvent AI text detectors. Online communities are actively exploring how to prompt ChatGPT in ways that allow the user to evade detection. Human users can also superficially rewrite AI outputs, effectively scrubbing away the traces of AI (like its overuse of the words "commendable," "meticulously" and "intricate").

The second problem is that banning generative AI outright prevents us from realizing these technologies' benefits. Used well, generative AI can boost academic productivity by streamlining the writing process. In this way, it could help further human knowledge. Ideally, we should try to reap these benefits while avoiding the problems.

The problem is poor quality control, not AI

The most serious problem with AI is the risk of introducing unnoticed errors, leading to sloppy scholarship. Instead of banning AI, we should try to ensure that mistaken, implausible or biased claims cannot make it onto the academic record.

After all, humans can also produce writing with serious errors, and mechanisms such as peer review often fail to prevent its publication.

We need to get better at ensuring academic papers are free from serious mistakes, regardless of whether these mistakes are caused by careless use of AI or sloppy human scholarship. Not only is this more achievable than policing AI usage, it will improve the standards of academic research as a whole.

This would be (as ChatGPT might say) a commendable and meticulously intricate solution.

Provided by The Conversation

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