Nicolas F. Martin

Nicolas F. Martin
University of Illinois Urbana-Champaign | UIUC · Department of Crop Sciences

Doctor of Philosophy

About

60
Publications
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681
Citations

Publications

Publications (60)
Article
Full-text available
Machine Learning algorithms have emerged in precision agriculture as a promising approach for increasing productivity. However, the diffusion of this technology is still limited by the lack of clear applicability for crop input management and by the farmer’s perception of risk. In this work, we tackle both problems by incorporating uncertainty quan...
Article
Full-text available
Achieving high corn yields while reducing fertilizer losses seems attainable through nitrogen (N) management decisions that include the use of cover crops (CCs). To determine whether CCs result in a net positive balance between N fertilization and crop utilization, we used US field trial data comparing corn systems with and without CCs, and estimat...
Article
Full-text available
Several studies have used aerial images to predict physiological maturity (R8 stage) in soybeans (Glycine max (L.) Merr.). However, information for making predictions in the current growing season using models fitted in previous years is still necessary. Using the Random Forest machine learning algorithm and time series of RGB (red, green, blue) an...
Article
Full-text available
La agricultura de precisión supone la existencia de variabilidad espacial de la respuesta de los cultivos a la aplicación de insumos. Los experimentos a escala de lote permiten explorar dicha variabilidad. No obstante, la interacción entre la variabilidad espacial de los factores que controlan la respuesta del cultivo y el diseño experimental aplic...
Article
Full-text available
This research introduces a novel framework for enhancing soybean cultivation in North America by categorizing growing environments into distinct ecological and maturity-based zones. Using an integrated analysis of long-term climatic data and records of soybean varietal trials, this research generates a zonal environmental characterization which cap...
Article
Full-text available
The quantification of the spatial and temporal variability of crop response to controllable inputs and the relationship with their controlling factors is important for making input prescriptions. In this study, we (1) assessed the within‐field spatial variability of corn (Zea mays L.) response to nitrogen (NR) and seed (SR) rates using on‐farm prec...
Article
Full-text available
Associations between nitrogen (N) management and losses with soil health indicators (SHI) are widely presumed but relatively untested. An on‐farm experiment conducted in central Illinois was conducted to test potential relationships of SHI with agroecosystem outcomes of maize (Zea mays L.) yield and N losses under bounding N‐fertilization rates of...
Poster
Full-text available
Here we generate adaptable and deployable management policies based on deep reinforcement learning (RL) and imitation learning (IL). Using N fertilization and irrigation application as examples, we use the crop model Gym-DSSAT to train several reward functions to examine trade-offs between yield, resource use and environmental impacts. We show that...
Conference Paper
Full-text available
Crop management has a significant impact on crop yield, economic profit, and the environment. Although management guidelines exist, finding the optimal management practices is challenging. Previous work used reinforcement learning (RL) and crop simulators to solve the problem, but the trained policies either have limited performance or are not depl...
Preprint
Full-text available
Geographically weighted regression (GWR) analysis and on-farm precision experiments (OFPE) allow the quantification of the within-field spatial variability of crop response to controllable inputs. Few studies have quantified the magnitude and consistency of these responses across years, and their relationship with site-specific characteristics. In...
Conference Paper
Full-text available
The European Mediterranean region is heralded globally for both its high vulnerability to soil degradation and realization of the climate crisis, with ambient temperatures increasing at rates 20% faster than the global average. Maize crops in this region experience moderate to severe water stress during late spring and summer, although such trends...
Preprint
Full-text available
Crop management, including nitrogen (N) fertilization and irrigation management, has a significant impact on the crop yield, economic profit, and the environment. Although management guidelines exist, it is challenging to find the optimal management practices given a specific planting environment and a crop. Previous work used reinforcement learnin...
Conference Paper
Full-text available
Nitrogen (N) management is critical to sustain soil fertility and crop production while minimizing the negative environmental impact, but is challenging to optimize. This paper proposes an intelligent N management system using deep reinforcement learning (RL) and crop simulations with Decision Support System for Agrotechnology Transfer (DSSAT). We...
Article
Full-text available
Legacy effects of P in agricultural soils have been highlighted in recent literature. However, co-accumulation and release of organic P (Po) have often been ignored in current agro-environmental assessments. The mineralizable Po fraction has a potential to increase the activity of phosphate in pore water, increasing fertility or degrading water qua...
Preprint
Nitrogen (N) management is critical to sustain soil fertility and crop production while minimizing the negative environmental impact, but is challenging to optimize. This paper proposes an intelligent N management system using deep reinforcement learning (RL) and crop simulations with Decision Support System for Agrotechnology Transfer (DSSAT). We...
Article
Full-text available
Multiple strategies are available that could reduce nitrogen (N) fertilizer use in agricultural systems, ranging from voluntary adoption of new N management practices by farmers to government regulations. However, these strategies have different economic and political costs, and their relative effectiveness in decreasing N leaching has not been eva...
Article
Transparent, consistent, and statistically reliable land use/ land cover area estimates are needed to assess land use change and greenhouse gas emissions associated with biofuel production and other land uses that are influenced by policy. As relevant studies have increased rapidly during past decades, the methods used to combine data extracted fro...
Article
Full-text available
For several decades, maize (Zea mays L.) management decisions in smallholder farming in tropical regions have been a puzzle. To best balance alternative management practices' environmental and economic outcomes, an extensive dataset was gathered through CIMMYT's knowledge hub in Chiapas, a state in southern Mexico. In a knowledge hub, farmers, with...
Article
Full-text available
Restrictive layers such as hardpans limit the soil water and nutrients available for crops. In the southern Argentinean pampas, petrocalcic hardpans are found at variable depth within the field. Mapping the spatial distribution of depth to the petrocalcic hardpan is important for proper land evaluation, use, and management. Intensive grid sampling...
Article
CONTEXT Improving nitrogen (N) fertilizer recommendations for maize (Zea mays L.) in the US Midwest has been the focus of much research, yet there is no agreement for which methodology is the best to balance trade-offs between production and environmental outcomes. This study investigated the strengths and limitations of two broad approaches: dynam...
Article
Full-text available
Nitrogen (N) fertilizer recommendations for corn (Zea mays L.) in the US Midwest have been a puzzle for several decades, without agreement among stakeholders for which methodology is the best to balance environmental and economic outcomes. Part of the reason is the lack of long-term data of crop responses to N over multiple fields since trial data...
Article
Full-text available
Identifying the distribution of soil lead (Pb) in urban areas can serve to quantify the location and magnitude of health risks, and thereby inform urban land use and Pb mitigation policies. We evaluated total soil Pb distribution across the third largest metropolitan region of the United States (U.S.), Chicago, a city with multiple historical sourc...
Article
Full-text available
Time to maturity (TTM) is an important trait in soybean breeding programs. However, soybeans are a relatively new crop in Africa. As such, TTM information for soybeans is not yet as well defined as in other major producing areas. Multi-environment trials (METs) allow breeders to analyze crop performance across diverse conditions, but also pose stat...
Article
Full-text available
Within-field variability of crop yield levels has been extensively investigated, but the spatial variability of crop yield responses to agronomic treatments is less understood. On-farm precision experimentation (OFPE) can be a valuable tool for the estimation of in-field variation of optimal input rates and thus improve agronomic decisions. Therefo...
Preprint
Full-text available
A bstract Time-to-maturity (TTM) is an important trait in soybean breeding programs. However, soybean is a relatively new crop in Africa. As such, TTM information is not yet well defined as in other major producing areas. Multi Environment trials (MET) allow breeders to analyze crop performance across diverse conditions but also pose statistical ch...
Article
Full-text available
Site‐specific prescriptions require estimating response functions to controllable inputs across the field. The methodology of applying geographically weighted regression to on‐farm precision experimentation studies opens new opportunities to study site‐specific responses to inputs in farmers' fields by locally estimating the regression coefficients...
Article
Full-text available
More on‐farm research is necessary to determine the practical benefits and drawbacks of cover crops at the field‐scale. The objective of this study was to advance the use of unmanned aerial vehicle (UAV) platforms for evaluating the effects of cover crop biomass on crop growth and grain yield in two corn (Zea mays L.) fields and two soybean [Glycin...
Article
Full-text available
BACKGROUND By 2050, weather is expected to become more variable with a shift towards higher temperatures and more erratic rainfall throughout the U.S. Corn Belt. The effects of this predicted weather change on pre‐emergence (PRE) herbicide efficacy have been inadequately explored. Using an extensive database, spanning 252 unique weather environment...
Article
Full-text available
Eco-efficient use of nitrogen (N) fertilizer in Corn (Zea Mays L.) requires timely information about the supply of N from the soil and the response to N by the crop. These are complex processes, and multiple N management strategies (NMS) have been proposed over time. In this work, we used APSIM (Agricultural Production Systems sIMulator) to simulat...
Presentation
Recent developments in the availability of satellite imaging possible to develop new applications of remote sensing to improve the understanding of cropping systems. In this presentation, we cover recent changes in satellite platforms, digital infrastructure, and methods of analysis.
Conference Paper
The development of proximal sensors and variable rate technology has allowed crop production to be managed at a higher spatial resolution. The current development of more precise machinery and small size robots promises to further increase the spatial and temporal resolution of crop management. These benefits are currently limited by the lack of mo...
Conference Paper
On-farm precision experiments (OFPE) help farmers and agronomists to quantify within-field spatial variability of crop response. Spatially dense crop and soil data are now cheap and easily available. Although there are numerous studies about relationships between site-specific characteristics and yield aimed to get yield predictions or develop mana...
Conference Paper
Site-specific prescriptions require estimating response functions to controllable inputs across the field. The methodology of applying geographically weighted regression to on-farm precision experimentation studies opens new opportunities to study site-specific responses to inputs in farmers' fields by locally estimating the regression coefficients...
Article
Full-text available
Soybean maturity is a trait of critical importance for the development of new soybean cultivars, nevertheless, its characterization based on visual ratings has many challenges. Unmanned aerial vehicles (UAVs) imagery-based high-throughput phenotyping methodologies have been proposed as an alternative to the traditional visual ratings of pod senesce...
Preprint
Full-text available
Soybean maturity is a trait of critical importance for the development of new soybean cultivars, nevertheless, its characterization based on visual ratings has many challenges. Unmanned aerial vehicles (UAVs) imagery-based high-throughput phenotyping methodologies have been proposed as an alternative to the traditional visual ratings of pod senesce...
Article
Full-text available
Sufficient soil moisture is crucial for corn (Zea mays L.) germination and emergence. As within‐field soil moisture varies, it is often expected that corn seeding depth should vary accordingly. As seedbeds get drier, deeper planting increases the chances of higher soil moisture and faster emergence. The goal was to evaluate the corn yield response...
Article
Full-text available
Crop breeding is as ancient as the invention of cultivation. In essence, the objective of crop breeding is to improve plant fitness under human cultivation conditions, making crops more productive while maintaining consistency in life cycle and quality. Predictive breeding has been demonstrated in the agricultural industry and in public breeding pr...
Article
Full-text available
Predicting crop yield response to management and environmental variables is a crucial step towards nutrient management optimization. With the increase in the amount of data generated by agricultural machinery, more sophisticated models are necessary to get full advantage of such data. In this work, we propose a Convolutional Neural Network (CNN) to...
Poster
Full-text available
Recent advances in other areas have been incorporated into statistical models to explain how complex relationships between environmental characteristics and management decisions affect crop yields. Artificial neural networks are becoming the state-of-the-art in many such tasks. Architectures with many hidden layers and shared weights (convolutional...
Conference Paper
The impact of in-field variability on crop yields has been extensively investigated. In contrast, the spatial variability of crop responses to agronomic treatments is less understood. On-farm precision experimentation (OFPE) can be a valuable tool to estimate the in-field variation of optimum input rates and improve agronomic decisions. In associat...
Article
Full-text available
On‐farm experimentation using Precision Agriculture technology enables farmers to make decisions based on data from their fields. Results from on‐farm experiments depend on the experimental design and statistical analyses performed. Detailed information about the accuracy of the treatment effect estimates, and Type I error rates of hypothesis testi...
Article
Full-text available
The Data‐Intensive Farm Management (DIFM) project works with participating farmers, using precision technology to inexpensively design and run randomized agronomic field trials on whole commercial farm fields, to provide data‐based, site‐specific farm input management guidance, thus providing economic and environmental benefits. This article lays o...
Preprint
Full-text available
Crop breeding is as ancient as the invention of cultivation. In essence, the objective of crop breeding is to improve plant fitness under human cultivation conditions, making crops more productive while maintaining consistency in life cycle and quality. The applications of predictive breeding has been gaining momentum in agricultural industry and p...
Preprint
Full-text available
There is a large body of research on determining the impact of field variability of soil on crop yields. In contrast, site-specific information about crop responses to agronomic treatments is less frequent. On-Farm Precision Experimentation (OFPE) brings important information to understand the spatial variation of crop response to agronomic practic...
Preprint
Full-text available
The objective of this work was to investigate the use of remotely sensed vegetation indices to improve the quality of yield maps. The method was applied to the yield data of twelve cornfields from the Data Intensive Farm Management project. The results revealed the need to time shift the yield values up to three seconds to better match the sensor r...
Conference Paper
Full-text available
On-farm precision experimentation is an important resource to understand the spatial variation of crop response to management practices and thus improve agronomic decisions. High-quality yield data is fundamental for getting real insights from this type of experiment. Previous experimental projects have demonstrated that yield data quality affects...
Article
Full-text available
Crop performance is often shown as areas of differing grain yield. Many producers utilize simple GIS color ramping techniques to produce visual yield maps with delineated clusters. However, a more quantitative approach such as an unsupervised clustering procedure is generally used by scientists since it is much less arbitrary. Intuitively the yield...
Article
Full-text available
The main objective of this study is to find associations between site characteristics (topographic, and soil physical and chemical properties) and soybean [Glycine max (L.) Merr.] plant performance (e.g. yield, canopy development) occurring at a field scale. The study took place in an Illinois production field in the 2000 and 2001 seasons. These as...
Article
Full-text available
Data collected with "Precision Agriculture" (PA) technologies can provide new insights into soil plant relationships and how these relationships are affected by management practices. However, to analyze these datasets requires the consideration of limitations due to differential spatial scaling, multicollinearity, and autocorrelation. The main obje...

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