Engineering Commons^™

Next-Generation Crop Monitoring Technologies: Case Studies About Edge Image Processing For Crop Monitoring And Soil Water Property Modeling Via Above-Ground Sensors, Nipuna Chamara

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

Artificial Intelligence (AI) has advanced rapidly in the past two decades. Internet of Things (IoT) technology has advanced rapidly during the last decade. Merging these two technologies has immense potential in several industries, including agriculture.

We have identified several research gaps in utilizing IoT technology in agriculture. One problem was the digital divide between rural, unconnected, or limited connected areas and urban areas for utilizing images for decision-making, which has advanced with the growth of AI. Another area for improvement was the farmers' demotivation to use in-situ soil moisture sensors for irrigation decision-making due to inherited installation difficulties. As Nebraska …

Irt-Based Irrigation Scheduling And Dry Bean Crop Water Productivity Under Different Irrigation Scenarios In The Nebraska High Plains, Angie Gradiz

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Irrigation plays a critical role for crop production in western Nebraska of the United States, where crop evapotranspiration often exceeds in-season precipitation. This study investigated the impacts of different irrigation treatments on yield and key physiological parameters of dry edible beans grown in semi-arid western Nebraska during the 2022-2023 growing seasons. Seven irrigation levels (0%, 25%, 50%, 75%, 100%, 125%, 150%) of the fully irrigated treatment (FIT), were applied using a Variable Rate Irrigation (VRI) Linear-Move Sprinkler System. Additionally, an eighth treatment was scheduled based on measurement from infrared radiometry thermometers (IRT) to evaluate the performance of the two-source energy …

Will Saf Turbocharge The Corn Ethanol Market?, Richard Perrin, Lilyan Fulginiti, Felipe Miranda De Souza Almeida

Cornhusker Economics

The long-run outlook for the corn ethanol industry is questionable, due to a transition to electric and hybrid vehicles. One source of hope for the long run is the potential demand for producing Sustainable Aviation Fuel (SAF). SAF is a key component in the United States Aviation Climate Action Plan, a path to net-zero greenhouse gas (GHG) emissions in the aviation industry by 2050. Demand for ethanol for SAF offers hope to the ethanol industry, but it depends a great deal on policy decisions that are being made now. Here we sketch out this story.

Based on the information available …

Field Research Report: Results From The Enreec Vri Field For The 2021, 2022, And 2023 Crop Seasons, Derek M. Heeren, Ali T. Mohammed, Eric Wilkening, Christopher M. U. Neale, Alan L. Boldt, Ankit Chandra, Precious Nneka Amori, Ivo Z. Goncalves, Yeyin Shi, Guillermo R. Balboa

Department of Biological Systems Engineering: Conference Presentations and White Papers

Long-term irrigation management research has been conducted from 2014 to 2023 for corn and soybean at the Eastern Nebraska Research, Extension, and Education Center (ENREEC) Variable Rate Irrigation (VRI) Field located in subhumid east-central Nebraska (in the Lower Platte North Natural Resources District). The objective of this report was to present the overall results from the VRI Field for 2021 to 2023. Across the three growing seasons, there were the following irrigation treatments: Best Management Practice (BMP), 50% BMP, 125% BMP, rainfed, Spatial ET Modeling Interface (SETMI), SDD1, SDD2, machine-learning-based Cyber-Physical System (CPS), a student team recommended rate, and industry …

Soil Nitrate Prediction Using Ftir-Atr, Vis-Nir, And Raman Spectroscopy, Sabiha Ferdous

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Fourier transform infrared spectroscopy (FTIR) combined with Attenuated total reflectance (ATR), Visible-Near Infrared spectroscopy (Vis-NIR), and Raman spectroscopy (RS) are non-destructive techniques for rapid determination of nitrogen compounds in soil. Leveraging FTIR-ATR and Vis-NIR spectra using partial least squares regression (PLSR) modeling, the study aims to predict soil nitrate content and explored the feasibility of Raman spectroscopy to detect nitrate (NO₃^-), nitrite (NO₂^-), and ammonium (NH₄⁺) in soil. Soil samples were collected from four different fields, dried, sieved (2mm), and then used for collecting spectra (FTIR-ATR and Vis-NIR). Laboratory analysis was …

Stage And Discharge Prediction From Documentary Time-Lapse Imagery, Kenneth W. Chapman, Troy E. Gilmore, Mehrube Mehrubeoglu, Christian D. Chapman, Aaron R. Mittelstet, John E. Stranzl Jr.

Biological Systems Engineering: Papers and Publications

Imagery from fixed, ground-based cameras is rich in qualitative and quantitative information that can improve stream discharge monitoring. For instance, time-lapse imagery may be valuable for filling data gaps when sensors fail and/or during lapses in funding for monitoring programs. In this study, we used a large image archive (> 40,000 images from 2012 to 2019) from a fixed, ground-based camera that is part of a documentary watershed imaging project (https://plattebasintimelapse.com/). Scalar image features were extracted from daylight images taken at one-hour intervals. The image features were fused with United States Geological Survey stage and discharge data as …

Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer

Biological Systems Engineering: Papers and Publications

Brazilian agriculture is constantly questioned concerning its environmental impacts, particularly greenhouse gas (GHG) emissions. This research study used data from a 34-year field experiment to estimate the life cycle GHG emissions intensity of maize production for grain in farming systems under no-tillage (NT) and conventional tillage (CT) combined with Gramineae (oat) and legume (vetch) cover crops in southern Brazil. We applied the Feedstock Carbon Intensity Calculator for modeling the “field-to-farm gate” emissions with measured annual soil N₂O and CH₄ emissions data. For net CO₂ emissions, increases in soil organic C (SOC) were applied as a proxy, …

Development Of A Machine Learning System For Irrigation Decision Support With Disparate Data Streams, Eric Wilkening

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

In recent years, advancements in irrigation technologies have led to increased efficiency in irrigation applications, encompassing the adoption of practices that utilize data-driven irrigation scheduling and leveraging variable rate irrigation (VRI). These technological improvements have the potential to reduce water withdrawals and diversions from both groundwater and surface water sources. However, it is vital to recognize that improved application efficiency does not necessarily equate to increased water availability for future or downstream use. This is particularly crucial in the context of consumptive water use, which refers to water consumed and not returned to the local or sub-regional watershed, representing a …

Enhancing Urban Water Quality Through Biological-Chemical Treatment: Aquatic Macroinvertebrate Community And Temporal Chlorophyll-A Response, Matthew Chaffee

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

With a growing human population, urbanization is impeding a plethora of natural waterways. Of these, urban ponds play a vital role in nutrient sequestration, flood prevention, and habitat sanctuaries. However, nutrient loading can reduce habitat effectiveness and promote harmful algae blooms. To reduce internal nutrient loads, a biological-chemical treatment strategy consisting of floating treatment wetlands (FTWs) and lanthanum were applied to two urban retention ponds, Densmore and Wilderness Ridge Ponds. To measure effectiveness, chlorophyll-a samples were collected and correlated with Sentinel-2. A novel band algorithm termed 3BR1 produced a strong correlation (R² = 0.72) to physical chlorophyll-a …

Responses Of Maize To Different Irrigation Regimes In Semi-Arid Western Nebraska, Swathi Palle

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

As the “Cornhusker State”, Maize (Zea mays) is an important crop in Nebraska. However, farmers in the state are challenged by unstable supply of surface water and limited groundwater resources. A better understanding of maize's response to water stress that occurs at different growth stages can help implement the best irrigation practices that conserve water while maintaining yields. In this study, we conducted field experiments at the Panhandle Research, Extension, and Education Center to compare the responses of maize to eight irrigation treatments which included both limited and deficit irrigation regimes during 2022 and 2023 growing seasons. Specifically, …

Renovating The Ipmu Via Internet Of Things For Pollutant Emission Estimations In Poultry Facilities, Joshua Dotto

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

The emissions of ammonia (NH₃), particulate matter (PM_2.5), and carbon dioxide (CO₂) are major concerns in poultry facilities. They can pose environmental concerns and nuances. Robust and affordable measurement systems are needed to accurately measure in-barn concentrations and quantify the emissions.

The Intelligent Portable Monitoring Unit (iPMU or PMU3) developed in 2016 was reconstructed into PMU4 to include upgraded NH₃ and PM_2.5 sensors and wireless connectivity for a low-cost, robust, and accurate air quality monitoring device with contactless data transfer using the concept of Internet of Things (IoT). In addition, a user-friendly …

Aicropcam: Deploying Classification, Segmentation, Detection, And Counting Deep-Learning Models For Crop Monitoring On The Edge, Nipuna Chamara, Geng (Frank) Bai, Yufeng Ge

Biological Systems Engineering: Papers and Publications

Precision Agriculture (PA) promises to meet the future demands for food, feed, fiber, and fuel while keeping their production sustainable and environmentally friendly. PA relies heavily on sensing technologies to inform site-specific decision supports for planting, irrigation, fertilization, spraying, and harvesting. Traditional point-based sensors enjoy small data sizes but are limited in their capacity to measure plant and canopy parameters. On the other hand, imaging sensors can be powerful in measuring a wide range of these parameters, especially when coupled with Artificial Intelligence. The challenge, however, is the lack of computing, electric power, and connectivity infrastructure in agricultural fields, preventing …

Modeling Overdraft-Driven Nitrate Transport In Shallow Wells For Mitigation And Scenario Planning, Jonathan Cronk

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

In Nebraska, average nitrate concentrations in groundwater have doubled since 1974, making water quality management more important than ever. As droughts, heat waves, and floods become more common climate events, understanding their impacts will be necessary to make informed management decisions. Emerging literature describes that drought correlates to an increase in the concentration of nitrate-N at domestic and irrigation wells, however the relative contributions of the mechanisms thought to be responsible is currently unknown.

This research assessed the impact of recharge and pumping rate changes as two mechanisms affecting nitrate-N concentration during drought, assessed the relationship between well depth and …

Statistical And Machine Learning Approaches To Describe Factors Affecting Preweaning Mortality Of Piglets, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Vamsi Manthena, Yeyin Shi

Biological Systems Engineering: Papers and Publications

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the United States Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, …

Statistical And Machine Learning Approaches To Describe Factors Affecting Preweaning Mortality Of Piglets, Md Towfiqur Rahman, Tami M. Brown-Bandl, Gary A. Rohrer, Sudhendu R. Sharma, Vamsi Manthena, Yeyin Shi

Biological Systems Engineering: Papers and Publications

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the U.S. Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, litter, …

Creating An Automatic Lowering Function For Quarter-Scale Tractor Pulling Sled, Sam Wilkins

Honors Theses

As the agricultural industry works to continuously integrate innovative technology and improve production efficiency, improved on-board data acquisition and transmission will be necessary for all agricultural machines. To make this a reality, the utilization of controller area network (CAN) technology will be crucial. Therefore, it is important for all agricultural engineers to have foundational knowledge of CAN bus systems and the standards that govern their use in industry. The UNL quarter-scale tractor team regularly utilizes CAN buses on their tractors and testing equipment. One such testing machine is the team’s pulling sled, which uses CAN messages to transport important information …

Upscaling Wetland Methane Emissions From The Fluxnet-Ch4 Eddy Covariance Network (Upch4 V1.0): Model Development, Network Assessment, And Budget Comparison, Gavin Mcnicol, Etienne Fluet-Chouinard, Zutao Ouyang, Sara Knox, Zhen Zhang, Tuula Aalto, Sheel Bansal, Kuang Yu Chang, Min Chen, Kyle Delwiche, Sarah Feron, Mathias Goeckede, Jinxun Liu, Avni Malhotra, Joe R. Melton, William Riley, Rodrigo Vargas, Kunxiaojia Yuan, Qing Ying, Qing Zhu, Pavel Alekseychik, Mika Aurela, David Billesbach, David I. Campbell, Jiquan Chen, Housen Chu, Ankur R. Desai, Eugenie Euskirchen, Jordan Goodrich, Timothy Griffis, Manuel Helbig, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, John King, Franziska Koebsch, Randall Kolka, Ken Krauss, Annalea Lohila, Ivan Mammarella

Biological Systems Engineering: Papers and Publications

Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). …

Resilin Distribution And Abundance In Apis Mellifera Across Biological Age Classes And Castes, Audrey Anderson, Noah Keime, Chandler Fong, Andrew Kraemer, Carol Fassbinder-Orth

Biological Systems Engineering: Papers and Publications

The presence of resilin, an elastomeric protein, in insect vein joints provides the flexible, passive deformations that are crucial to flapping flight. This study investigated the resilin gene expression and autofluorescence dynamics among Apis mellifera (honey bee) worker age classes and drone honey bees. Resilin gene expression was determined via ddPCR on whole honey bees and resilin autofluorescence was measured in the 1m-cu, 2m-cu, Cu-V, and Cu2-V joints on the forewing and the Cu-V joint of the hindwing. Resilin gene expression varied significantly with age, with resilin activity being highest in the pupae. Autofluorescence of the 1m-cu and the Cu-V …

Clim4omics: A Geospatially Comprehensive Climate And Multi-Omics Database For Maize Phenotype Predictability In The United States And Canada, Parisa Sarzaeim, Francisco Munoz-Arriola, Diego Jarquin, Hasnat Aslam, Natalia De Leon Gatti

Biological Systems Engineering: Papers and Publications

The performance of numerical, statistical, and data-driven diagnostic and predictive crop production modeling relies heavily on data quality for input and calibration or validation processes. This study presents a comprehensive database and the analytics used to consolidate it as a homogeneous, consistent, multidimensional genotype, phenotypic, and environmental database for maize phenotype modeling, diagnostics, and prediction. The data used are obtained from the Genomes to Fields (G2F) initiative, which provides multiyear genomic (G), environmental (E), and phenotypic (P) datasets that can be used to train and test crop growth models to understand the genotype by environment (GxE) interaction phenomenon. A particular …

Plant Height Estimation Using Rtk-Gnss Enabled Unmanned Aerial Vehicle (Uav) Photogrammetry, Pascal Izere

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Using Unmanned Aerial Vehicle (UAV) based remote sensing technology to provide high-throughput plant phenotypic traits has shown a great potential of eliminating manual measurements. For example, the use of UAV imaging to estimate plant height is of great interest to plant breeders and agronomists. Height is linked to a plant’s physical growth, light competition, health, biomass, and yield; thus, its accurate estimation is crucial in breeding. Conventionally, accurate height estimation by UAV platforms relies heavily on the use of ground control points (GCPs) for geometric calibration due to the relatively low positioning accuracy of regular differential global navigation satellite system …

Influence Of Ultrasound Machine Settings On Quantitative Measures Derived From Spatial Frequency Analysis Of Muscle Tissue, Scott K. Crawford, Stephanie A. Kliethermes, Bryan C. Heiderscheit, Greg Bashford

Biological Systems Engineering: Papers and Publications

Background Ultrasound is a powerful tool for diagnostic purposes and provides insight into both normal and pathologic tissue structure. Spatial frequency analysis (SFA) methods characterize musculoskeletal tissue organization from ultrasound images. Both sonographers in clinical imaging and researchers may alter a minimized range of ultrasound settings to optimize image quality, and it is important to know how these small adjustments of these settings affect SFA parameters. The purpose of this study was to investigate the effects of making small adjustments in a typical default ultrasound machine setting on extracted spatial frequency parameters (peak spatial frequency radius (PSFR), Mmax, Mmax%, and …

Characterizing Feedlot Feed Using Depth Cameras And Imaging Technology, Jean Niwenshuti

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Imaging technology is a growing field that provides solutions in many areas from manufacturing to agriculture. Through previous research, imaging technologies have been studied in livestock farming to monitor the animal’s health and welfare in the production process. However, the feedlot industry is still behind in validating the feasibility to use some of these technologies nor to adopt such technologies to address challenges the industry is facing, such as lack of skilled labor.This work proposes using novel imaging methods to identify feed types and estimate the amount of feed remaining in a typical Midwestern feedlot feed bunk. These methods have …

Assessment Of Integrated Nutrient Management Practices On Soil Health And Nitrogen Efficiency In Cropping Systems, María José Oviedo Ventura

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Groundwater quality in Nebraska is threatened by non-point source contributions of nitrate-nitrogen, primarily by agricultural systems. Intensive crop and livestock production that neglects the value of manure in crop fertility plans can contribute to soil degradation and natural resource impairment. The purpose of this study is to evaluate opportunities to improve agricultural nutrient management throughout Nebraska by quantifying opportunities for manure distribution, evaluating soil health implications of organic and inorganic soil amendments, and assessing nutrient management practices focused on reducing nitrate leaching in agricultural soils.

This study described in Chapter 2 provides a spatial illustration of nitrogen and phosphorus balances …

Prairie Protector: Student Development Of Systems Thinking Habits In The Context Of Agroecosystems, Erin Ingram, Jennifer Keshwani

Biological Systems Engineering: Papers and Publications

Introduction: The Great Plains ecosystem offers an opportunity for young people to gain knowledge about intricate systems through practical learning. The spread of woody plants into grasslands, known as the “Green Glacier,” poses a risk to biodiversity and animal production. Although effective management strategies exist, some land managers are reluctant to use them. It is critical to cultivate a scientifically literate population that can think systematically and make informed decisions based on STEM principles to address such complex agroecosystem problems.

Methods: In this study, semi-structured focus group discussions with high school students were analyzed to determine whether Prairie …

Assessing The Impact Of Spatial Resolution Of Uas-Based Remote Sensing And Spectral Resolution Of Proximal Sensing On Crop Nitrogen Retrieval Accuracy, Kianoosh Hassani, Hamed Gholizadeh, Saleh Taghvaeian, Victoria Natalie, Jonathan Carpenter, Jamey Jacob

Biological Systems Engineering: Papers and Publications

Foliar nitrogen (N) plays a central role in photosynthetic machinery of plants, regulating their growth rates. However, field-based methods for monitoring plant N concentration are costly and limited in their ability to cover large spatial extents. In this study, we had two objectives: (1) assess the capability of unoccupied aerial system (UAS) and non-imaging spectroscopic data in estimating sorghum and corn N concentration and (2) determine the impact of spatial and spectral resolution of reflectance data on estimating sorghum and corn N concentration. We used a UAS and an ASD spectroradiometer to collect canopy- and leaf-level spectral data from sorghum …

Exploring The Determinants Of Organic Matter Bioavailability Through Substrate-Explicit Thermodynamic Modeling, Firnaaz Ahamed, Yaqi You, Amy Burgin, James C. Stegen, Timothy D. Scheibe, Hyun-Seob Song

Biological Systems Engineering: Papers and Publications

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations …

Development Of A Scalable Edge-Cloud Computing Based Variable Rate Irrigation Scheduling Framework, Eric J. Wilkening, Derek M. Heeren, Yeyin Shi, Abia Katimbo, Precious N. Amori, Guillermo R. Balboa, Laila A. Puntel, Kuan Zhang, Daran R. Rudnick

Department of Biological Systems Engineering: Conference Presentations and White Papers

Currently, variable-rate precision irrigation (VRI) scheduling methods require large amounts of data and processing time to accurately determine crop water demands and spatially process those demands into an irrigation prescription. Unfortunately, irrigated crops continue to develop additional water stress when the previously collected data is being processed. Machine learning is a helpful tool, but handling and transmitting large datasets can be problematic; more rural areas may not have access to necessary wireless data transmission infrastructure to support cloud interaction. The introduction of “edge-cloud” processing to agricultural applications has shown to be effective at increasing data processing speed and reducing the …

A Robotic System For In-Situ Measurement Of Soil Total Carbon And Nitrogen, Husein Harun

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Surges in the cost of fertilizer in recent times coupled with the environmental effects of their over-application have driven the need for farmers to optimize the amount of fertilizer they apply on the farm. One of the key steps in determining the right amount of fertilizer to apply in a given field is measuring the amount of nutrients present in the soil. To ascertain nutrient deficiencies, most farmers perform wet chemistry analysis of soil samples which requires a lot of time and is expensive. In this research project, a robotic system was designed and developed that could autonomously move to …

Peer Review Of Teaching: Et Theory, Deficit Irrigation And Consumptive Use, Derek M. Heeren, Saleh Taghvaeian

Department of Biological Systems Engineering: Conference Presentations and White Papers

A BSE Peer Review of Teaching was carried out for a graduate level course on Advanced Irrigation Management. This course has been offered for several years; each time improvements are made, but there is always a need for additional improvement. In particular, ET theory, deficit irrigation, and consumptive use are topics that the students struggle to grasp. These topics involve a relatively high level of math for an MS-level (800-level) Agricultural Systems Technology course, and the available materials on these topics either were not well developed or were not a good fit for this class. The primary objective was to …

Maize Nitrogen Uptake, Grain Nitrogen Concentration And Root-Zone Residual Nitrate Nitrogen Response Under Center Pivot, Subsurface Drip And Surface (Furrow) Irrigation, Suat Irmak, Ali T. Mohammed, Matthew Drudik

Biological Systems Engineering: Papers and Publications

While the impact(s) of irrigation and nitrogen (N) levels on crop yields have been investigated separately, research lacks about how different irrigation methods coupled with different N application timing strategies under full and limited irrigation levels effect yield, soil nitrate nitrogen (NO₃-N) residual and stover N uptake. Knowledge of these dynamics can help to establish effective water and N management guidelines for the same crop under different irrigation methods and irrigation levels. This research investigated maize (Zea mays L.) residual soil NO₃-N concentration and stover and grain N uptake response to water under different irrigation …