Bioresource and Agricultural Engineering Commons^™

Nebraska And The Midwest Agtech Ecosystem: Benchmarking Innovation Investment And Translation Gaps, Ankit Chandra, Ishani Lal, Brennan Costello

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Agricultural innovation is central to the sustainable transformation of food systems, yet the capital that finances it is unevenly distributed relative to where food is produced. This paper develops a diagnostic framework for measuring this mismatch and applies it across the U.S. Midwest from 2021 to 2025, with particular emphasis on Nebraska's structural position within this landscape. Drawing on venture capital deal-flow data, 17 stakeholder interviews, and a novel strength-weakness-opportunity-gap (SWOG) ecosystem mapping methodology, we document $736 million in tracked Midwest AgTech funding across eight states (Nebraska, Iowa, Missouri, Illinois, Indiana, Kansas, North Dakota, and South Dakota). We introduce three …

Evaluation Of A Vortex Flow Device On A Center Pivot Irrigation System, Ankit Chandra, Derek M. Heeren, Tyler Smith

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

This study presents the first independent field evaluation of a passive vortex flow device designed to reduce hydraulic friction in pressurized irrigation systems. Experiments were conducted on a full-scale, groundwater-fed center pivot irrigation system at the Eastern Nebraska Research, Extension, and Education Center (ENREEC). A paired comparison approach was used to quantify differences in flow rate, energy consumption, and pressure distribution along the pivot lateral under baseline (no device) and treatment (device installed) conditions. Results showed negligible change in system flow rate (621 vs. 618 gpm) and energy consumption (~1.2% difference), consistent with expectations for pressure-regulated irrigation systems. However, the …

Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …

Thermodynamic Modeling Of Ph Impacts On Subsurface Microbial Consortia, Jackfin K C

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

Underground hydrogen storage is affected by microbial consumption, and the different minerals present in the subsurface. However, most studies consider either biotic or abiotic factors in isolation and hence, the conditions that drive a self-sustaining storage remain poorly understood. This thesis uses a genome-informed thermodynamic model developed by Kharel et al. (2026) in which pH is the central variable coupling hydrogenotrophic microbial metabolism, inter-species competition, and carbonate mineral buffering. The model includes four hydrogen-consuming species: methanogen (Methanobacterium), acetogen (Acetoanaerobium), aerobic acetate oxidizer (Pseudomonas stutzeri), and sulfate reducer (Nitratidesulfovibrio) by conditioning each organism's …

Undergraduate Design Spine For Biological Systems Engineering And Agricultural Engineering, David Mabie, Derek M. Heeren, Deepak R. Keshwani, Heidi A. Diefes-Dux, Nicole M. Iverson, Rachel Padrnos, Greg Bashford, Taryn King, Jenna Hefley, Curtis L. Tomasevicz

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Engineering education is undergoing a shift toward preparing graduates with demonstrated capabilities that integrate technical knowledge, durable skills, and the ability to adapt in a rapidly evolving professional landscape. This paper describes a comprehensive redesign of the undergraduate curriculum in Biological Systems Engineering (BSEN) and Agricultural Engineering (AGEN) at the University of Nebraska–Lincoln. The redesign is grounded in a “Design Spine” framework, which distributes and scaffolds design experiences across all four years of the program to support progressive development of problem solving, systems thinking, communication, and professional skills. The curriculum is organized around clearly defined capabilities and threads that connect …

Assessment Of Super Absorbent Polymer In Soybean Cultivation Under Variable Irrigation Conditions In Nebraska, Ankit Chandra, Abia Katimbo, Ronaldo Marchezan, Martha Nabaggala

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Water limitation is a primary constraint to soybean productivity in both irrigated and rainfed systems. Soil-applied superabsorbent polymers (SAPs) have been proposed as a strategy to buffer crops against episodic drought stress; however, their physiological and agronomic performance under varying irrigation regimes remains insufficiently quantified. Here, we evaluate three biodegradable polymer formulations: broader granules (BB), original granules (OG), and powder (PWR) applied at low (17.7 lb/ac) and high (120 lb/ac) rates under full (100% ET), reduced (50% ET), and no irrigation conditions in western Nebraska. Polymer application had negligible effects under full irrigation, with yields comparable to untreated controls. Under …

A New Electroencephalography Electrode Design For Curly And Kinky Hair Types, Elena Butler

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

Medical discrimination and implicit bias are present in both societal systems and into the design and validation of medical devices. Traditional electroencephalography (EEG) systems often fail to provide reliable physiological recordings on curly and kinky hair types (3B–4C), associated typically with Black American and others of African descent. EEG on these hair types often results in high electrode-scalp impedance, poor signal quality, and participant discomfort. Consequently, such technical biases contribute to the underrepresentation of these populations in neuroscience research and clinical diagnostics, while simultaneously limiting equitable access to EEG-based medical care.

To address this gap, a novel conductive electrode attachment …

Beyond Local Pathology: Exploring The Role Of Gut Microbiota In Chronic Low Back Pain Using An Integrated Behavioral And Microbiological Approach, Adan L. Redwine

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

Chronic low back pain (LBP) affects millions worldwide, often originating from intervertebral disc (IVD) degeneration. While the gut microbiome modulates musculoskeletal pain, prior studies of the gut-disc axis have focused entirely on structural changes. This leaves a critical gap: does the microbiome influence the experience of discogenic pain? To answer this, an integrated approach using longitudinal gut microbiome profiling, machine learning-based behavioral phenotyping, and structural disc assessments in a rat model of discogenic LBP was utilized.

Female Sprague Dawley rats underwent one of four conditions: sham surgery, IVD injury, antibiotic-mediated microbiome depletion + IVD injury, or IVD injury + treatment …

Understanding Agtech Adoption: Evidence From The Farm Tech Adoption Challenge 2025, Ankit Chandra, Mark Stone

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

The Farm Tech Adoption Challenge (FTAC) examined how farmers evaluate emerging agricultural technologies through structured interactions with startups. Farmers assessed solutions based on their on-farm challenges and indicated adoption decisions. Results showed that adoption was driven by how well technologies addressed economic pressure, risk reduction, and operational simplicity. Startups aligned with these priorities were more likely to gain traction, with five out of nine receiving farmer commitments for adoption. However, adoption also depended on clear economic value, field validation, and system integration. Overall, the findings suggest that the primary bottleneck in agtech is not the lack of relevant technologies, but …

Why Agtech Startups Fail? Evidence From Global Shutdown Patterns In 2025 And The Cost-Adoption Mismatch Effect, Ankit Chandra, Ishani Lal

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Agricultural technologies are widely seen as a driver for sustainability, resilience, and food-system transformation. Yet in 2025, agtech startup across North America, Europe, Asia, and Africa experienced multiple shutdowns. Although each company closed for its own reasons, the failures highlight consistent underlying patterns. We analyze 18 publicly reported shutdowns across controlled-environment agriculture (CEA), robotics, insect protein, digital platforms, sensors, and ag-biotechnology. We find that most ventures struggled not with scientific feasibility but with economic and adoption dynamics at the farm level. We identify a Cost-Adoption Mismatch Effect, in which the capital and operational burden of a technology exceeds farmers’ capacity …

Design And Fabrication Of A Scaled Automated Dairy Farm Model: A Report, Md Towfiqur Rahman

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Summary

This study investigates how ventilation systems work in dairy barns and builds a scaled model to support education and research. The project is designed to help students from the University of Nebraska–Lincoln (UNL), K-12 learners, and researchers in animal science, veterinary medicine, and engineering gain visual experience with dairy facility components and processes. Different ventilation methods were studied, leading to the design of a 1/64-scale tunnel-ventilated dairy barn meant for 60 Holstein Friesian cows. Barn dimensions were set based on real Holstein cow measurements to ensure proper cow comfort, while airflow requirements were calculated and scaled down. Miniature fans …

Deep Learning Framework For Sow Posture Classification From Depth Images: Comparison With Data Transformation Techniques, Models, And Cross-Validation, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Suzanne M. Leonard, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Piglet preweaning mortality (PWM) in the United States averages ≈14–15%, with sow overlaying causing about one third proportion of these losses. This research aimed to develop and evaluate deep learning models to classify six sow postures using depth images to monitor behaviors linked to overlaying risk. Top-down depth images were captured with Kinect V2^® cameras at 10 frames min^-1 for five consecutive days (2 days before to 2 days after farrowing), yielding 26,506 training images from 18 sows, 17,901 testing images from 12 sows, and 4,697 additional images from three sows in diagonal stalls for external validation. Three …

Assessment Of Soybean Response To Irrigation Variability In Eastern Nebraska Using The Aquacrop Model, Anmol Singh, Saleh Taghvaeian, Yufeng Ge, Derek M. Heeren, Frank Bai

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Soybean [Glycine max (L.) Merr.] is a major irrigated crop in eastern Nebraska, where recent expansions in irrigated agriculture and projected trends in irrigation demand necessitate thorough investigations of approaches that can optimize its irrigation management. In this study, the AquaCrop model was calibrated and validated using 19 variable irrigation treatments from a five-year field experiment. The model accurately simulated canopy cover, soil water content, and grain yield, with validation normalized root mean square error (nRMSE) of 12%, 7%, and 7%, respectively. The model was subsequently applied to estimate soybean yield and water requirement during a 15-year period (2010–2024) …

In-Field Tractor Operational Load Profile Generation In Support Of Advanced Tractor Testing In Mixedmode Power, Andrew Donesky

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

This dissertation addresses the need to better characterize real-world tractor power requirements across drawbar, power take-off (PTO), and hydraulic modes to support more representative tractor testing. Conventional testing protocols, such as OECD Code 2, emphasize steady-state performance under controlled high-load conditions, which do not reflect the mixed and dynamic demands of modern field operations. To address this gap, a Tractor Instrumentation System (TIS) was developed, validated, and deployed to collect high-resolution, mixed-mode power data during planting, anhydrous ammonia application, and grain cart operations. The TIS integrates physical sensors, including custom load pins, hydraulic pressure/flow sensors, and a redesigned PTO torque …

An Integrated Modeling Framework To Evaluate Circularity Of The Corn–Water–Ethanol–Beef Nexus, Heydi Han

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

This dissertation examines the transition from conventional linear agricultural and food bioenergy systems toward more circular, resilient, and resource-efficient configurations. Prior research indicates that spatial and temporal variability in soil, weather, animal biological responses, and management decisions strongly influences productivity, nutrient-use efficiency, and profitability. Studies have also shown that a diversified circular system can buffer these sources of variability, improving stability and adaptive capacity. Building on these insights, the central focus of this work is to develop an integrated modeling framework to evaluate circularity within the Corn-Water-Ethanol-Beef (CWEB) nexus and explore how climate variability and management choices shape system-wide performance. …

Evaluation Of Performance Characteristics And Groundwater Contamination Risks Associated With On-Farm Swine Carcass Disposal Via Composting And Shallow Burial With Carbon, Gustavo Castro Garcia

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

This dissertation evaluates the performance of three on-farm swine carcass disposal methods: whole carcass composting (WCC), ground carcass composting (GCC), and shallow burial with carbon (SBC), focusing on biosecurity factors and groundwater contamination risks. Foreign animal diseases (FADs), such as African swine fever and classical swine fever, pose severe economic and animal well-being risks if introduced to the United States. With confirmation of an FAD, swine movement will be halted, creating an urgent need for practical, biosecure, and environmentally responsible on-farm disposal strategies for swine carcasses. Nebraska, as a leading swine-producing state, exemplifies the vulnerability of high-density livestock regions to …

Development Of A Machine Learning Framework For An Irrigation Decision Support System, Eric Wilkening, Derek M. Heeren, Yeyin Shi, Laila A. Puntel, Guillermo R. Balboa, Abia Katimbo, Kuan Zhang, Precious Nneka Amori, Bruno Lena

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Currently used irrigation scheduling techniques often require significant human intervention and are time consuming, particularly for variable rate irrigation. This research aimed to develop a conceptual framework that incorporates disparate data sources leveraging both mechanistic and machine learning (ML) approaches. The overarching objective is to utilize the growing availability of data and technology to manage irrigation more precisely, which will minimize negative impacts of irrigation on our water resources. An initial irrigation machine learning model was proposed and tested in this study as a key component of an edge-cloud computing and federated learning decision-making framework. The specific objectives were (1) …

Groundwater Flooding On Highways In The Nebraska Sandhills: Applying Remote Sensing, Precipitation And Groundwater Modeling To Determine Depth, Cause And Frequency, Aaron R. Mittelstet

Nebraska Department of Transportation: Research Reports

Climate change significantly impacts infrastructure sustainability, particularly through shifts in precipitation patterns, intensity, and duration. These precipitation dynamics may increase the occurrence of surface water and groundwater flooding. Groundwater in the Nebraska Sand Hills (NSH), including the thickest portions of the High Plains Aquifer, extends close to the land surface in interdunal areas, making the NSH vulnerable to groundwater flooding. Recent events involving heavy precipitation, snow melt, and rising groundwater levels have caused prolonged highway flooding, disrupting transportation networks. This study estimates groundwater flood inundation depth, duration and frequency in the highways of NSH using remote sensing techniques and groundwater …

Geophysical Tools For Agricultural Management: Trends, Challenges, And Opportunities, Sophia Becker, Trenton Franz, Yufeng Ge, Joe Luck, Derek M. Heeren

School of Natural Resources: Faculty Publications

Agrogeophysics is a convergence of proximal soil sensing and hydrogeophysics in which geophysical methods are used to describe soil patterns and dynamics that shape agronomic management (including precision agriculture). To fully realize its potential for optimizing agricultural production, current barriers and targets for future agrogeophysics research must be identified. In this review, we compare the trajectory of agrogeophysics within peer-reviewed literature, patents, and the US university extension literature and examine the current challenges and opportunities for supporting agricultural production and sustainability with agrogeophysical tools. We conducted a repeatable search of Web of Science and Scopus for seven geophysical methods (electromagnetic …

Ai Tools In Natural Resources And Environmental Systems For The Classroom, Research, Extension And Industry, Derek M. Heeren, C. T. Agouridis, Debabrata Sahoo, Isaya Kisekka, Trisha L. Moore

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

This white paper synthesizes a series of panel insights on AI adoption across education, Extension, research and industry contexts within natural resources and environmental systems. It emphasizes that while advanced machine learning and generative AI introduce structural shifts in autonomy, scale, and cognitive augmentation, their value lies in augmenting, not replacing, human expertise. Applied tool examples include decision‑support systems for rural water operators, HAB‑diagnosis apps integrating image classification and natural‑language guidance, an irrigation educational chatbot tailored to user background, and sensor‑driven orchard AI for light interception estimation and data gap filling. A recurring design imperative involves co‑development with end users, …

Response Of Soybean To Variable Irrigation Levels In Eastern Nebraska Using The Aquacrop Model, Anmol Singh

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

AquaCrop was calibrated and validated for soybean [Glycine max (L.) Merr.] using 19 irrigation treatments from five years using data from field experiments. The model accurately simulated canopy cover (CC), soil water content (SWC), and grain yield, with overall validation nRMSE values of 12%, 7%, and 7%, respectively. The overall validation nRMSE for SWC in individual 30-cm soil layers was comparatively higher, at 19%. The model was subsequently applied for long-term simulations (2010–2024) to estimate soybean yield and water requirements for two dominant soil types, Yutan silty clay loam and Tomek silt loam under three irrigation levels - rainfed, …

Legacy Nutrient Transport By Overland Sheet Flow, John E. Gilley, Ryan P. Mcgehee, Kenneth M. Wacha

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The transport of phosphorus (P) and nitrogen (N) from sites containing varying quantities of legacy nutrients was evaluated in this investigation. The data that were examined were collected during four previously reported field hydrologic studies performed in eastern Nebraska. Additional flow was introduced to the top of the rainfall simulation plots to replicate runoff conditions occurring along a hillslope. It was observed that both P and N delivery were influenced by runoff rate on sites where beef cattle manure or inorganic fertilizer had been applied. Legacy nutrient delivery appeared to have been influenced by the quantity of nutrients released at …

Farmnav-Uav: A Field-Ready Autonomous Uav For Tracking Static And Dynamic Trajectories In Agricultural Applications, Veera Venkata Ram Murali Krishna Rao Muvva

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

This study presents the design and development of a custom-built uncrewed aerial vehicle (UAV) tailored for precision agriculture. Unlike commercial UAVs, which are often constrained by proprietary systems and limited hardware customization, the proposed platform emphasizes modularity, upgradeability, and cost-effectiveness. The UAV is equipped with a Cube Blue flight controller for reliable low-level actuation and a Raspberry Pi 4 companion computer that executes a Model Predictive Control (MPC) algorithm for high-level trajectory optimization and stability enhancement.

Most conventional UAV autopilot systems rely on non-optimal control strategies, such as proportional–integral–derivative (PID) controllers, which can be inadequate for dynamic or resource-constrained environments. …

Integrating High Throughput Phenotyping Approaches To Characterize Plant Traits And Support Nutrient Management Research, Katie J. Bathke

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

Over the past decade, considerable research has addressed the social, economic, and agronomic challenges posed by imbalanced nutrient applications, particularly nitrogen and, more recently, sulfur. In response, high throughput plant phenotyping, as one of the latest approaches, has contributed to the development of innovative techniques for assessing key plant phenotypes under stress over time in both field and greenhouse environments. However, there is a limited number of studies applying these techniques for nutrient management, particularly in scenarios where two abiotic stressors coexist, such as the combination of water stress and nitrogen deficiency, or concurrent nitrogen and sulfur deficiencies.

In chapter …

A Case Study On Readiness Of Engineers In Agricultural Technology Start-Ups, Katie Marie Mowat

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

This dissertation explores the perceptions of practicing engineers regarding the skills necessary to be workforce-ready at agricultural technology (ag-tech) start-ups in the Midwestern United States. A qualitative case study methodology is leveraged, combining both interview and job description data. Given their uniqueness, the study divides the ag-tech start-up industry into two subcases: livestock and cropping systems. The Work Readiness Integrated Competence Model (WRICM) is used as the theoretical framework for this study and informs the conceptual framework and analysis processes. The study identified skills that fit into thirteen distinct categories, which are further grouped into four overarching resource groups. Skills …

Optimizing Nitrogen Management: Assessing Nitrate Transport In The Deep Vadose Zone And Its Impact On Groundwater Quality In East-Central Nebraska, Muili O. Lawal

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

Groundwater contamination by nitrate (NO₃-N) is a growing environmental and public health concern driven largely by intensive agricultural fertilizer applications. The vadose zone plays an important role in NO₃-N transport, influencing groundwater quality and agricultural sustainability. This study investigated NO₃-N leaching dynamics in the deep vadose zone of Water Quality Sub-Area 30 (WQA30) within the Lower Loup Natural Resources District (LLNRD), northeast of Columbus, Nebraska (mean groundwater NO₃-N: 20.3 mg/L), using soil cores from 16 shallow (to 6.1 m) and four deep (down to 25.9 m) across four zones, two with inorganic fertilizer (Zones 1 and 4) and two with …

Assessing Sleep Quality In A Preclinical Model Of Low Back Pain Through Novel Noninvasive Methods, Lydia C. Saltz

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

Chronic low back pain (LBP) has widespread negative impacts on quality of life. Current treatments for chronic LBP fail to provide long-term efficacy and motivate the need to understand key drivers of poor patient outcomes. Mounting evidence indicates that sleep disturbances and chronic LBP have a strong reciprocal relationship. Women may be particularly vulnerable to the negative impacts of the sleep-pain axis, exhibiting greater prevalence in both conditions. However, the relationship between sleep, pain, and sex remains understudied. Preclinical models can be used to parse out characteristic sleep features that degrade with pain, which can be further broken out by …

Field Calibration Of A Time Domain Reflectometry Sensor For Water Content Measurement In Soils With Low Content Of Coarse Fragments, Rehnuma Maisha, Dean Steele, Aaron L. M. Daigh, Derek M. Heeren, Trenton E. Franz

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Comparison of soil water sensors for irrigation scheduling requires an accurate reference measurement. An Acclima TDR-310H soil water content sensor was calibrated and validated for sand, loamy sand, clay loam, sandy clay loam, and sandy loam soils. In 2021, sensor readings and soil samples were collected in the same sensor volume at depths of 15 and 46 cm at three irrigated field sites with five stations each. Gravimetric water content, bulk density, and volumetric water content (θv) were determined in the lab. The root mean square error was 0.032 cm³ cm⁻³, which was within acceptable limits. The …

The Effect Of Participation In A Place-Based Engineering Learning Experience On Engineering Career Aspiration Of Nebraska’S Rural Students: A Mixed Method Study, Samereh Soleimani Babadi

Department of Agricultural and Biological Systems Engineering: Masters Project Reports

This study investigates the influence of a place-based, hands-on engineering learning experience on rural middle school students' engineering career aspirations, using Social Cognitive Career Theory (SCCT) as a framework. Employing a mixed-methods approach, we explored how these localized learning experiences shape students' career goals through socio-cognitive factors such as self-efficacy, outcome expectations, goals, and interest. Quantitative analysis of pre- and post-activity surveys revealed significant increases in career aspiration scores, particularly among students from farming backgrounds and female students with initially lower expectations. Path analyses indicated that self-efficacy and interest were the strongest mediators between Place-based learning and engineering career aspirations. …

Cover Crops Can Reduce Greenhouse Gas Emissions From No-Till Maize In Southern Brazil: Insights From A Long-Term Field Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimélio Bayer

Adam Liska Papers

Brazil is one of the countries that has the most agricultural area under no-till (NT) management. This research study aims to evaluate life-cycle greenhouse gas (GHG) emissions from maize (M) grain production in agroecosystems that used different cover crops under NT management in southern Brazil. The data for this study were from a long-term 41-year field experiment in southern Brazil. The long-term experiment evaluated the effects of fallow (F) and cover crops (oat (O), vetch (V), cowpea (B), pigeon pea (P), and lablab (L)) on nitrous oxide and methane emissions and soil carbon (C) sequestration in maize agroecosystems. Five cropping …