Agriculture Commons^™

Editorial, Anne M. Friel, Brigid Hooban, Therese Montgomery, Anne Marie O'Brien, Cormac Quigley, Edel Mcneela, Eva Campion, James Walshe, Sinead Loughran

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Bridging The Gap From Preschool To Primary: From Policy To Practice, Aimee O'Connor, Cóilín O’ Braonáin

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Identifying Superior Finger Millet (Eleusine Coracana L.) Landraces Using The Multi-Trait Genotype-Ideotype Distance Index (Mgidi), Sujan Chapagaina, Bishnu Prasad Kandela, Sudikshya Shresthaa, Ankur Poudela, Shubh Pravat Singh Yadavb

Extension Publications

Genetic variability and selection are crucial for finger millet breeding programs to maximize genetic gain and productivity. This study evaluated 18 finger millet landraces cultivated in the mid-hills of Nepal, along with ‘Kavre Kodo 2’ as a check variety, assessing 14 agro-morphological traits. The objective was to identify superior finger millet landraces using a multivariate approach based on the multi-trait genotype– ideotype distance index (MGIDI). The experiment was conducted in a randomized complete block design (RCBD) with three replications. Principal component analysis revealed that the first five components collectively accounted for 80.8% of the total variation, reflecting the genetic relatedness …

Comparative Decomposition Rates Of Prickly Pear And Sage Using Litterbags, Curtis Jang, Vy Ly, Ashlyn Reagan, Ellie Sebaugh, Darlene Panvini

Science University Research Symposium (SURS)

Litterbags are used to study nutrient cycling and track the rate of decomposition over time. Decomposition rates may vary between plant species due to various factors. One factor includes the abundance of lignin, or a structural component that provides support to a plant, which can slow the rate of decomposition. This study compared the decomposition rate of sage (Salvia officinalis), which has higher lignin levels, and prickly pear (Opuntia humifusa), which has higher water content and thus lower lignin levels. Four samples of each species, with two replicates each, were initially weighed and then placed in …

Ecophysiological Benefits Of Industrial Organic Wastes On Alfalfa Yield And Stress Mitigation In Saline Soils, Shugao Fan, Zhuanzhuan Ma, Jiawei Wu, Tianhui Yang, Jincheng Hao, Shumei Chen, Xutong Hu, Ying Zhao

School of Mathematical & Statistical Sciences Faculty Publications

Rising soil salinity and water scarcity demand sustainable solutions to maintain crop productivity. This study evaluated four agro-industrial organic amendments—fish emulsion, neem cake, coffee grounds, and seaweed extract on alfalfa (Medicago sativa) under combined salinity and drought stress, assessing their effects on soil respiration, plant physiology, and yield. Soil CO₂ efflux varied significantly among treatments: coffee grounds induced the highest microbial activity (6.2 μmol m⁻² s⁻¹), suggesting rapid decomposition, while neem cake exhibited stable emissions (3.8 μmol m⁻² s⁻¹), indicating slower organic matter turnover. Fish emulsion showed intermediate dynamics, peaking at 4.8 μmol m⁻² s⁻¹ by week 4, …

Quantifying Single, Compound And Cascading Climate Extremes: Implications For Agricultural Resilience In California, Shahryar Fazli, Wenzhao Li, Rejoice Thomas, Surendra Maharjan, Mohammad Sina Jahangiri, Andre Daccache, Hesham Morgan, Mohamed Allali, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

As climate change intensifies, extreme weather increasingly threatens California’s Central Valley (CV), a vital agricultural region exposed to rising risks from heatwaves (HW), droughts (DR), and compound extremes. These events disrupt crop productivity and broader processes like water demand, pest dynamics, and soil stability, posing systemic risks. This study examines the spatiotemporal dynamics of HW, coldwaves (CW), DR, excessive rainfall (ER), and their compound (e.g., HWDR) and cascading forms from 1951 to 2025, using NOAA nClimGrid-Daily data. We assessed trends in frequency, intensity, and duration over long-term (1951–2025) and mid-term (1981–2025) periods. Results show increasing HW and DR in the …

Securing The Digital Harvest: Cybersecurity As A Core Agribusiness Skill, Jody Herchenbach, George Grispos

Mountain Plains Business Conference

The digitization of agriculture, through IoT-enabled equipment, cloud platforms, and precision technologies, has improved efficiency and profitability while also introducing significant cybersecurity risks. These vulnerabilities can disrupt supply chains, compromise sensitive data, and undermine financial stability. Yet agribusiness degree programs often overlook cybersecurity education. This paper proposes integrating cybersecurity content on threat awareness, incident response, and data protection into agribusiness curricula. Embedding these elements equips graduates to manage both digital and financial risks, enhancing resilience and competitiveness. Such curricular innovation aligns technical and managerial training, preparing future agribusiness professionals to lead securely and sustainably in an increasingly connected industry.

Factors Influencing Plant Community Structure And Composition Of Restored Tamaulipan Thornscrub Forests, Jerald T. Garrett, Audrey J. Hicks, Christopher A. Gabler

School of Earth, Environmental, & Marine Sciences Faculty Publications

The Lower Rio Grande Valley (LRGV) of Texas is a biodiversity hotspot due to its high alpha, beta, and gamma diversity and high regional endemism, which are at high risk of degradation. The region has lost 95% of its native thornforest habitat primarily due to agricultural and urban expansion. This study aims to evaluate the current vegetative structure and composition of restored thornforest sites located in the LRGV to identify restoration methods and site characteristics that affect forest restoration outcomes. Twelve restored thornforest sites were selected for this study that varied in time since restoration, patch size, degree of isolation, …

A Feature Engineering Technique For Enhancing The Generalization Of Machine Learning Models In Estimating Crop Evapotranspiration, Gaku Yokoyama, Sohta Harigai, Shigehiro Kubota, Koichi Nomura, Gregory R. Goldsmith, Daisuke Yasutake, Tomoyoshi Hirota, Masaharu Kitano

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Accurate and precise estimation of evapotranspiration (ET) is crucial for understanding the terrestrial carbon, water, and energy cycles. While process-based models of ET, such as the Penman–Monteith model offer robust generalization capabilities, they are limited by the need for detailed parameters (e.g., stomatal conductance,) that are challenging to measure continuously. On the other hand, machine learning models can estimate ET by capturing relationships between ET and environmental variables without experimentally measuring model parameters. However, machine learning models face the challenge of limited generalizability. This issue is particularly significant given the uncertainty introduced by changing climatic …

Western Australian And South Australian Grain Enterprise Emission Intensities And Gross Margins: A Review, Christophe D'Abbadie, Ross Kingwell

Farm Systems and Economics research articles

Drawing on various datasets, crop enterprise emission intensities and gross margins are reported for the main broadacre crops grown in Western Australia and South Australia. Values are reported for various rainfall regions and across time, and for different farm performance groupings. As a generalisation, in each region, wheat and canola production display marked increases in emissions intensity across the study period whilst legume crops’ emission intensities increase far less. Wheat crops display upward emission intensity trajectories across time whilst displaying different rates of increase in emissions intensity according to regional rainfall. Canola demonstrates higher emissions intensities per tonne compared to …

Unraveling Crop Nitrogen-Water Dynamics With Hyperspectral-Thermal Sensing In Northern Central Valley, California, Shahryar Fazli, Surendra Maharjan, Wenzhao Li, Joshua B. Fisher, Rejoice Thomas, Fernando Romero Galvan, Gabriela Shirkey, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Ensuring global food security in the face of climate change requires optimizing crop water use and nutrient management. This study investigates the relationship between canopy nitrogen (N) and evapotranspiration (ET) across sunflower, rice, walnut, alfalfa, and plum crops using advanced remote sensing technologies. High-resolution hyperspectral data from NASAs Earth Surface Mineral Dust Source Investigation (EMIT) and thermal multispectral data from the Landsat-based OpenET system were analyzed over 1,135 km² in California. Regression analysis revealed strong spatial association between canopy N and ET for sunflower (R² = 0.82), rice (R² = 0.71), and walnut (R² = 0.68), …

Procedures For Rangeland Condition Assessment In The Pilbara And Southern Rangelands 2025, Department Of Primary Industries And Regional Development, Western Australia

Natural resources published reports

This report defines the procedures used in 2025 by DPIRD to complete rangeland condition assessment (RCA) in the Pilbara and southern rangelands region which has predominantly shrub-based pastures. For the rest of the pastoral estate, DPIRD uses the Procedures for RCA in the Kimberley which has grass pastures.

RCA is the process DPIRD uses to make systematic, station-level assessment of rangeland. Rangeland condition considers both the condition of pastures (defined in the ‘Pasture condition guides for the Pilbara’ and ‘Pasture condition guides for the southern rangelands including the Gascoyne, Murchison and Goldfields-Nullarbor’) and soils as determined by erosion, using the …

Procedures For Rangeland Condition Assessment In The Kimberley 2025, Department Of Primary Industries And Regional Development, Western Australia

Natural resources published reports

This report defines the procedures used in 2025 by DPIRD to complete rangeland condition assessment (RCA) in the Kimberley region which has grass-based pastures. For the rest of the pastoral estate, DPIRD uses the Procedures for RCA in the Pilbara and southern rangelands which have predominantly shrub pastures.

RCA is the process DPIRD uses to make systematic, station-level assessment of rangeland. Rangeland condition considers both the condition of pastures (as defined in the 'Pasture condition guide for the Kimberley') and soils as determined by erosion, using the erosion assessment method on pastoral lands in Western Australia. The methods have evolved …

An Economic Assessment Of Precision Conservation With On-Farm Precision Experiment Data, Karina A. Schoengold, Badri Khanal, Taro Mieno, David S. Bullock

Cornhusker Economics

Using a novel dataset that includes within field variation in productivity, we find that partial field retirement for a prairie strip can not only provide conservation benefits, but can also be economically beneficial. We note that these results are for a single field with one year of data, and that additional years of production and fields are essential to determine how much these results can be generalized. We also note that precision systems can be costly, and a comparison of outcomes with and without this information is essential to determine if investing in such systems is profitable. However, variable rate …

Efficacy Of Lactobacillus Rhamnosus And Its Metabolites To Mitigate The Risk Of Foodborne Pathogens In Hydroponic Nutrient Solution, Esther Oginni, Robin A. Choudhury, Veerachandra Yemmireddy

School of Earth, Environmental, & Marine Sciences Faculty Publications

Hydroponic nutrient solution (HNS) has been established as an ideal conduit for pathogen contamination and proliferation. This study evaluated the efficacy of lactic acid bacteria and their metabolites in mitigating the risk of foodborne pathogens in HNS when compared to conventional chemical treatments. Hoagland’s HNS were prepared according to the manufacturer’s instructions and inoculated with Salmonella Typhimurium, Escherichia coli 0157:H7, and Listeria innocua at 105 CFU/mL cell concentration. These nutrient solutions were subjected to treatment with various concentrations of Lactobacillus rhamnosus live cells, a cell-free extract (CFE) of L. rhamnosus metabolites, sodium hypochlorite and peroxyacetic acid at 22 ± 1 …

Crop Yield Prediction At Multiple Spatial Scales With Statistical Machine Learning, Vaibhav Charan, Pratishtha Poudel

Discovery Undergraduate Interdisciplinary Research Internship

Understanding and accurately predicting crop yield is becoming increasingly important today in the face of global food security challenges, and thus, the availability of standardized data and scalable models is the need of the hour. To support this, researchers have developed CY-Bench (Crop Yield Benchmark), a comprehensive dataset that helps forecast maize and wheat yields on a global scale. This research project primarily involved working with the CY-Bench dataset aiming to improve crop yield prediction through machine learning. Initially, papers explaining the CY-Bench dataset and other papers for agriculture modeling were studied and analyzed in detail. The research then progressed …

Life Cycle Assessment Of The Cultivation Of Lettuce In A Hydroponic System Using The Nutrient Film Technique, Raquel Jordan

All Theses

Hydroponic systems are an emerging method of soilless crop cultivation typically done inside a greenhouse where nutrients are delivered dissolved in water rather than being supplied from the soil. Potential benefits of hydroponic systems include reduced irrigation requirements, higher crop yield per area, and the ability to grow crops year-round in nontraditional areas such as urban settings, cold climates, and sites with contaminated soil. However, hydroponic systems tend to have high energy requirements for lighting and climate control, which can yield significant environmental impacts. To explore the environmental impacts of cultivating lettuce in a nutrient film technique (NFT) hydroponic system, …

Farming With Data: Tracing Critical Tensions Using Data Science For Food Justice, Marc Sager, Maximilan Sherard, Anthony Petrosino

Publications

In this manuscript, we explore the intersection of artificial intelligence (AI) and equitable learning in higher education, focusing on data science as a subset of AI and social justice as the core theme of equity. Our investigation sheds light on the nuanced tensions inherent in employing data science for social justice. Rooted in situated perspectives of learning and consequential learning, our study employs an instrumental case-study methodology and analysis techniques from interaction and conversation analysis. Collaborating with three undergraduate students and an urban farm, the students used data science practices to highlight inequities surrounding food justice and access to food. …

Multi-Crop Systems And Crop-Switching Strategies To Enhance Water Use Efficiency And Climate Resilience In Arid Agricultural Regions, Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Agriculture in the Lower Colorado River (LCR) region faces mounting challenges from climate change, arid conditions, and water scarcity. This study evaluates water use efficiency (WUEc) and crop-switching strategies under SSP2-4.5 and SSP5-8.5 scenarios for 2025–2049, 2050–2074, and 2075–2099. Using historical data, climatic drivers such as temperature and precipitation were analyzed for their influence on key crops, including durum wheat, winter wheat, and corn. Results show SSP2-4.5 supports water use reductions up to 16%, stable profits (80–90%), and modest calorie increases (up to 15%), while SSP5-8.5 poses severe challenges, with water use reductions of 2–5%, profits dropping to around 20%, …

A Simple Guide For Describing Soils, 2nd Edition, Angela Stuart-Street, Nicolyn Short Dr, Paul Galloway, Noel R. Schoknecht

Natural resources published reports

Soils are enormously diverse and can be very confusing to understand and talk about. This simple guide for describing soils helps to identify the most important parts of a soil profile and provide an easy way to understand and explain what you see. It gives you a step-by-step guide of what soil properties to describe and how to describe them, along with the tools to make basic soil classifications. The soil descriptors help you to identify the soil type and aid in assigning a simple and standardised name to the soil. While this guide is designed to link with a …

Adaptive Crop Switching For Irrigated Agriculture In Response To Climate Change In The Western U.S., Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Aqil Tariq, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Adaptive irrigation strategies are crucial for balancing water use, economic viability, and food security in the arid Western United States. However, as a key indicator vital in regulating agricultural productivity and crop irrigation, water use efficiency (WUEc) is becoming increasingly complex to estimate due to climate change. This study explores the critical role of key meteorological drivers, such as maximum temperature (tmax) and vapor pressure deficit (vpd), and their impacts on crop-specific WUEc. Future impacts are also assessed through integrating machine learning models with climate projections from the CMIP6 framework under SSP2–4.5 and SSP5–8.5 scenarios to forecast WUEc trends from …

High Spatial Resolution Crop Type And Land Use Land Cover Classification Without Labels: A Framework Using Multi-Temporal Planetscope Images And Variational Bayesian Gaussian Mixture Model, Minh Tri Le

Mathematics, Physics, and Computer Science Faculty Articles and Research

Previous studies often combined high spatial resolution data (e.g., PlanetScope) with wider spectral range data (e.g., Sentinel-2) and relied on supervised classification methods to produce land use and land cover (LULC) maps. This study proposed a new unsupervised framework to generate crop type and LULC maps at high spatial resolution (< 5 m) using available PlanetScope data solely without requiring ground truths. We used PlanetScope surface reflectance images and their derived spectral indices during growing seasons to create multi-temporal input features, which were fed into an unsupervised Variational Bayesian Gaussian Mixture Model (VBGMM). The VBGMM, unlike the traditional unsupervised classification methods, (1) first estimated optimal parameters that are most suitable based on the input features and then (2) assigned pixels to the cluster with maximum posteriori probability of a mixture of several Gaussian distributions. The crop type and LULC maps were then generated by labeling the derived clusters using the best possible assignment method, referring to the existing crop type or LULC products. We evaluated the produced PlanetScope-based crop type and LULC maps using true labels, corresponding reference maps, and other unsupervised classification methods. The results demonstrated the robustness and effectiveness of the proposed framework in mapping crop types and LULC at 3–5 m pixels across various ecosystems, climate zones, and human-managed landscapes. The spatial patterns of PlanetScope-based maps were (1) highly comparable with all the reference datasets at 10–30 m spatial resolution and (2) better than the traditional GMM and K-means clustering methods. The VBGMM produced classification maps with high confidence, yielding class probabilities above 0.9 for over 90 % of all study areas. The area percentage for all crop type and LULC classes agreed well with their reference maps, with R2 of 0.95 and RMSE of 1.04 %. The confusion matrices using true labels indicated that PlanetScope-based maps achieved a higher overall accuracy of 84 % than the supervised referenced maps of 81 %. Besides, the entropy comparison showed that our framework-based maps were better at capturing fine-scale features such as developed areas within cities that commonly mix with open space and vegetation, deforestation and cropland conversion in South America, smallholder croplands in Africa and Asia, and generating homogeneous crop fields in North America. This study further highlighted the potential for future research to implement our proposed framework to generate timely and extensive annotated datasets, which can be used for operationally training machine learning models to map crop types and LULC, track deforestation, detect wildfires, and delineate flooded areas at larger scales using medium/coarse Earth observations.

Soil Health In Nebraska: Exploring Practitioners' Needs And Insights From A Long-Term Organic Farm, Ingrids Isabel Mata Vigil

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Soil health is foundational to sustainable agriculture, environmental resilience, and long-term food security. Yet, the adoption of soil health assessments remains limited, often perceived as too technical, costly, or difficult to implement in real-world contexts. To better understand these challenges, the first chapter presents findings from a statewide survey of 41 soil health practitioners in Nebraska, including farmers, extension educators, NRCS staff, and conservation professionals. Respondents highlighted the need for simpler, more accessible, and context-specific tools for soil health assessment that help practitioners make informed decisions aligned with their management goals. Complementing these insights, the second chapter includes an independent, …

Status Of The Western Australian Pastoral Rangelands 2024: Total Vegetative Cover, Cover Risk And Pasture Condition, Department Of Primary Industries And Regional Development, Western Australia

Natural resources published reports

The Department of Primary Industries and Regional Development (DPIRD) monitors and reports on the vegetation condition of pastoral rangelands in Western Australia. Two levels of reporting are provided: every 5 years a full report (this report) details the state, trend and risk of decrease of vegetation condition in the pastoral rangelands using information derived from remotely sensed and on-ground data; in the intervening years, short reports are provided based on remotely sensed data.

This full report is based on remotely sensed vegetation cover data, rainfall data, livestock data and station-level rangeland condition assessment (RCA) data available in November 2024. Data …

Digital Infrastructure For The Regenerative Movement: A Case Study Of The Mycelium Learning Network, Abigail Karparis

Journal of Nonprofit Innovation

The regenerative movement is gaining momentum worldwide, driven by communities working to restore ecological and social systems through place-based, culturally rooted action. Yet many of the groups leading this work, especially in the Global South or in hyper-local contexts, remain digitally invisible due to structural barriers, including limited access to appropriate technology, funding constraints, and misalignment between available tools and local values. Conventional digital infrastructures often exclude or marginalize these efforts, leaving regenerative practitioners disconnected from each other and from potential sources of support.

This article explores these challenges and presents a case study response: the co-creation of accessible, relational …

Enhancing Water Scarcity Resilience In Egypt Through Machine Learning-Driven Phenological Crop Mapping And Water Use Efficiency Analysis, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Aqil Tariq, Rejoice Thomas, Cyril Rakovski, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Agriculture forms the backbone of Egypt’s economy, with the Nile Valley and Delta serving as key production zones for crops like wheat, rice, and clover. However, the sector faces mounting pressure from water scarcity, as it depends almost entirely on the Nile for irrigation, making it necessary to map major crops for assessing Water Use Efficiency (WUE) and informing agricultural planning. In this study, we used machine learning (ML) techniques—specifically Support Vector Machine (SVM) to time-series phenological data and optical indices (Enhanced Vegetation Index (EVI), Bare Soil Index (BSI), Land Surface Water Index (LSWI), Normalized Difference Vegetation Index (NDVI), and …

Arts-Based Sustainability: From New York To Malawi, Martha B. Lerski

Publications and Research

Recognizing that libraries serve multiple constituencies and subject areas, this chapter documents and advocates for development of transdisciplinary arts-based research (ABR) and culture-related projects linked to environmental challenges. Libraries contribute collections and spaces, as well as the research of library and information scientists. Libraries are currently among invisible contributors to sustainability planning and services. The chapter will link this invisibility to the value of what visual arts refer to as negative space elements in subjects ranging from traditional ecological knowledge to environmental science. Library collections, projects, and research contribute to education for sustainable development (ESD) as required to achieve the …

Impact Of Seed Moisture And Temperature On Hemp Seed Germination, Paul Cockson, Andrea Webb, Natalia Martinez-Ochoa, Lindsey Moffitt, Robert Pearce, Manohar Chakrabarti

School of Integrative Biological & Chemical Sciences Faculty Publications

Germination rates of commercial lots of hemp have been highly variable, resulting in poor stand establishment. Germination rates in some seed lots have decreased by 50% after only 1 year of storage. The objective of this trial was to investigate the impact of seed storage conditions on seed germination over time. Industrial hemp (IH) seeds (cv. NWG2730) were harvested from the field. The seeds were cleaned, sorted, and dried to specific moisture contents (MC) 6%, 8%, 10%, and 14%. Seeds were subdivided, placed in hermetically sealed packets, and stored at temperatures of −20°C, 4°C, 10°C, or 21°C for 3, 6, …

Clearing Cloudy Or Coloured Water On Farms In Western Australia, Department Of Primary Industries And Regional Development, Western Australia

Natural resources factsheets

Cloudy or coloured water can be a nuisance when used for household purposes, and sometimes be unsuitable for livestock, irrigation, or crop spraying. The following is for general information only, it is recommended that people seek expert advice for treating cloudy or coloured water.

State And Transition Models For Mulga Rangelands Of Western Australia, Alison O'Donnell, Anna E. Richards, Suzanne Prober, Peter-Jon A. Waddell, Sarah Luxton, Ian Watson, Brett Abbott, Philip Thomas, Joshua E. Foster

Natural resources published reports

This report details a collaborative project between the Western Australian Department of Primary Industries and Regional Development and CSIRO that focused on developing State and Transition Models (STMs) for mulga rangelands in Western Australia. The overarching aim of the project was to improve the common understanding of the characteristics and dynamics of mulga rangeland ecosystems and the expected impacts of management. Specifically, the project aimed to collate expert knowledge and monitoring information using a nationally consistent framework to develop quantitative and dynamic STMs. The geographic scope of the project covers the extensive mulga rangelands of Western Australia, particularly the Gascoyne …