Agriculture Commons^™

Long-Term Variability Of Air Quality And Greenhouse Gas Emissions From Rice Crop Burning In Punjab During 2012–2020, Harsimranjit Kaur Romana, Dericks Praise Shukla, Ramesh P. Singh

Mathematics, Physics, and Computer Science Faculty Articles and Research

Punjab, India's primary rice and wheat production hub, has witnessed rapid expansion of paddy cultivation over the past two decades, driven by minimum support price incentives, changes in government policies, alignment of sowing with the monsoon season and the adoption of high-yielding varieties. This transition has intensified groundwater extraction and shortened the fallow period between rabi and kharif crop seasons, reducing the window between rice harvesting and wheat sowing, leading to widespread open-field burning of rice residue and recurrent post-monsoon air-quality deterioration across the Indo-Gangetic Plain. Despite numerous short-term or single-pollutant assessments, a spatially resolved, multi-pollutant and multi-decadal evaluation linking …

High Spatiotemporal Resolution Monitoring Of Crop Water Stress Across The Contiguous United States Using Harmonized Landsat And Sentinel-2 Data, Na Chen, Yanlei Feng, Na Wang, Jevan Yu, Mohammad Reza Alizadeh, Yifeng Cui, Ning Ye, Wenzhe Jiao, Joshua B. Fisher, César Terrer

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Accurate and timely monitoring of crop water stress is essential for efficient agricultural water management, ultimately maintaining and improving crop productivity. While Landsat has been used for this purpose, its temporal resolution hampers timely detection of crop water stress. The recently released Harmonized Landsat and Sentinel-2 Version 2.0 dataset, which enables a higher-frequency time series of satellite observations (2–3 days, 30 m), offers a promising solution to this challenge. However, its potential for crop stress monitoring remained unexplored. In this study, we utilized 923 HLS satellite tiles to assess crop water stress across the contiguous United States (CONUS). Crop water …

Effective Control Of Tomato Leaf Miner, Tuta Absoluta (Meyrick) (Lepidoptera: Gelechiidae) Using The Entomopathogenic Fungus, Beauveria Pseudobassiana Rehner & Humber In Commercial High-Arched Plastic Tunnels, Aya Fardoun, Nour Ezzeddine, Hagop S. Atamian, Hana Sobh, Houssam Shaib, Yusuf Abou Jawdah

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Background

The tomato leafminer, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is a highly invasive pest that causes significant damages to tomato crops globally. Its resistance to commonly used chemical insecticides has made management increasingly difficult, prompting the need for sustainable, effective alternatives. This study investigated the efficacy of a Lebanese isolate of Beauveria pseudobassiana as a biological control agent against T. absoluta, compared its performance to Bacillus thuringiensis and conventional pesticide mixtures under both controlled, commercial production conditions

Results

Three preliminary cage experiments were conducted under controlled infestation conditions using larvae reared from field-collected adults. Conidial suspensions of B. pseudobassiana …

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 …

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 …

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), …

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%, …

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.

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 …

Multi-Sensor Data Fusion And Gis-Drastic Integration For Groundwater Vulnerability Assessment With Rainfall Consideration, Wu Jiazhe, Dai Xinrui, Su Yangcheng, Zheng Xiangtian, Bushra Ghaffar, Rabiya Nasir, Ahsan Jamil, Zeeshan Zafar, Mohammad Suhail Meer, M. Abdullah-Al-Wadud, Rahila Naseer, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

In many areas of the world, particularly in arid and semi-arid regions, groundwater is the primary source of fresh water, and it supplies around one-third of the world's fresh water. Agriculture is the primary economic sector on the coast in the southern district (Nowshera). More food productivity is required due to the expanding population and diminishing agricultural lands, which increases the use of chemical pesticides and fertilizers in farming. The current study was conducted in northwestern parts of Pakistan to evaluate the impacts of the frequent use of pesticides and fertilizers in agricultural fields. Nine hydrogeological parameters were considered, and …

Identifying Opportunities For Nature-Based Solutions With Geospatialized Life Cycle Assessments And Fine-Scale Socioecological Data, Gabriela Shirkey, Annick Anctil, Ranjeet John, Venkatesh Kolluru, Leah Mungai, Herve Kashongwe, Lauren T. Cooper, Ilke Celik, Joshua B. Fisher, Jiquan Chen

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) …

Satellite Observations Indicate That Chia Uses Less Water Than Other Crops In Warm Climates, Brian Kirsch, Joshua B. Fisher, Thomas Piechota, Mohammad Hassani, Diego C. Suardiaz, Radhika Puri, Joseph Cahill, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Many parts of the world face severe and prolonged drought conditions, stressing the sustainability of water resources and agriculture. Transitioning to water-efficient crops is one strategy that can help adapt to water scarcity. An emerging drought-tolerant crop of interest is chia (Salvia hispanica). Yet, no study has compared its large-scale water use dynamics to those of widely established crops across the globe. Here, we use satellite data over multiple years to assess the water use efficiency of chia, alfalfa, corn, and soybean globally. Results show that chia consumed 13-38% less water than alfalfa, corn, and soy and assimilated …

How Advection Affects The Surface Energy Balance And Its Closure At An Irrigated Alfalfa Field, Tianxin Wang, Joseph Alfieri, Kanishka Mallick, Ariane Arias-Ortiz, Martha Anderson, Joshua B. Fisher, Manuela Girotto, Daphne Szutu, Joseph Verfaillie, Dennis Baldocchi

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Orbiting around the non-closure problem in eddy covariance, a new generation of high-resolution thermal imagery has revealed that advection may be more common than previously expected. To investigate this, we conducted an extensive study over an irrigated alfalfa field that experienced heat and moisture advection. Over the course of five analysis periods (37 days total), multiple tower arrays and profile measurements were deployed to measure the horizontal advection and vertical heat flux divergence. Latent heat flux (λE) measured at the anchor tower showed an enhancement (i.e., increase) due to both local and non-local processes. Locally, as a result of the …

Impact Of Land Use Dynamics On The Water Yields In The Gorgan River Basin, Masoomeh Yaghoobi, Aram Fathi, Shahryar Fazli, Wenzhao Li, Elham Haghshenas, Vahid Shokri Kuchak, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

This research investigates the future dynamics of water yield services in the Gorgan River Basin in the North of Iran by analyzing land cover changes from 1990 to 2020, using Landsat images and predicting up to 2040 with the Land Change Modeler and InVEST model under three scenarios: continuation, conservation, and mitigation. The results indicate significant shifts in agricultural land impacted water yields, which fluctuated from 324.7 million cubic meters (MCM) in 1990 to 279.7 MCM in 2010, before rising to 320.1 MCM by 2020. The study uniquely assesses the effects of land use changes on water yields, projecting a …

A Comparative Analysis Of Openet For Evaluating Evapotranspiration In California Almond Orchards, Kyle Knipper, Martha Anderson, Nicholas Bambach, Forrest Melton, Zac Ellis, Yun Yang, John Volk, Andrew J. Mcelrone, William Kustas, Matthew Roby, Will Carrara, Sebastian Castro, Ayse Kilic, Joshua B. Fisher, Anderson Ruhoff, Gabriel B. Senay, Charles Morton, Sebastian Saa, Richard G. Allen

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in …

Assessing Rice Phenological Features With Hyperspectral Imaging Insights From Earth Surface Mineral Dust Source Investigation (Emit), Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

In California's Central Valley, water management and crop health, particularly in rice cultivation, are critical. This paper details the application of Earth surface Mineral dust source InvesTigation (EMIT) hyperspectral imaging, specifically employing Spectral Correlation Mapper (SCM) and Spectral Information Divergence (SID), for precise phenological analysis. By aligning EMIT data with Hyperion satellite references, we address spectral and geographical discrepancies. Our methodology includes seasonal sampling of spectral curves to capture the phenological stages of rice. Results show a strong correlation (R ² = 0.86) between August EMIT and Reference dataset, emphasizing EMIT's utility in enhancing agricultural practices and water efficiency in …

Enhancing Sustainable Development Goals Through Future Vapor Pressure Deficit Analysis In The Nile River Basin, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Hani Sewilam, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Vapor Pressure Deficit (VPD) is crucial in meteorology and agriculture for understanding plant-environment interactions. Its application as an indicator in agricultural practices notably advances Sustainable Development Goals such as Zero Hunger (SDG 2) and Climate Action (SDG 13). This research focuses on the impact of climate change on agricultural productivity and food security in the Nile River Basin (NRB), emphasizing the role of VPD, temperature, and precipitation. Utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets from NEX-GDDP-CMIP6, the study analyzes key climatic variables that influence agricultural conditions. The study applies the Mann-Kendall test to evaluate VPD trends from 2000 …

Biological Control Of Three Major Cucumber And Pepper Pests: Whiteflies, Thrips, And Spider Mites, In High Plastic Tunnels Using Two Local Phytoseiid Mites, Yusuf Abou Jawdah, Nour Ezzedine, Aya Fardoun, Samer Kharroubi, Hana Sobh, Hagop S. Atamian, Margaret S. Skinner, Bruce Parker

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

To enhance food security, food safety, and environmental health, a bio-based integrated pest management (BIPM) strategy was evaluated at two coastal locations in Lebanon as an alternative to toxic pesticide sprays in commercial high-arched plastic tunnels common in many countries. The evaluation occurred during two cucumber and pepper cropping seasons: spring and fall. At each site, two commercial tunnels were used; farmers’ conventional practices were applied in one tunnel, while the BIPM approach was followed in the second tunnel. In the farmers’ practices, a total of 14 sprays of insecticide/acaricide mixtures were applied during the spring growing season, and 6 …

An Inquiry-Based Approach For Teaching Type Iii Functional Responses In Ecology, Jeremy L. Hsu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Maize (also known as corn) has played an important role in human agriculture ever since its domestication by indigenous peoples of Mexico some 10,000 years ago. The crop is now planted across the world, including in China. However, several invasive pests, including the fall armyworm Spodoptera frugiperda, have threatened this crop and lowered yield. Eupeodes corollae, an endemic syrphid hoverfly, has been proposed as a biological control agent. Here, students will explore the antagonistic relationship between S. frugiperda and E. corollae, with both species feeding on larvae of the other species, and learn about type III functional …

Mapping California Rice Using Optical And Sar Data Fusion With Phenological Features In Google Earth Engine, Li Wenzhao, Hesham El-Askary, Daniele C. Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

California, known for its diverse agriculture, is also a major producer of rice, especially in its northern regions in Sacramento River Valley. Traditional methods, predominantly reliant on optical-based satellite imagery, encounter limitations due to atmospheric interference and sensor resolution. The ability of Synthetic Aperture Radar (SAR) to penetrate atmospheric distortions and exhibit high sensitivity to vegetation structure presents a distinct advantage over optical-based methods. Utilizing Optical and SAR data fusion, this study advances the enhanced pixel-based phenological feature composite (Eppf) method using SVM classification algorithm, which can track phenological changes and patterns, providing valuable insights for agricultural planning and management. …

Weakly-Supervised Learning Method For The Recognition Of Potato Leaf Diseases, Junde Chen, Xiaofang Deng, Yuxin Wen, Weirong Chen, Adnan Zeb, Defu Zhang

Engineering Faculty Articles and Research

As a crucial food crop, potatoes are highly consumed worldwide, while they are also susceptible to being infected by diverse diseases. Early detection and diagnosis can prevent the epidemic of plant diseases and raise crop yields. To this end, this study proposed a weakly-supervised learning approach for the identification of potato plant diseases. The foundation network was applied with the lightweight MobileNet V2, and to enhance the learning ability for minute lesion features, we modified the existing MobileNet-V2 architecture using the fine-tuning approach conducted by transfer learning. Then, the atrous convolution along with the SPP module was embedded into the …

Total Prevention: A History Of Schistosomiasis In Japan, Alexander Bay

History Faculty Articles and Research

In Japan, schistosomiasis was endemic in Yamanashi Prefecture and a few other hotspot areas where the Miya’iri snail lived. The parasite’s lifecycle relied on the intermediary Miya’iri snail as well as the human host. Parasite eggs passed into the agrarian environment through untreated night soil used as fertiliser or through the culture of open defecation in rural Japan. Manmade rice fields and irrigation ditches, night soil covered paddies and highly refined growing seasons put people in flooded rice paddies to intensively work the land in the spring and summer. The disease was equally dependent on human intervention in the natural …

Extreme Development Of Dragon Fruit Agriculture With Nighttime Lighting In Southern Vietnam, Shenyue Jia, Son V. Nghiem, Seung-Hee Kim, Laura Krauser, Andrea E. Gaughan, Forest R. Stevens, Menas Kafatos, Khanh D. Ngo

Institute for ECHO Faculty Books and Book Chapters

Dragon fruit is widely grown in Southeast Asia and other tropical or subtropical regions. As a high-value cash crop ideal for exportation, dragon fruit cultivation has boomed during the past decade in southern Vietnam. Light supplementing during the winter months using artificial lighting sources is a widely adopted cultivation technique to boost productivity in the major dragon fruit planting regions of Vietnam. The application of electric lighting at night leads to a significant increase of nighttime light (NTL) observable by satellite sensors. The strong seasonality signal of NTL in dragon fruit cultivation enables identifying dragon fruit plantations using NTL images. …

Physicochemical And Pasting Properties Of Flour And Starch From Two New Cassava Accessions, Raphael Aidoo, Ibok Nsa Oduro, Jacob K. Agbenorhevi, William Otoo Ellis, Nana Baah Pepra-Ameyaw

Food Science Faculty Articles and Research

Some new cassava accessions have been developed and released because of their high yield, resistance to disease, adaptability to wider ecological environment, and less cost of production. However, their flour and starch properties have not been characterized for potential food applications. In the present study, starch and flour were produced from two new cassava accessions (Sika Bankye and Bankye Hemaa) and evaluated for their physicochemical and pasting properties. The flour samples recorded higher values for the various functional parameters compared to their starch counterparts. Both flour samples had a similar water absorption capacity (WAC) of ~263% but the associated …

Modeling Nitrous Oxide Emissions From Large-Scale Intensive Cropping Systems In The Southern Amazon, Ciniro Costa Jr., Gillian L. Galford, Michael T. Coe, Marcia Macedo, Kathijo Jankowski, Christine S. O'Connell, Christopher Neill

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Nitrogen (N) fertilizer use is rapidly intensifying on tropical croplands and has the potential to increase emissions of the greenhouse gas, nitrous oxide (N₂O). Since about 2005 Mato Grosso (MT), Brazil has shifted from single-cropped soybeans to double-cropping soybeans with maize, and now produces 1.5% of the world's maize. This production shift required an increase in N fertilization, but the effects on N₂O emissions are poorly known. We calibrated the process-oriented biogeochemical DeNitrification-DeComposition (DNDC) model to simulate N₂O emissions and crop production from soybean and soybean-maize cropping systems in MT. After model validation with …

A Microbiome Engineering Framework To Evaluate Rhizobial Symbionts Of Legumes, Kenjiro W. Quides, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Background

For well over a century, rhizobia have been recognized as effective biofertilizer options for legume crops. This has led to the widespread use of rhizobial inoculants in agricultural systems, but a recurring issue has emerged: applied rhizobia struggle to provide growth benefits to legume crops. This has largely been attributed to the presence of soil rhizobia and has been termed the ‘rhizobial competition problem.’

Scope

Microbiome engineering has emerged as a methodology to circumvent the rhizobial competition problem by creating legume microbiomes that do not require exogenous rhizobia. However, we highlight an alternative implementation of microbiome engineering that focuses …

Assessment Of Agricultural Drought Considering The Hydrological Cycle And Crop Phenology In The Korean Peninsula, Chul-Hee Lim, Seung Hee Kim, Jong Ahn Chun, Menas Kafatos, Woo-Kyun Lee

Mathematics, Physics, and Computer Science Faculty Articles and Research

Hydrological changes attributable to global warming increase the severity and frequency of droughts, which in turn affect agriculture. Hence, we proposed the Standardized Agricultural Drought Index (SADI), which is a new drought index specialized for agriculture and crops, and evaluated current and expected droughts in the Korean Peninsula. The SADI applies crop phenology to the hydrological cycle, which is a basic element that assesses drought. The SADI of rice and maize was calculated using representative hydrological variables (precipitation, evapotranspiration, and runoff) of the crop growing season. In order to evaluate the effectiveness of SADI, the three-month Standardized Precipitation Index, which …

Reporting Charcoal Rot In Chia And Developing A Susceptibility Assay, Reis M. Misaka, Hagop S. Atamian Dr., Julien Besnard Dr.

Student Scholar Symposium Abstracts and Posters

Chia (Salvia Hispanica) cross breeds were planted in the summer of 2018 with the intent of selective breeding for agricultural benefit. Preexisting pathogens in the soil caused 40-50% fatality of adult plants. This was surprising due to the precursory knowledge that chia has antibiotic and antifungal oils (Elshafie et. al. 2018); chia was only recently documented to be susceptible to Fusarium wilt (Fusarium oxysporum). The primary pathogen responsible was identified as Macrophomina phaseolina (aka charcoal rot); a widespread soilborne pathogen which has multiple commercial hosts (Su et. al. 2001).

M. phaesolina on wheat seed vector where used as …

An Attainable Global Vision For Conservation And Human Well-Being, Heather M. Tallis, Peter L. Hawthorne, Stephen Polasky, Joseph Reid, Michael W. Beck, Kate Brauman, Jeffrey M. Bielicki, Seth Binder, Matthew G. Burgess, Emily Cassidy, Adam Clark, Joseph Fargione, Edward T. Game, James Gerber, Forest Isbell, Joseph Kiesecker, Robert Mcdonald, Marc Metian, Jennifer L. Molnar, Nathan D. Mueller, Christine S. O'Connell, Daniel Ovando, Max Troell, Timothy M. Boucher, Brian Mcpeek

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A hopeful vision of the future is a world in which both people and nature thrive, but there is little evidence to support the feasibility of such a vision. We used a global, spatially explicit, systems modeling approach to explore the possibility of meeting the demands of increased populations and economic growth in 2050 while simultaneously advancing multiple conservation goals. Our results demonstrate that if, instead of “business as usual” practices, the world changes how and where food and energy are produced, this could help to meet projected increases in food (54%) and energy (56%) demand while achieving habitat protection …