Scholarly Works, School of Plant and Environmental Sciences

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Vegetation Structure and Distribution Across Scales in a Large Metropolitan Area: Case Study of Austin MSA, Texas, USA
Jamil, Raihan; Julian, Jason P.; Steele, Meredith K. (MDPI, 2025-03-03)
The spatial distribution of vegetation across metropolitan areas is important for wildlife habitat, air quality, heat mitigation, recreation, and other ecosystem services. This study investigated relationships between vegetation patterns and parcel characteristics at multiple scales of the Austin Metropolitan Statistical Area (MSA), a rapidly growing region in central Texas characterized by diverse biophysical and socioeconomic landscapes. We used LiDAR data to map vegetation types and distributions across a 6000 km² study area. Principal component analysis (PCA) and regression models were employed to explore tree, shrub, and grass cover across parcels, cities, and the MSA, considering home value, age, size, and distance to the city center. At the MSA scale, tree and shrub cover were higher in the Edwards Plateau than in the Blackland Prairie ecoregion. Tree cover increased with parcel size and home value, especially in suburban areas. Older parcels had more mature trees, though less so in the grass-dominated Blackland Prairie. Shrub cover was higher on larger parcels in the Edwards Plateau, while the Blackland Prairie showed the opposite trend. PCA explained 60% of the variance, highlighting links between vegetation and urban development. Our findings reveal how biophysical and socioeconomic factors interact to shape vegetation, offering considerations for land use, housing, and green infrastructure planning.
Functional Verification of the Soybean Pseudo-Response Factor GmPRR7b and Regulation of Its Rhythmic Expression
Song, Ziye; Liu, Jia; Qian, Xueyan; Xia, Zhengjun; Wang, Bo; Liu, Nianxi; Yi, Zhigang; Li, Zhi; Dong, Zhimin; Zhang, Chunbao; Zhang, Bo; Tadege, Million; Dong, Yingshan; Li, Yuqiu (MDPI, 2025-03-09)
The pseudo response regulator (PRR) gene is an important component of the core oscillator involved in plant circadian rhythms and plays an important role in regulating plant growth and development and stress responses. In this study, we investigated the function of GmPRR7b by overexpression and gene editing approaches. It was found that GmPRR7b plays a role in delaying flowering. While GmPRR7b overexpressing plants showed significantly delayed flowering compared to untransformed WT, GmPRR7b edited plants flowered earlier than the control WT. On the basis of previous research results and bioinformatics analysis, we re-identified 14 soybean PRR genes and analysed their rhythmic expression. Based on the rhythmic expression pattern, we found that GmPRR5/9a and GmPRR5/9b interacted with GmPRR7b by yeast two-hybrid and bimolecular fluorescence complementation (BiFC) experiments. Combined with the expression regulatory networks of the GmPRR7b, we inferred a possible regulatory mechanism by which GmPRR7b affects flowering through quit rhythm expression. These research elements provide valuable references for understanding growth, development, and circadian regulation in soybean.
Recovery quality index as a tool for monitoring the mined land reclamation
Quintiliano Alves, Maísa; Rodrigues de Assis, Igor; Lima Neves, Júlio César; Zeidan Oliveira, Fernanda; de Abreu Anunciaçāo, Amanda; Silva Moreira, Sandro Lúcio; Stewart, Ryan Daniel (Elsevier, 2024-02-10)
Many ecosystems are being severely degraded, leading the United Nations to deem 2021–2030 as the Decade on Ecosystem Restoration. To be successful, this effort requires robust monitoring tools to assess land reclamation practices. This study aimed to evaluate the quality of recovery efforts in mined areas by developing a Recovery Quality Index (RQI) based on soil and vegetation indicators. Using the heavily mined Iron Quadrangle region of Brazil as an example, four undisturbed reference areas were selected: Atlantic Forest; ferruginous rupestrian grassland with dense vegetation; ferruginous rupestrian grassland with sparse vegetation; and quartzite rupestrian grassland. Four areas directly or indirectly affected by mining were selected, including an environmental compensation area set aside 5 years prior to the study, two sterile piles that had undergone recovery for 15 and 20 years, and a cave area with 15 years of recovery. Two vegetation parameters and 34 soil attributes were used in a Principal Component Analysis (PCA) to select indicators and scores. Vegetative parameters had the lowest RQI weights. Soil physical indicators tended to be the most important. RQI values were lowest when Atlantic Forest was used as the reference, showing that the forest was a unique ecosystem, and the cave site had lower RQI scores than the other restored sites, indicating the high degree of disturbance that occurred in that low-lying area. The oldest sterile pile tended to have higher RQI values than the newest and similar values to the less disturbed compensation areas. The recovery quality index values were similar in all areas, with 5 to 20 years in the recovery process, showing that the rehabilitation process is slow in this environment.
Breeding Potential for Increasing Carbon Sequestration via Rhizomatous Grain Sorghum
Zheng, Yaojie; Hays, Dirk B.; Jessup, Russell W.; Zhang, Bo (MDPI, 2025-02-26)
Rhizomes, key carbon sequestration sinks in perennial crops, are hypothesized to exhibit a trade-off with grain yield. This study evaluated rhizomatous grain sorghum populations for increasing carbon sequestration potential. Twelve F_3:4 heterogeneous inbred families (HIFs) from a Sorghum bicolor (L.) Moench × Sorghum propinquum (Kunth) Hitchc cross were tested in a greenhouse, and two F_4:5 HIF progenies were field tested. Traits measured included rhizome biomass, root biomass, total belowground biomass, and grain yield. Rhizome biomass showed high heritability (0.723) and correlated strongly with belowground biomass (r₁ = 0.95; r₂ = 0.97) in both F_4:5 HIFs, suggesting the potential of rhizomes to sequester carbon. Contrary to the hypothesized trade-off, a positive relationship between rhizome biomass and grain yield was observed, potentially via rhizome-derived shoots, and individual plants pyramiding high rhizome biomass, biomass yield, and grain yield were also identified. Using bulked segregant analysis (BSA), twenty simple sequence repeat (SSR) markers linked to eight genomic regions associated with rhizome presence were identified, with five regions potentially being novel. This study suggests that breeding rhizomatous grain sorghum with high rhizome biomass could enhance carbon sequestration while preserving agronomic yields, offering new insights for future breeding and mapping initiatives.
scGFP: A Single-Cell RNA-Seq Study of Correlation Methods for Promoter-Reporter and Native Gene Expression
Chau, Tran N.; Alajoleen, Razan; Kundu, Sanchari; Bargmann, Bastiaan; Li, Song (2025-02-21)
Single-cell RNA sequencing (scRNA-seq) enables the exploration of transcriptomic heterogeneity at the individual cell level, facilitating the identification of distinct cell types, rare populations, and dynamic gene expression patterns over time. This technique has advanced plant biology by enabling cross-species comparisons and uncovering gene regulatory networks. While gene co-expression networks are essential for understanding these networks, commonly used correlation methods have primarily been applied to microarray and bulk RNA-seq datasets, with limited validation in single-cell contexts. This study uses an Arabidopsis scRNA-seq dataset to evaluate the performance of various correlation methods in comparing promoter-reporter genes with their native counterparts, addressing challenges such as zero-inflation and demonstrating the benefits of pseudo-bulk analysis and imputation techniques for improving correlation accuracy.
The Impact Aerobic and Anaerobic Incubations of Poultry Litter Have on Class 1 Integron Resistome and Microbiome
Maurer, John J.; Hoke, Alexa; Das, Keshav C.; Wu, Jian; Williams, Mark A.; Kinstler, Sydney; Ritz, Casey; Pittman, Gregory P.; Berghaus, Roy; Lee, Margie D. (MDPI, 2025-02-13)
Animal manure is a desirable fertilizer because of its rich nitrogen, but it also contains a large and diverse reservoir of antimicrobial resistance (AMR) genes (ARGs). To reduce this AMR reservoir, five treatments (passive aeration, forced aeration, static or anaerobic incubations, autoclaving) were assessed for their impact on the poultry litter resistome. Bacterial DNA was extracted from the litter and the qPCR-estimated copy number of 16S rrs, class1 integrons (intI1) and associated resistance genes (aadA, sul1). Then, 16S amplicon metagenomic sequencing was used to determine community diversity and composition. Depending on incubation conditions, class 1 integrons and their associated ARGs were reduced by 0.5 to 1.0 Log₁₀/g poultry litter. Only autoclaving reduced integrons and associated AMR genes by three Log₁₀. Changes in AMR abundance reflected fluctuations in litter bacteriome composition at the family, genus, and sequence variant level. There was a negative correlation between class 1 integron and AMR genes, with genera belonging to Actinobacteria, Firmicutes, and Proteobacteria phyla. While these poultry litter treatments failed to reduce AMR abundance, aerobic and anaerobic treatments reduced taxons that contained pathogenic species. The approach to remediating resistance in poultry litter may be more effective if is focused on reducing bacterial pathogens.
Precision Soil Moisture Monitoring Through Drone-Based Hyperspectral Imaging and PCA-Driven Machine Learning
Vahidi, Milad; Shafian, Sanaz; Frame, William Hunter (MDPI, 2025-01-28)
Accurately estimating soil moisture at multiple depths is essential for sustainable farming practices, as it supports efficient irrigation management, optimizes crop yields, and conserves water resources. This study integrates a drone-mounted hyperspectral sensor with machine learning techniques to enhance soil moisture estimation at 10 cm and 30 cm depths in a cornfield. The primary aim was to understand the relationship between root zone water content and canopy reflectance, pinpoint the depths where this relationship is most significant, identify the most informative wavelengths, and train a machine learning model using those wavelengths to estimate soil moisture. Our results demonstrate that PCA effectively detected critical variables for soil moisture estimation, with the ANN model outperforming other machine learning algorithms, including Random Forest (RF), Support Vector Regression (SVR), and Gradient Boosting (XGBoost). Model comparisons between irrigated and non-irrigated treatments showed that soil moisture in non-irrigated plots could be estimated with greater accuracy across various dates. This finding indicates that plants experiencing high water stress exhibit more significant spectral variability in their canopy, enhancing the correlation with soil moisture in the root zone. Moreover, over the growing season, when corn exhibits high chlorophyll content and increased resilience to environmental stressors, the correlation between canopy spectrum and root zone soil moisture weakens. Error analysis revealed the lowest relative estimation errors in non-irrigated plots at a 30 cm depth, aligning with periods of elevated water stress at shallower levels, which drove deeper root growth and strengthened the canopy reflectance relationship. This correlation corresponded to lower RMSE values, highlighting improved model accuracy.
Effects of Sericea Lespedeza Supplementation on Steers Grazing Wild-Type Endophyte-Infected Tall Fescue
Poudel, Sanjok; Pent, Gabriel J.; Fike, John H.; Zeller, Wayne E.; Davis, Brittany E. (MDPI, 2025-01-28)
Condensed tannins (CTs) in certain leguminous forages can mitigate toxic alkaloid absorption linked to fescue toxicosis due to their high affinity towards various steroidal and protein-like alkaloids. However, their use as feed supplements remains underexplored. This study evaluated the impact of CT-rich sericea lespedeza (Lespedeza cuneata) pellets on the post-ingestive effects of fescue toxicosis. Twelve steers on wild-type endophyte-infected tall fescue pastures received either sericea lespedeza pellets (LES) or LES with polyethylene glycol (LPEG; negative control) for 12 weeks over three consecutive summers. Body weight, hair coat scores, temperatures (rectal and extremity), cortisol levels, and caudal artery lumen area were measured every four weeks. Steers fed LES showed trends toward higher ADG (p = 0.0999) and reduced hair retention (p = 0.0547) compared to those fed LPEG. Steers on LES also showed hotter tail skin temperatures (p = 0.0053) and cooler rectal temperatures (p < 0.0001) compared to those fed LPEG. LES-fed steers had a 21% larger caudal artery lumen area (p < 0.01), suggesting reduced vasoconstriction. Additionally, LES-fed steers tended to have lower hair cortisol (p = 0.0746), indicating reduced chronic stress. These results suggest that supplementation with CTs may alleviate the post-ingestive effects of fescue toxicosis, potentially by improving blood flow and reducing stress. However, further research is needed to determine whether CTs directly reduce alkaloid absorption, as well as to validate the long-term efficacy of CT supplementation.
Treatment of cattle with ivermectin and its effect on dung degradation and larval abundance in a tropical savanna setting
Ruhinda, Miriam; Xia, Kang; Rist, Cassidy; Shija, Gerald; Lyimo, Issa N.; Meza, Felician; Brewster, Carlyle; Chaccour, Carlos; Rabinovich, N. Regina; Schuerch, Roger (Elsevier, 2024-12-12)
When ingested as part of a blood meal, the antiparasitic drug ivermectin kills mosquitoes, making it a candidate for mass drug administration (MDA) in humans and livestock to reduce malaria transmission. When administered to livestock, most ivermectin is excreted unmetabolized in the dung within 5 days post administration. Presence of ivermectin, has been shown to adversely affect dung colonizers and dung degradation in temperate settings; however, those findings may not apply to, tropical environment, where ivermectin MDA against malaria would occur. Here we report results of a randomized field experiment conducted with dung from ivermectin-treated and control cattle to determine the effect of ivermectin on dung degradation in tropical Tanzania. For intact pats, we measured termite colonization, larval numbers and pat wet and dry weights. Pat organic matter was interpolated from a subsample of the pat (10 g wet weight). Additionally, we counted larvae growing in the treated and untreated pats in a semi-field setting. We found that termites colonized ivermectin pats more readily than controls. Despite this, wet weight decreased significantly slower in the ivermectin-treated pats in the first two weeks. As water was lost, sub-sample dry weight increased, and organic matter decreased similarly over time for the treatment and control. Interpolated for whole pats, total organic matter was higher, and larval counts were lower in the ivermectin-treated pats after the first month. Our results demonstrate an effect of ivermectin and its metabolites on dung degradation and fauna in a tropical savanna setting. Because slow dung degradation and low insect abundance negatively impact pastureland, these non-target, environmental effects must be further investigated within the context of real-world implementation of ivermectin MDA in cattle and weighed against the potential benefits for malaria control.
Evaluation of Insecticides to Control Stink Bug and Broad Headed Bug in Edamame, 2021
Sutton, Kemper L.; Wilczek, Daniel; Kuhar, Thomas P.; McIntyre, Kelly; Rideout, Steven L.; Zhang, Bo (Oxford University Press, 2022-06-23)
UAV‐Based Prediction of Sugarbeet Yield and Quality
Walsh, Olga S. (Wiley, 2023-03-07)
In Idaho, nitrogen (N) and water management are two major factors affecting sugarbeet yield and quality. If sugarbeet crop yield potential can be accurately predicted early in the growing season, then the crop can be topdressed based on crop nutrient requirements. This approach has the potential to improve the economic returns to sugarbeet growers and processors. The objective of this study was to assess the feasibility of predicting root yield and estimated recoverable sugar using UAV‐based normalized difference vegetation index (NDVI) in sugarbeets grown under varied N and water rates.
Teff: Food for the Future
Lamichhane, Ritika; Walsh, Olga S. (Wiley, 2023-03-06)
Teff (Eragrostis tef) is a native Ethiopian grain crop that is gaining popularity in the United States as a nutritious grain and a high quality forage crop. It is a reliable low‐risk crop that is relatively resistant to biotic and abiotic stresses and can be grown under moisture stress or waterlogged conditions. While it has a lot of potential, more research and education on teff is needed, particularly in the area of breeding and in the cropʼs nutrient and water requirements.
Drones for Fruit Producers
Nambi, Eva; Walsh, Olga S.; Ansah, Emmanuella Owusu; Lamichhane, Ritika (Wiley, 2022-07-12)
Fruit orchards require site‐specific or even individual‐tree‐specific management throughout the growing season. Remote sensing via drones, or unmanned aerial vehicles (UAVs), is becoming more common among growers and is useful for real‐time crop monitoring, weed detection, tree classification, water stress assessment, disease detection, yield and fruit quality estimation, and various pest and nutrient management strategies.
Impact of 2021 Drought in the Pacific Northwest
Ansah, Emmanuella Owusu; Walsh, Olga S. (Wiley, 2021-11-03)
Drought causes tremendous losses to agriculture and impacts water supply, energy production, and public health. This year’s drought in Idaho is extreme due to a very dry spring followed by an extreme, prolonged summer heat wave. This article will provide an overview of the current drought in the Pacific Northwest, how crops have been impacted, and look at ways farmers can adapt.
Varietal Response of Wheat and Barley to Nitrogen
Walsh, Olga S.; Spackman, J. A.; Adjesiwor, A. T.; Lamichhane, R.; Ansah, E. Owusu (Wiley, 2021-09-03)
Recap of the 2021 Western Society of Crop Science Virtual Meeting
Walsh, Olga S.; Islam, Anowarul; Kesoju, Sandya; Marsalis, Mark; Ghimire, Rajan (Wiley, 2021-08)
Monitoring Wind and Particle Concentrations Near Freshwater and Marine Harmful Algal Blooms (HABs)
Bilyeu, Landon; Gonzalez-Rocha, Javier; Hanlon, Regina; AlAmiri, Noora; Foroutan, Hosein; Alading, Kun; Ross, Shane D.; Schmale, David G. III (Royal Society of Chemistry, 2023-10-05)
Harmful algal blooms (HABs) are a threat to aquatic ecosystems worldwide. New information is needed about the environmental conditions associated with the aerosolization and transport of HAB cells and their associated toxins. This information is critical to help inform our understanding of potential exposures. We used a ground-based sensor package to monitor weather, measure airborne particles, and collect air samples on the shore of a freshwater HAB (bloom of predominantly Rhaphidiopsis, Lake Anna, Virginia) and a marine HAB (bloom of Karenia brevis, Gulf Coast, Florida). Each sensor package contained a sonic anemometer, impinger, and optical particle counter. A drone was used to measure vertical profiles of windspeed and wind direction at the shore and above the freshwater HAB. At the Florida sites, airborne particle number concentrations (cm−3) increased throughout the day and the wind direction (offshore versus onshore) was strongly associated with these particle number concentrations (cm−3). Offshore wind sources had particle number concentrations (cm−3) 3 to 4 times higher than those of onshore wind sources. A predictive model, trained on a random set of weather and particle number concentrations (cm−3) collected over the same time period, was able to predict airborne particle number concentrations (cm−3) with an R squared value of 0.581 for the freshwater HAB in Virginia and an R squared value of 0.804 for the marine HAB in Florida. The drone-based vertical profiles of the wind velocity showed differences in wind speed and direction at different altitudes, highlighting the need for wind measurements at multiple heights to capture environmental conditions driving the atmospheric transport of aerosolized HAB toxins. A surface flux equation was used to determine the rate of aerosol production at the beach sites based on the measured particle number concentrations (cm−3) and weather conditions. Additional work is needed to better understand the short-term fate and transport of aerosolized cyanobacterial cells and toxins and how this is influenced by local weather conditions.
Wheat Yield and Protein Estimation with Handheld and Unmanned Aerial Vehicle-Mounted Sensors
Walsh, Olga S.; Marshall, Juliet M.; Nambi, Eva; Jackson, Chad A.; Ansah, Emmanuella Owusu; Lamichhane, Ritika; McClintick-Chess, Jordan; Bautista, Francisco (MDPI, 2023-01-10)
Accurate sensor-based prediction of crop yield and grain quality in-season would enable growers to adjust nitrogen (N) fertilizer management for optimized production. This study assessed the feasibility (and compared the accuracy) of wheat (Triticum aestivum L.) yield, grain N uptake, and protein content prediction with in-season crop spectral reflectance measurements (Normalized Difference Vegetative Index, NDVI) obtained with a handheld GreenSeeker (GS) sensor and an Unmanned Aerial Vehicle (UAV)-mounted sensor. A strong positive correlation was observed between GS NDVI and UAV NDVI at Feekes 5 (R2 = 0.78) and Feekes 10 (R2 = 0.70). At Feekes 5, GS NDVI and UAV NDVI explained 42% and 43% of wheat yield, respectively. The correlation was weaker at Feekes 10 (R2 of 0.34 and 0.25 for GS NDVI and UAV NDVI, respectively). The accuracy of wheat grain N uptake prediction was comparable to that of yield: the R2 values for GS NDVI and UAV NDVI were 0.53 and 0.37 at Feekes 5 and 0.13 and 0.20 at Feekes 10. We found that neither GS NDVI nor UAV NDVI in-season data were useful in prediction of wheat grain protein content. In conclusion, wheat yield and grain N uptake can be estimated at Feekes 5 using either handheld or aerial based NDVI with comparable accuracy.
Virginia Small Grain Official Variety Trials, 2024
Walsh, Olga S.; Santantonio, Nicholas; Bishop, Caleb; Khulal, Aarati; Kumari, Sheetal; Rathore, Jitender; Wright, Matthew (2024-12-11)
Virginia Corn Hybrid Trials in 2023
Walsh, Olga S.; Bishop, Caleb; Santantonio, Nicholas; Khulal, Aarati; Kumari, Sheetal; Rathore, Jitender (2024-10-09)

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