Haile Tewolde’s research while affiliated with Agricultural Research Service and other places

The effect of soil carbon on the available water content (AWC) has garnered considerable attention. An increasing number of studies have recognized a beneficial impact of soil organic matter (SOM) on available water content (AWC); however, results are not consistent regarding the magnitude of soil organic carbon (SOC) effect on AWC. In particular, the critical SOC range necessary for enhancing AWC requires clarification. Accordingly, 165 samples were collected from four sites, where two sites received poultry litter (PL) and two sites did not, covering a wide range of carbon contents from low to high (4.5–22.9 g kg ⁻¹ ). The bulk density was the same, and the soils were tested for their field capacity (FC) and permanent wilt point (PWP) in the lab. The results revealed that there was no significant correlation between the clay and AWC, and a significant positive relationship between SOC and AWC was exhibited, suggesting that the increase in AWC mostly resulted from the increase in SOC. However, the AWC did not change significantly with increasing SOC when the SOC was below 10 g kg ⁻¹ , whereas a significant increase in AWC occurred when the SOC increased from 10 to 14 g kg ⁻¹ . The largest increment in AWC occurred when the SOC increased from 14 to 18 g kg ⁻¹ , but the increase in AWC with increasing SOC decreased when the SOC was above 18 g kg ⁻¹ . Thus, a critical range of SOC for AWC from 14 to 18 g kg ⁻¹ could significantly improve the soil water‐holding capacity. Additionally, most soil samples within the critical SOC range were collected from sites that received PL. Thus, this study also evaluated the enhancement of AWC by PL application, which efficiently improved the soil water‐holding capacity.

This study explored the efficacy of soil aggregate indices in quantifying soil structural development, utilizing 5‐year field experiment data from the Southeastern United States. The experiment utilized a split‐plot design with cover crops (native vegetation as control, cereal rye (Secale cereale L.), winter wheat (Triticum aestivum), hairy vetch (Vicia villosa), and mustard (Brassica rapa) plus cereal rye as the main factor and fertilizer source (no fertilizer as control, inorganic fertilizer with phosphorus, potassium, and elemental sulfur, and poultry litter) as the secondary factor. Aggregate size fractions were determined using the wet‐sieving method, and aggregate stability index (ASI), mean weight diameter (MWD), geometric mean diameter (GMD), and fractal dimension (FD) were calculated to assess soil structural stability. Main effects results indicated that cereal rye (55.11%) and poultry litter (50.97%) exhibited the highest ASI values. The highest MWD, GMD, and FD were observed under mustard plus cereal rye (1.187 mm), cereal rye (0.462 mm), and hairy vetch (2.573), respectively. Principal component analysis revealed that cover crops significantly improved soil aggregate structure and stability, overcoming limitations of sole fertilization practices. Regression analysis suggested that ASI, MWD, and GWD positively correlated with soil organic carbon, whereas FD negatively correlated with MWD, GMD, and ASI. Principal component analysis exhibited that FD decreased with increasing soil organic carbon, ASI, MWD, and GMD, demonstrating that lower FD values indicate enhanced soil aggregation and structure. Assessed indices, FD included, effectively gauged soil structural stability. These metrics should be prioritized in managerial decisions to support soil productivity and health in agricultural systems.

Interest in improving the long-term sustainability of agricultural production systems has focused on identifying management practices that promote soil health. No tillage, cover cropping, and amending soils with broiler (Gallus gallus domesticus L.) litter are commonly adopted conservation practices that have been shown to improve soil fertility and crop yield. However, the overall influence of these conservation practices on soil health in the southeastern US are not well understood. Thus, a study was conducted to evaluate the influence of tillage, broiler litter (BL) applications, and cropping systems on soil biochemical properties. Soils were collected from field research plots under long-term management (>than 25 years of tillage, 15 years of broiler litter application, and 15 years of cropping system). Soil microbial biomass, C, N, and P, amidohydrolases, and dissolved organic matter (DOM) were evaluated as indicators of soil health. Adopting tillage and BL into the agricultural management system modified the biochemical parameters of the soils evaluated. Most of these modifications occurred in the 0–5 cm depth. Higher microbial biomass carbon (MBC; 85%) and nitrogen (MBN; 10%) and enzyme activities of asparaginase (65%) and glutaminase (70%) were observed in the 0–5 cm depth under no tillage (NT) compared to conventional tillage (CT), indicating greater biological activities were established in these soil ecosystems. Broiler litter applications increased microbial biomass N and activities of asparaginase and glutaminase in both soil depths. In addition, microbial biomass phosphorus (MBP) was increased following BL application in the 0–5 cm depth. The results suggest that long-term management of NT and BL additions can improve the health of eroded southeastern US soils by altering the soil biochemical parameters.

The application of remote sensing, which is non-destructive and cost-efficient, has been widely used in crop monitoring and management. This study used a built-in multispectral imager on a small unmanned aerial vehicle (UAV) to capture multispectral images in five different spectral bands (blue, green, red, red edge, and near-infrared), instead of satellite-captured data, to monitor soybean growth in a field. The field experiment was conducted in a soybean field at the Mississippi State University Experiment Station near Pontotoc, MS, USA. The experiment consisted of five cover crops (Cereal Rye, Vetch, Wheat, Mustard plus Cereal Rye, and native vegetation) planted in the winter and three fertilizer treatments (Fertilizer, Poultry Liter, and None) applied before planting the soybean. During the soybean growing season in 2022, eight UAV imaging flyovers were conducted, spread across the growth season. UAV image-derived vegetation indices (VIs) coupled with machine learning (ML) models were computed for characterizing soybean growth at different stages across the season. The aim of this study focuses on monitoring soybean growth to predict yield, using 14 VIs including CC (Canopy Cover), NDVI (Normalized Difference Vegetation Index), GNDVI (Green Normalized Difference Vegetation Index), EVI2 (Enhanced Vegetation Index 2), and others. Different machine learning algorithms including Linear Regression (LR), Support Vector Machine (SVM), and Random Forest (RF) are used for this purpose. The stage of the initial pod development was shown as having the best predictability for earliest soybean yield prediction. CC, NDVI, and NAVI (Normalized area vegetation index) were shown as the best VIs for yield prediction. The RMSE was found to be about 134.5 to 511.11 kg ha−1 in the different yield models, whereas it was 605.26 to 685.96 kg ha−1 in the cross-validated models. Due to the limited number of training and testing samples in the K-fold cross-validation, the models’ results changed to some extent. Nevertheless, the results of this study will be useful for the application of UAV remote sensing to provide information for soybean production and management. This study demonstrates that VIs coupled with ML models can be used in multistage soybean yield prediction at a farm scale, even with a limited number of training samples.

Poultry litter (PL) is known to have residual effects on crop productivity long after applications cease. Whether this advantage is greater if applied by subsurface vs. surface broadcast is unknown. The objective of this study was to determine whether the residual benefit of PL to corn and cotton production is greater if applied in subsurface bands vs. surface broadcast and identify PL components contributing to this effect. The residual effect of PL applied by the two methods or synthetic nitrogen (sN) at seven plant available N rates (0–292 kg ha−1 yr−1) in 2014–2015 was tested on corn and cotton in 2016–2019. Corn was grown without applying PL or sN in 2016, and cotton was grown in 2017–2019 after applying 90 kg ha−1 yr−1 sN to all plots. Corn produced 40% greater grain and cotton produced 29% more lint yield due to residuals from PL than sN. Residuals from PL distinctly increased cotton leaf K over sN regardless of the method of application. Corn and cotton yield benefits from PL residual were greater if applied by subsurface banding vs. surface broadcast. This difference diminished with time. The overall results show PL components persist in the soil for up to 4 years and affect corn and cotton production, but this persistence is greater if the PL is applied by subsurface banding. This study identified K as the key PL nutrient that persisted in the soil and benefited cotton yield 4 years after the last application.

Engineering fibers with nanomaterials is an effective way to modify their properties and responses to external stimuli. In this study, we doped cotton fibers with silver nanoparticles, both on the surface (126 ± 17 nm) and throughout the fiber cross section (18 ± 4 nm), and examined the resistance to soil biodegradation. A reagent-free one-pot treatment of a raw cotton fabric, where noncellulosic constituents of the raw cotton fiber and starch sizing served as reducing agents, produced silver nanoparticles with a total concentration of 11 g/kg. In a soil burial study spanning 16 weeks, untreated cotton underwent a sequential degradation process—fibrillation, fractionation, and merging—corresponding to the length of the soil burial period, whereas treated cotton did not exhibit significant degradation. The remarkable biodegradation resistance of the treated cotton was attributed to the antimicrobial properties of silver nanoparticles, as demonstrated through a test involving the soil-borne fungus Aspergillus flavus. The nonlinear loss behavior of silver from the treated cotton suggests that nanoparticle depletion in the soil depends on their location, with interior nanoparticles proving durable against environmental exposure.

Introgression of donor germplasm from Gossypium tetraploid species into Upland cotton (G. hirsutum L.) would help alleviate the constricted genetic base of Upland cotton and increase opportunities for genetic improvement. The objective of this research was to determine whether the mineral nutrition and fiber quality of cotton are affected by and might be improved using 11 quasi-isogenic BC5Sn interspecific chromosome substitution (CS) lines of Upland cotton. The CS lines were bred previously for disomic replacement of Upland cotton chromosomes 01, 04, 07, 15 (part), and 18 by homologs from G. barbadense L. and G. tomentosum Nutt. ex Seem., and another for part of Upland chromosome 08 by G. tomentosum. The CS lines were grown in two fields along with a related Upland inbred, TM-1. Leaf mineral nutrition of the CS lines was measured based on samples taken two weeks after flowering. Fiber quality was based on bolls hand-picked at harvest. CS lines involving 1 and 18 were associated with leaf nutrient improvement. CS-B18 improved leaf N, P, K, and Zn relative to TM-1. All fiber quality traits were affected by CS lines, but none led to more than two fiber quality improvements. CS-B15Lo and CS-B18 improved fiber strength and elongation, whereas CS-T15Lo improved fiber elongation and yellow index. Some leaf mineral and fiber quality traits exhibited positive correlations. Overall results suggest these chromosome substitutions broaden the genetic base and allow for potential enhancement of leaf mineral nutrition and fiber quality of Upland cotton.