A field study was conducted to investigate the effects of selected climate-smart agriculture practices on soil bulk density (ρ), porosity (β), hydraulic conductivity (K_sat), and nutrient dynamics in southeast Texas. Treatment combinations of two types of organic manure (chicken and dairy) with three rates (0, 224, and 448 kg N ha⁻¹) and two levels of biochar (2500 and 5000 kg ha⁻¹) were used in a factorial randomized block design. Bulk density and porosity measurements were conducted on undisturbed soil core samples collected from the topsoil (0–10 cm) of a field cultivated with sweet corn. K_sat was calculated from the steady-state infiltration measured using the Tension Infiltrometer (TI). The ANOVA results indicated that the manure application rates, and biochar levels significantly affected the soil properties. Compared to the control, β increased by 15% and 29% for the recommended and double recommended manure rates. Similarly, hydraulic conductivity increased by 25% in the double-recommended rate plots compared to the control. Also, we applied the concept of non-parametric elasticity to understand the sensitivity of soil physical and chemical properties to K_sat. ρ and β are critical physical properties that are highly sensitive to K_sat. Among soil nutrients, Boron showed the highest sensitivity to K_sat. Hydraulic conductivity can be enhanced by employing selected climate-smart practices and improving water management. Future directions for this study focus on scaling these findings to diverse cropping systems and soil types while integrating long-term assessments to evaluate the cumulative effects of climate-smart practices on soil health, crop productivity, and ecosystem sustainability.

The knowledge about nutrient dynamics in the soil is pivotal for sustainable agriculture. A comprehensive research trial can retort unanswered questions. Dynamics of nutrients sourced from organic amendment types (chicken manure, dairy manure, and Milorganite^TM) applied at different rates (0, 168, 336, 672 kg total N/ha) were monitored within and below the rootzone of collard greens cultivated on a sandy loam soil in Prairie View, TX, USA. Macro- and micronutrients (e.g., TN: total nitrogen, P: phosphorous, K: potassium, Na: sodium, Ca: calcium, Mg: magnesium, B: boron, Cu: copper, Fe: iron, and Zn: zinc) were analyzed from soil solution samples collected during six sampling periods from within and below the rootzone. As hypothesized, the organic amendment types and rates significantly (p < 0.05 and/or 0.01) affected nutrient dynamics within and below the crop rootzone. Chicken manure released significantly more TN, P, K, Na, Ca, Mg, B, Cu, and Fe than the other two amendments. The application of chicken manure and Milorganite^TM resulted in higher below-the-rootzone leachate concentration of TN, Na, Mg, and Ca than in the leachates of dairy manure. Dairy manure treatments had the lowest concentrations of TN, Ca, and Mg; whereas, Milorganite^TM had the lowest concentrations of P, K, Na, B, and Cu in the collected leachates. The higher level of P (i.e., 4% in Milorganite^TM as compared to 2 and 0.5% in chicken and dairy manures, respectively, might have reduced the formation of Vesicular-Arbuscular (VA) mycorrhizae—a fungus with the ability to dissolve the soil P, resulting in slow release of P from Milorganite^TM treatment than from the other two treatments. Patterns of nutrient dynamics varied with rain and irrigation events under the effects of the soil water and time lapse of the amendment applications’ rates and types. All the macronutrients were present within the rootzone and leached below the rootzone, except Na. The dynamic of nutrients was element-specific and was influenced by the amendments’ type and application rate.

Sorghum [Sorghum bicolor (L.) Moench] is a vital cereal crop in semi-arid regions, but its productivity is often limited by water scarcity and inefficient nitrogen (N) management. While previous studies have explored the individual effects of irrigation and N application, limited research has examined their combined influence on sorghum growth, phenology, and yield. This study aimed to assess the impacts of four irrigation levels (0, 75, 100, and 125% of irrigation as I₀, I₇₅, I₁₀₀, and I₁₂₅) and four N application rates (0, 90, 180, and 360 kg N ha⁻¹ as N₀, N₉₀, N₁₈₀, and N₃₆₀) on sorghum performance to identify optimal water and nutrient management strategies. A field experiment was conducted over two growing seasons, measuring plant height, number of leaves, panicle length, flowering percentage, visual maturity rating, biomass, and grain yield using a split-plot design, with irrigation as the main factor and N rates as subplots with three replications. Key findings revealed that irrigation and N application significantly influenced plant height, number of leaves, panicle length, biomass, and grain yield. The highest plant height (58.06 cm), number of leaves (10.25), and panicle length (26.60 cm) were observed under I₁₂₅. Compared to the I₀ treatment, the increase in visual maturity rating in I₇₅ and I₁₀₀ was 64.91% and 249.70%, respectively. The highest biomass (3.25 t/ha) was observed for treatment I₁₂₅, while the highest grain yield (2.40 t/ha) was for I₁₀₀. Compared to N₀, treatments N₉₀, N₁₈₀, and N₃₆₀ increased grain yield by 64.8, 66.4, and 81.6%, respectively. The Pearson correlation analysis revealed significant positive relationships among key crop growth, phenology, and yield traits. The maturity rating correlated highest with flowering percentage (0.76). The response to N application was more pronounced under well-watered conditions, with the steepest grain yield increase observed under N₃₆₀. In water-limited conditions, higher N rates did not improve yield. Based on these results, applying irrigation at 100% of the crop water requirement and at least 180 kg N ha⁻¹ is recommended to enhance sorghum resilience, resource-use efficiency, and sustainable production, particularly in water-scarce regions.

Machine learning (ML) models are widely used to analyze the spatiotemporal impacts of agricultural practices on environmental sustainability, including the contribution to global greenhouse gas (GHG) emissions. Management practices, such as organic amendment applications, are critical pillars of Climate-smart agriculture (CSA) strategies that mitigate GHG emissions while maintaining adequate crop yields. This study investigated the critical threshold of soil moisture level associated with soil CO₂ emissions from organically amended plots using the classification and regression tree (CART) algorithm. Also, the study predicted the short-term soil CO₂ emissions from organically amended systems using soil moisture and weather variables (i.e., air temperature, relative humidity, and solar radiation) using multilinear regression (MLR) and generalized additive models (GAMs). The different organic amendments considered in this study are biochar (2268 and 4536 kg ha⁻¹) and chicken and dairy manure (0, 224, and 448 kg N/ha) under a sweet corn crop in the greater Houston area, Texas. The results of the CART analysis indicated a direct link between soil moisture level and the magnitude of CO₂ flux emission from the amended plots. A threshold of 0.103 m³m⁻³ was calculated for treatment amended by biochar level I (2268 kg ha⁻¹) and chicken manure at the N recommended rate (CXBX), indicating that if the soil moisture is less than the 0.103 m³m⁻³ threshold, then the median soil CO₂ emission is 142 kg ha⁻¹ d⁻¹. Furthermore, applying biochar at a rate of 4536 kg ha⁻¹ reduced the soil CO₂ emissions by 14.5% compared to the control plots. Additionally, the results demonstrate that GAMs outperformed MLR, exhibiting the highest performance under the combined effect of chicken and biochar. We conclude that quantifying soil moisture thresholds will provide valuable information for the sustainable mitigation of soil CO₂ emissions.