Sulfur fertilization plays a crucial role in wheat (Triticum aestivum L.) production, influencing both protein concentration and grain yield. Wheat, being one of the most important food crops globally, requires efficient management of essential nutrients, including sulfur and nitrogen, to achieve optimal production. This study aimed to quantify the effect of sulfur fertilization on wheat protein concentration and grain yield and the relationship with nitrogen through two complementary methods: a comprehensive meta-analysis and a controlled greenhouse experiment. The meta-analysis, encompassing 55 studies from 20 countries with 545 comparisons, quantified the overall response of wheat to sulfur fertilization in diverse field environments, examining the effects based on soil texture and organic matter content. The greenhouse study investigated the effects of varying sulfur application rates and sources on protein concentration and grain yield and analyzed the relationship between sulfur and nitrogen concentrations in the grain. The meta-analysis showed overall positive effects of sulfur application on both protein concentration (2.1%) and grain yield (4.2%), with the magnitude of these effects varying based on soil texture and organic matter content. Sandy soils and soils with low organic matter content exhibited the most pronounced responses to sulfur fertilization. The greenhouse experiment revealed responses of both protein concentration and grain yield to increasing sulfur application rates, indicating an optimal rate beyond which additional sulfur may not provide further benefits. A strong positive correlation between sulfur and nitrogen concentrations in the grain highlighted their interdependence in wheat nutrition. These findings emphasize the importance of considering soil properties and the sulfur–nitrogen interaction when developing site-specific sulfur fertilization strategies for wheat. The results provide valuable insights for optimizing grain yield and protein concentration, contributing to more sustainable and efficient wheat production systems.

Phosphorus (P) management in corn ( Zea mays L.) traditionally relies on soil testing, but other diagnostic tools, such as tissue analysis, can be used to assess nutrient management. This study aimed to evaluate plant tissue analysis, Normalized Difference Vegetation Index (NDVI), and Soil Plant Analysis Development (SPAD) readings as diagnostic tools and identify the critical P tissue concentration (CPTC) in two different growth stages of corn in relation to response to P fertilizer. Field experiments were conducted at 30 site‐years in Kansas. Fertilizer treatments included four different phosphorus rates and a control. Whole plant tissue samples and NDVI were collected at the V6 growth stage, and ear leaf samples and SPAD were collected at the R1 growth stage. The CPTC was determined using linear plateau and quadratic plateau models, and model averaging was performed for final estimation. Results indicated that the average CPTC in the whole plant at V6 and the ear leaf at R1 were 5.5 and 3.3 g kg ⁻¹ , respectively. Regression analysis revealed that as the P tissue concentration increases, the optimum fertilizer recommendation rate decreases with R ² of 0.26 and 0.25 for V6 and R1, respectively. Correlation analysis highlighted that NDVI and SPAD correlation displayed some potential for assessing P in corn. Correlation and regression analysis showed a moderate correlation between plant P tissue concentration at V6 and leaf P tissue concentration at R1 ( r = 0.50 and R ² = 0.25). This study contributes valuable insights for phosphorus management in corn, providing CPTC and fertilizer calibration and highlighting diagnostic tools’ shortcomings and potential.

Corn ( Zea mays L .) response to sulfur (S) fertilizations remains difficult to assess due to the dynamic nature of S availability. This study evaluated corn response and diagnostic tools across 30 field sites in Kansas (Experiment 1; with and without S) and in complementary rate trials at two sites (Experiment 2; multiple S rates). Measurements included normalized difference vegetation index (NDVI), soil plant analysis development (SPAD), tissue S concentrations at various growth stages, grain S concentration, total S uptake, and yield. Sulfur fertilization increased tissue S concentration and uptake across stages, but yield responses were generally low. SPAD at R1 and tissue S concentrations outperformed NDVI and soil sulfate, although the diagnostic value was inconsistent. Grain yield and total S uptake showed a strong relationship, requiring 1.5 kg S uptake Mg ⁻¹ grain. In the rate study, yield followed a plateau response, and the agronomic optimum S rate was estimated at 21 kg ha ⁻¹ using model averaging of linear and quadratic plateau functions, while the 95% confidence interval (12–42 kg ha ⁻¹ ) was obtained using bootstrap aggregation. Efficiency metrics varied widely: agronomic and recovery efficiencies were low in nonresponsive sites but improved at lower rates in responsive environments, while internal efficiency averaged 619 kg grain kg ⁻¹ S uptake. Hierarchical Bayesian dilution models yielded a critical S concentration curve (S _C = 2.05 × biomass ^−0.2 ) and a nitrogen‐to‐sulfur (N:S) ratio curve (N:S _R = 15.59 × biomass ^−0.08 ), providing a physiological framework for in‐season diagnosis. Overall, moderate, well‐targeted S rates, combined with tissue diagnostics and dilution curves, can guide strategies to enhance S efficiency and management in corn.