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Leguminous cover crop systems have been envisaged as a critical component of sustainable agriculture because of their potential to increase soil productivity by cycling C and N in agricultural systems. Our objectives were to: (i) determine the effects of including summer cover crops and N rates in the cropping system on the growth and yield of the succeeding grain sorghum [Sorghum bicolor (L.) Moench] crop, (ii) calculate the N fertilizer replacement value (NFRV) and evaluate economic returns, and (iii) determine the most cost-effective cropping system. Field experiments were conducted for two seasons in Kansas. Leguminous summer cover crops and double-cropped soybean [Glycine max (L.) Merr.] residues improved soil N availability; N was subsequently used by the succeeding crop. Across years and cropping systems, the mean increases in grain yield as a result of including cowpea [Vigna unguiculata (L.) Walp.], pigeonpea [Cajanus cajan (L.) Millsp.], sunn hemp (Crotalaria juncea L.), double-cropped soybean, and double-cropped grain sorghum in the rotation compared with a fallow system with 0 kg N ha–1 were 56, 62, 43, 32, and 3%, respectively, and NFRVs across the years were 53, 64, 36, 27, and –3 kg N ha–1, respectively. Across years, grain sorghum in a double-cropped soybean system and a fallow system with 90 kg N ha–1 gave profitable economic net returns. We conclude that including leguminous cover crops in a cropping system has the potential to reduce N requirements and improve the N availability and grain yield of the succeeding grain sorghum crop.

Grain sorghum [Sorghum bicolor (L.) Moench] is an important crop in semiarid regions of the world because of its drought tolerance. Nitrogen is one of the most limiting nutrients in crop production due to low availability and loss. We hypothesize that there are differences in physiological and yield traits among grain sorghum genotypes in response to N. The objectives of this study were to determine the responses of sorghum genotypes (hybrids and inbred lines) to N fertilizer and the relationship between their physiological and yield traits. Field experiments were conducted at two locations in Kansas for two seasons (2010 and 2011). Genotype × N regimes and year × genotype interactions were significant for leaf chlorophyll, aboveground biomass, grain yield, and seed number. Overall, the hybrids were superior to inbred lines for grain yield and total aboveground biomass, but grain yields of inbred lines TX2783 and TX7000 were comparable to hybrids. Maximum total aboveground biomass, leaf chlorophyll index, and grain yield were obtained at 90 kg N ha –1 . Across years, application of 45 and 90 kg N ha –1 resulted in an increase in yield of 13 and 48% over 0 kg N ha –1 , respectively. No strong relationship was detected between genotypes and leaf chlorophyll index or chlorophyll a fluorescence and grain yield, but there was a strong relationship between seed number and total aboveground biomass and grain yield. Leaf chlorophyll index and chlorophyll a fluorescence did not provide physiological basis for differences in N response among the genotypes for grain yield.

Leaf area index (LAI) is a widely used physiological parameter to quantify the vegetative canopy structure of crops. Over the years, several models to estimate LAI have been developed with various degrees of complexity and inherent shortcomings. The LAI simulation models proposed so far for sorghum [Sorghum bicolor (L.) Moench] either lack details of the leaf area dynamics of expanding leaves or demand exhaustive measurements. The objective of this study was to develop a simple quantitative model to predict the LAI of sorghum by introducing a new method for simulation of the leaf area of expanding leaves. The proposed model relates LAI to thermal time. It calculates LAI from an algorithm considering the total number of mature leaves, the area of mature leaves, the area of expanding leaves, and plant density. The performance of the model was tested using LAI data collected using a nondestructive method under field conditions. The slope of the regression of modeled LAI on observed LAI varied for photoperiod-sensitive and -insensitive genotypes in 2010. The coefficients of determination ( R 2 ) between modeled and observed LAI were 0.96 in 2009 and 0.99 (photoperiod insensitive) and 0.95 (photoperiod sensitive) in 2010. The inclusion of expanding leaves in the model improved its accuracy. The model provides an accurate estimate of LAI at any given day of the vegetative growing season based only on thermal time and making use of default coefficients demonstrated in this research.

Increasing water and radiation use efficiencies (WUE and RUE, respectively) are critical to enhance crop production. Exploring genetic variability in WUE and RUE is necessary to improve these traits. The objectives of this research were to evaluate eight sorghum [Sorghum bicolor (L.) Moench] genotypes for biomass production, WUE, and RUE and to test whether the differences in WUE among sorghum genotypes were associated with increased biomass production or decreased water use under field conditions. The WUE was estimated as the slope of the regression of aboveground biomass on cumulative water use for specified sampling intervals. The RUE was estimated as the slope of the regression of aboveground biomass on cumulative intercepted photosynthetically active radiation (IPAR). Sorghum genotypes showed significant differences in biomass production, WUE, and RUE. The WUE varied from 3.39 ± 0.80 to 5.42 ± 0.80 g kg⁻¹ in 2009 and from 4.04 ± 0.58 to 7.63 ± 0.58 g kg⁻¹ in 2010. Similarly, RUE varied from 2.13 ± 0.33 to 3.53 ± 0.31 g MJ⁻¹ IPAR in 2009 and from 2.08 ± 0.35 to 3.83 ± 0.33 g MJ⁻¹ IPAR in 2010. Among the eight sorghum genotypes tested in this study, IS 27111 and IS 27150 had the largest biomass production, WUE, and RUE. The WUE was more strongly correlated to biomass production than to water use. This result implies that it is possible to improve WUE without compromising biomass production. The sorghum genotypes evaluated for biomass production, WUE, and RUE in this study offer useful plant materials for identifying the mechanisms causing differences in these traits.