Explore the vast range of titles available.

Seed priming is a state-of-the-art, low-cost, and environment-friendly strategy to improve seed germination, seed vigor, abiotic and biotic stress tolerance, and the yield of field and horticultural crops. Seed priming involves imbibing the seeds in a priming solution under a desired set of environmental conditions for a period followed by drying before the radicle protrusion. Several seed priming approaches including hydropriming, osmopriming, bio-priming, hormonal priming, nutrient priming, nanoparticle priming, and electropriming can be effectively employed under different environmental conditions to improve crop growth and stress resilience. Seed priming is known to trigger enzymatic, hormonal, physiological, transcriptomic, metabolomic, and proteomic regulations in seed embryos during seed germination and plant growth, which leads to faster and synchronized seed germination and higher abiotic and biotic stress tolerance in crop plants. Furthermore, seed priming can induce cross-tolerance between abiotic and biotic stressors and induce stress memory for higher resilience of the next generation to environmental stresses. The present review paper discusses the applications of seed priming in biotic and abiotic stress tolerance and the underlying abiotic and biotic stress tolerance physiological, biochemical, and molecular mechanisms of seed priming. Furthermore, we discuss the current challenges/bottlenecks in the widespread application of seed priming in crop production.

Low nutritive value of perennial grasses during mid-late summer limits stocker cattle production in the Southern Great Plains (SGP). Our objectives were to explore annual crop species that might fit as a summer forage, and quantify their forage potentials under the highly variable agro-climatic conditions of the SGP. A field experiment compared the seasonal changes in above ground dry matter (ADM), leaf-to-stem ratio, and chemical composition of tepary bean (Phaseolus acutifolius) and guar (Cyamopsis tetragonoloba) to soybean (Glycine max). Tepary bean outperformed soybean and guar by producing greater ADM (6.5 Mg ha-1) with a leaf-to-stem ratio of 3.1 at 65 days after planting (DAP), and its chemical composition also remained superior and consistent throughout the growing season. Secondly, ten mothbean (Vigna aconitifolia) lines were evaluated for their forage, grain or green manure potentials. Mothbean lines generated a ADM range of 7.3-18.1 Mg ha-1 with 10.8-14.6% crude protein (CP), 32.0-41.7% neutral detergent fiber (NDF), 20.7-29.6% acid detergent fiber (ADF), and 73-84% in vitro true digestibility (IVTD) at 100 DAP. Third, eleven finger millet (Eleusine coracana) accessions were assessed for their adaptability and forage characterization under the SGP conditions. Finger millet accessions resulted in ADM ranging from 5.0-12.3 Mg ha-1, which contained 10.5-15.6% CP, 59.8-73.4% NDF, 26.8-38.2% ADF, and 59.7-73.0% IVTD at 165 DAP. Finally, a greenhouse study was conducted to compare vegetative growth and physiological responses of mothbean, tepary and guar under four different water regimes. Tepary bean showed the lowest stomatal conductance (gs) and photosynthetic rate (A), but it maintained the highest instantaneous water use efficiency (WUEi) among species under water-stressed treatments. At final harvest (77 DAP), the ADM generated by tepary bean was 38-60% and 41-56% higher than guar and mothbean, respectively, across four water deficits. Tepary bean was identified as the most drought-tolerant and reliable option for SGP among the tested species, considering its higher biomass production, WUEi, leaf-to-stem ratio, and consistent nutritive value when grown as a summer forage. Future research should focus on defining management practices for growing these novel crops in extensive production settings for grazing or hay.

Warm-season legumes have been receiving increased attention as forage resources in the southern United States and other countries. However, the near infrared spectroscopy (NIRS) technique has not been widely explored for predicting the forage quality of many of these legumes. The objective of this research was to assess the performance of NIRS in predicting the forage quality parameters of five warm-season legumes—guar (Cyamopsis tetragonoloba), tepary bean (Phaseolus acutifolius), pigeon pea (Cajanus cajan), soybean (Glycine max), and mothbean (Vigna aconitifolia)—using three machine learning techniques: partial least square (PLS), support vector machine (SVM), and Gaussian processes (GP). Additionally, the efficacy of global models in predicting forage quality was investigated. A set of 70 forage samples was used to develop species-based models for concentrations of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), and in vitro true digestibility (IVTD) of guar and tepary bean forages, and CP and IVTD in pigeon pea and soybean. All species-based models were tested through 10-fold cross-validations, followed by external validations using 20 samples of each species. The global models for CP and IVTD of warm-season legumes were developed using a set of 150 random samples, including 30 samples for each of the five species. The global models were tested through 10-fold cross-validation, and external validation using five individual sets of 20 samples each for different legume species. Among techniques, PLS consistently performed best at calibrating (R2c = 0.94–0.98) all forage quality parameters in both species-based and global models. The SVM provided the most accurate predictions for guar and soybean crops, and global models, and both SVM and PLS performed better for tepary bean and pigeon pea forages. The global modeling approach that developed a single model for all five crops yielded sufficient accuracy (R2cv/R2v = 0.92–0.99) in predicting CP of the different legumes. However, the accuracy of predictions of in vitro true digestibility (IVTD) for the different legumes was variable (R2cv/R2v = 0.42–0.98). Machine learning algorithms like SVM could help develop robust NIRS-based models for predicting forage quality with a relatively small number of samples, and thus needs further attention in different NIRS based applications.

Novel drought-tolerant grain legumes like mothbean ( Vigna acontifolia ), tepary bean ( Phaseolus acutifolius ), and guar ( Cyamopsis tetragonoloba ) may also serve as summer forages, and add resilience to agricultural systems in the Southern Great Plains (SGP). However, limited information on the comparative response of these species to different water regimes prevents identification of the most reliable option. This study was conducted to compare mothbean, tepary bean and guar for their vegetative growth and physiological responses to four different water regimes: 100% (control), and 75%, 50% and 25% of control, applied from 27 to 77 days after planting (DAP). Tepary bean showed the lowest stomatal conductance ( g s ) and photosynthetic rate ( A ), but also maintained the highest instantaneous water use efficiency ( WUE i ) among species at 0.06 and 0.042 m 3  m −3 soil moisture levels. Despite maintaining higher A , rates of vegetative growth by guar and mothbean were lower than tepary bean due to their limited leaf sink activity. At final harvest (77 DAP), biomass yield of tepary bean was 38–60% and 41–56% greater than guar and mothbean, respectively, across water deficits. Tepary bean was the most drought-tolerant legume under greenhouse conditions, and hence future research should focus on evaluating this species in extensive production settings.

Low nutritive value of perennial warm‐season grasses often causes limitation to stocker cattle production in the U.S. southern Great Plains (SGP). Exploration of novel legumes capable of generating nutritious summer forage is required to fill forage deficit periods. This 2‐yr field experiment compared the seasonal changes in forage biomass, leaf/stem ratio, and chemical composition of three varieties each of tepary bean [Phaseolus acutifolius (A.) Gray] and guar [Cyamopsis tetragonoloba (L.) Taub.] to soybean [Glycine max (L.) Merr.]. Tepary bean cultivar Black outperformed soybean and guar varieties by producing 18–48% greater aboveground dry matter (ADM) amounts (6537 kg ha−1) with a leaf/stem ratio of 3.1 at 65 days after planting (DAP). The ADM and leaf nutritive value of soybean were not surpassed by the other five tested legumes, but had the least digestible stems with an in vitro true digestibility (IVTD) of 529–581 g  kg−1 in both years. Guar varieties maintained a lower leaf/stem ratio (1.3–1.5 kg kg−1) throughout the growing season, which could limit its value for grazing compared to other legumes. We concluded tepary bean could serve as an alternate forage option to soybean for producers in the SGP. Tepary bean possessed the greatest capabilities for producing adequate biomass yields with superior and consistent nutritive value when grown as a summer forage. Future research should focus on defining management practices for growing tepary bean in extensive production settings for grazing or hay.

Ambient temperatures are major factors regulating the growth rates, yields, and geographical distribution of crop species. The cultivation of sesame (Sesamum indicum L.) is expanding with the rising demand in regions where it is not traditionally grown, and sub-optimal yields due to extremely low or high temperatures could occur. Currently literature lacks information on the temperature responses of sesame growth. An experiment was conducted to quantify the effects of different temperatures on vegetative growth and reproductive development of sesame, and to estimate its cardinal temperature limits (Topt; Tmin; Tmax). Plants were subjected to six different day/night temperature treatments of 40/32, 36/28, 32/24, 28/20, and 20/12 °C using walk-in growth chambers. Vegetative growth of sesame was sensitive to low temperatures (< 15 °C), but tolerant of high temperatures. The cardinal temperature limits of 15.7 °C (Tmin), 27.3 °C (Topt), and 44.6 °C (Tmax) were observed for rate of biomass accumulation. Sesame reached the flowering stage under moderate to high temperature conditions; however, reproductive yields progressively declined above 25 °C, and no seed yields were obtained beyond 33 °C. The estimated temperature limits could be employed to develop crop models for simulating management and adaptation strategies of sesame under current and future climate scenarios, and adaptation to regions where the crop is not currently grown. Future research should focus on understanding factors controlling the temperature tolerance of reproductive development in sesame, to provide a broader geographical adaptation.

Challenges to sustainable agriculture are increasing with forecasts for greater climate variability, including rising temperatures, extreme precipitation events, and prolonged droughts. One important factor that contributes to the increasing climate variability is greenhouse gas emissions, including from agro-ecosystems. The US Environment Protection Agency indicates soil management and enteric fermentation from livestock contribute ~ 80% of total greenhouse gas from agriculture sector. Management practices conducive to greenhouse gas emissions, and possible mitigation strategies for the agricultural systems of Southern Great Plains, an integral part of the US beef industry, have not been thoroughly defined. The objective of this paper is to review and synthesize the literature regarding management practices conducive to emissions [carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4)] from croplands and grazing lands of Southern Great Plains, and potential strategies that may aid in greenhouse gas mitigation in the region. The results from different published studies evaluating such strategies were analyzed to determine whether these practices have potential in mitigating greenhouse gas emissions from agronomic and grazing lands. Based on the analysis, it can be recommended that increasing the amount of cropland managed by conservation tillage, fertilizer management, crop rotation systems, grazing management, and fertilizer amendments can be potential management strategies for greenhouse gas mitigation. As agro-ecosystems are very complex and reducing emissions using strategies in one sector may stimulate higher emissions in other sectors, these strategies require testing at the systems-level before they can be implemented to advise applied policies for the Southern Great Plains region.

The original version of this article unfortunately contained a mistake.