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Using existing protocols, RNA extracted from seeds rich in starch often results in poor quality RNA, making it inappropriate for downstream applications. Though some methods are proposed for extracting RNA from plant tissue rich in starch and other polysaccharides, they invariably yield less and poor quality RNA. In order to obtain high yield and quality RNA from seeds and other plant tissues including roots a modified SDS-LiCl method was compared with existing methods, including TRIZOL kit (Invitrogen), Plant RNeasy mini kit (Qiagen), Furtado (2014) method, and CTAB-LiCl method. Modifications in the extraction buffer and solutions used for RNA precipitation resulted in a robust method for extracting RNA in seeds and roots, where extracting quality RNA is challenging. The modified SDS-LiCl method revealed intense RNA bands through gel electrophoresis and a nanodrop spectrophotometer detected ratios of ≥ 2 and 1.8 for A260/A230 and A260/A280, respectively. The absence of starch co-precipitation during RNA extraction resulted in enhanced yield and quality of RNA with RIN values of 7–9, quantified using a bioanalyzer. The high-quality RNA obtained was demonstrated to be suitable for downstream applications, such as cDNA synthesis, gene amplification, and RT-qPCR. The method was also effective in extracting RNA from seeds of other cereals including field-grown sorghum and corn. The modified SDS-LiCl method is a robust and highly reproducible RNA extraction method for plant tissues rich in starch and other secondary metabolites. The modified SDS-LiCl method successfully extracted high yield and quality RNA from mature, developing, and germinated seeds, leaves, and roots exposed to different abiotic stresses.

Zn deficiency is a widespread problem in rice (Oryza sativa L.) grown under flooded conditions, limiting growth and grain Zn accumulation. Genotypes with Zn deficiency tolerance or high grain Zn have been identified in breeding programmes, but little is known about the physiological mechanisms conferring these traits. A protocol was developed for growing rice to maturity in agar nutrient solution (ANS), with optimum Zn-sufficient growth achieved at 1.5 μM ZnSO4.7H2O. The redox potential in ANS showed a decrease from +350 mV to −200 mV, mimicking the reduced conditions of flooded paddy soils. In subsequent experiments, rice genotypes contrasting for Zn deficiency tolerance and grain Zn were grown in ANS with sufficient and deficient Zn to assess differences in root uptake of Zn, root-to-shoot Zn translocation, and in the predominant sources of Zn accumulation in the grain. Zn efficiency of a genotype was highly influenced by root-to-shoot translocation of Zn and total Zn uptake. Translocation of Zn from root to shoot was more limiting at later growth stages than at the vegetative stage. Under Zn-sufficient conditions, continued root uptake during the grain-filling stage was the predominant source of grain Zn loading in rice, whereas, under Zn-deficient conditions, some genotypes demonstrated remobilization of Zn from shoot and root to grain in addition to root uptake. Understanding the mechanisms of grain Zn loading in rice is crucial in selecting high grain Zn donors for target-specific breeding and also to establish fertilizer and water management strategies for achieving high grain Zn.

Background Rice is a major staple food crop for more than half the world’s population. As the global population is expected to reach 9.7 billion by 2050, increasing the production of high-quality rice is needed to meet the anticipated increased demand. However, global environmental changes, especially increasing temperatures, can affect grain yield and quality. Heat stress is one of the major causes of an increased proportion of chalkiness in rice, which compromises quality and reduces the market value. Researchers have identified 140 quantitative trait loci linked to chalkiness mapped across 12 chromosomes of the rice genome. However, the available genetic information acquired by employing advances in genetics has not been adequately exploited due to a lack of a reliable, rapid and high-throughput phenotyping tool to capture chalkiness. To derive extensive benefit from the genetic progress achieved, tools that facilitate high-throughput phenotyping of rice chalkiness are needed. Results We use a fully automated approach based on convolutional neural networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM) to detect chalkiness in rice grain images. Specifically, we train a CNN model to distinguish between chalky and non-chalky grains and subsequently use Grad-CAM to identify the area of a grain that is indicative of the chalky class. The area identified by the Grad-CAM approach takes the form of a smooth heatmap that can be used to quantify the degree of chalkiness. Experimental results on both polished and unpolished rice grains using standard instance classification and segmentation metrics have shown that Grad-CAM can accurately identify chalky grains and detect the chalkiness area. Conclusions We have successfully demonstrated the application of a Grad-CAM based tool to accurately capture high night temperature induced chalkiness in rice. The models trained will be made publicly available. They are easy-to-use, scalable and can be readily incorporated into ongoing rice breeding programs, without rice researchers requiring computer science or machine learning expertise.

Heat stress during gametogenesis leads to spikelet sterility. To ascertain the role of female reproductive organ (pistil), two rice genotypes N22 and IR64 with contrasting heat stress responses were exposed to control (30 °C) and heat stress (38 °C and 40 °C) during megasporogenesis. Anatomical observations of ovule revealed greater disappearance of megaspore mother cell and nuclei at early stages, and during later stages mature embryo sac without female germ unit, improper positioning of nuclei, and shrunken embryo sac was observed in the sensitive IR64. Under heat stress, a decrease in sugar and starch, increase in H2O2 and malondialdehyde with lower antioxidant enzyme activities were recorded in pistils of both N22 and IR64. Lower accumulation of TCA cycle metabolites and amino acids were noticed in IR64 pistils under heat stress at gametogenesis, whereas N22 exhibited favorable metabolite profiles. At heading, however, N22 pistils had higher carbohydrate accumulation and better ROS homeostasis, suggesting higher recovery after heat stress exposure. In summary, the results indicate that heat stress during megasporogenesis leads to irreversible anatomical and physiological changes in pistil and alters metabolic signatures leading to increased spikelet sterility in rice. Mechanisms identified for enhanced heat tolerance in pistil can help in developing rice varieties that are better adapted to future hotter climate.

Increasing temperatures can severely affect wheat (Triticum aestivum L.) production, particularly when it coincides with the grain‐filling period. Heat stress induces rapid senescence resulting in early maturity and shortened grain‐filling period. In this study, the applicability of in vivo chlorophyll fluorescence (Chl‐F) and chlorophyll index to track rate of senescence in flag leaves and spikes exposed to heat stress were investigated. Seven winter wheat varieties were exposed to post‐flowering heat stress using growth chambers [35/15 °C (heat stress) and 25/15 °C (control) day/night] and unique field‐based heat tents (imposed +6 °C higher than ambient). Effective quantum yield of photosystem II (PSII) (QY) was recorded temporally in flag leaves and spikes, and compared with in vitro chlorophyll‐a (Chl‐a) concentration and non‐invasive estimation of chlorophyll and flavonoids index. Time point indicating the start of senescence (change‐point, CP) for QY was advanced by 0–8 and 0–6 d in flag leaves and spikes, respectively, under heat stress. In the chamber experiment, sustained heat stress induced accelerated decline of QY, particularly in wheat cultivars Larry and WB4458. Stronger positive relationship between days to senescence in spikes and thousand kernel weight indicated an extended period of assimilate supply from sink compared to the source tissue, during grain filling. Capturing heat stress‐induced changes in photosynthetic pigments and QY at high temporal frequency presents an effective phenotyping approach for testing genetic diversity in large‐scale field experiments involving different crops.

Sorghum is often exposed to suboptimal low temperature stress under field conditions, particularly at the seedling establishment stage. Enhancing chilling tolerance will facilitate earlier planting and so minimize the negative impacts of other stresses experienced at later growth stages. Genome-wide association mapping was performed on a sorghum association panel grown under control (30/20 °C; day/night) and chilling (20/10 °C) conditions. Genomic regions on chromosome 7, controlling the emergence index and seedling (root and shoot) vigor, were associated with increased chilling tolerance but they did not co-localize with undesirable tannin content quantitative trait loci (QTLs). Shoot and root samples from highly contrasting haplotype pairs expressing differential responses to chilling stress were used to identify candidate genes. Three candidate genes (an alpha/beta hydrolase domain protein, a DnaJ/Hsp40 motif-containing protein, and a YTH domain-containing RNA-binding protein) were expressed at significantly higher levels under chilling stress in the tolerant haplotype compared with the sensitive haplotype and BTx623. Moreover, two CBF/DREB1A transcription factors on chromosome 2 showed a divergent response to chilling in the contrasting haplotypes. These studies identify haplotype differences on chromosome 7 that modulate chilling tolerance by either regulating CBF or feeding back into this signaling pathway. We have identified new candidate genes that will be useful markers in ongoing efforts to develop tannin-free chilling-tolerant sorghum hybrids.

The global average daily minimum temperatures are increasing at a quicker pace than the average daily maximum temperatures, which are predicted to increase in severity impacting global food production. This study focuses on elucidating the physiological and transcriptional response to high night‐time temperature (HNT) stress in 12 US commercial maize (Zea mays) hybrids using unique field‐based infrastructure. Our experimental objectives were to (i) impose an accurate and uniformly distributed post‐flowering HNT stress of +4.0°C until physiological maturity, (ii) quantify the impact of HNT stress on physiological and yield‐related traits, (iii) establish the impact on end‐use quality of maize kernels formed under HNT stress, and (iv) analyze the differential expression of genes involved in grain starch metabolism. Accurate and uniformly distributed HNT stress of 3.8°C higher than the ambient night‐time temperature throughout the grain‐filling period reduced yield (−14%), kernel weight (−8%), and significantly reduced kernel nutrient content, specifically magnesium in the susceptible hybrids. HNT significantly increased the expression of key genes involved in starch metabolism in the tolerant hybrid. Although HNT stress had a negative impact on yield and quality in field grown maize, two hybrids had physiological and transcriptional regulation that favored higher level of resilience which lays the platform for developing climate smart maize hybrids. Core Ideas High night‐time temperature (HNT) stress significantly reduced yield (−14%) and kernel weight (−8%). HNT had a negative impact on grain quality properties such as starch content (−10%). A differential transcriptional regulation of starch metabolism was observed in hybrids under HNT stress. Agronomic and genetic mechanisms for HNT tolerance exist among current commercial hybrids.

A diverse panel of 320 winter wheat (Triticum aestivum L.) genotypes was evaluated for yield‐related parameters under control and high night‐time temperature (HNT) stress using custom‐designed, movable field‐based heat tents over 2 years. Genome‐wide association mapping identified several significant single nucleotide polymorphisms (SNPs) across environments, with SNPs under HNT conditions, based on absolute trait values and stress tolerance indices, grouped into 19 HNT quantitative trait loci (QTLs). Additionally, significant SNPs identified under both (control and HNT) conditions contributed to seven condition‐independent QTLs. Thirteen haplotype blocks, derived from some of these QTLs, significantly influenced traits, with nine specific to HNT stress and four shared across conditions. Candidate gene mining identified 17 high‐confidence genes involved in the HNT response, including those encoding ATP‐dependent RNA helicase, GCN5‐related N‐acetyltransferase, oxidoreductase FAD/NAD(P)‐binding, RNA recognition motif, and sugar/inositol transporter. Gene‐based haplotype analysis identified four haplotypes with significant differences under HNT conditions and one block with differences under both conditions. For instance, Hap1TraesCS1A02G305700 exhibited higher biomass and spike number under HNT, Hap1TraesCS2B02G599800 showed higher biomass under HNT, and Hap2TraesCS4B02G264300 demonstrated higher biomass under both conditions. This study elucidates the genetic control of traits contributing to HNT stress responses in wheat, supporting the selection of lines with favorable alleles for crosses and enabling marker‐assisted and genomic selections for HNT stress tolerance. The identified candidate genes and haplotypes provide valuable targets for functional validation, breeding strategies, and gene‐editing approaches to enhance HNT resilience in wheat. Core Ideas A panel of 320 winter wheat genotypes was assessed under control and high night‐time temperature (HNT) stress. Genome‐wide association mapping revealed significant single nucleotide polymorphisms (SNPs) linked to HNT response, grouped into 19 HNT‐specific quantitative trait loci (QTLs). Thirteen haplotype blocks significantly influenced traits, with nine specific to HNT and four shared across conditions. Candidate gene mining identified 17 high‐confidence genes related to HNT stress responses in wheat. These findings can support breeding programs in developing wheat varieties that sustain high yields despite warm nights. Plain Language Summary High night‐time temperature (HNT) reduces wheat yield by disrupting plant growth and development, making it essential to identify genetic factors that enhance resilience. This study evaluated 320 winter wheat genotypes under control and HNT conditions using field‐based heat tents over 2 years to uncover the genetic basis of yield‐related traits under HNT stress. Several genetic regions associated with HNT tolerance were identified, influencing key traits such as biomass, spike number, and spike weight. Distinct haplotypes were found, some specifically enhancing wheat performance under HNT, while others conferred benefits across both control and stress conditions. These insights provide valuable genetic targets for breeding wheat varieties with improved resilience to rising night‐time temperature.

One of the important factors that influences Zn deficiency tolerance and grain Zn loading in crops is the within-plant allocation of Zn. Three independent experiments were carried out to understand the internal Zn distribution patterns in rice genotypes grown in Zn-sufficient and Zn-deficient agar nutrient solution (ANS). In one of the experiments, two rice genotypes (IR55179 and KP) contrasting in Zn deficiency tolerance were leaf-labeled with (65)Zn. In the other two experiments, two Zn biofortification breeding lines (IR69428 and SWHOO) were either root- or leaf-labeled with (65)Zn. Rice genotype IR55179 showed significantly higher Zn deficiency tolerance than KP at 21 and 42 days after planting. When KP was Zn-deficient, it failed to translocate (65)Zn from the labeled leaf to newly emerging leaves. Similarly, the root-to-shoot translocation of unlabeled Zn was lower in KP than in IR55179. These results suggest that some Zn-efficient rice genotypes have greater ability to translocate Zn from older to actively growing tissues than genotypes sensitive to Zn deficiency. Among the two Zn biofortication breeding lines that were leaf-labeled with (65)Zn at 10 days before panicle initiation stage, (65)Zn distribution in the grains at maturity was similar between both genotypes in Zn-sufficient conditions. However, under Zn-deficient conditions, SWHOO accumulated significantly higher (65)Zn in grains than IR69428, indicating that SWHOO is a better remobilizer than IR69428. When the roots of these two Zn biofortication breeding lines were exposed to (65)Zn solution at 10 days after flowering, IR69428 showed higher root uptake of (65)Zn than SWHOO in Zn-sufficient conditions, but (65)Zn allocation in the aerial parts of the plant was similar between both genotypes.

Enriching iron (Fe) and zinc (Zn) content in rice grains, while minimizing cadmium (Cd) levels, is important for human health and nutrition. Natural genetic variation in rice grain Zn enables Zn-biofortification through conventional breeding, but limited natural Fe variation has led to a need for genetic modification approaches, including over-expressing genes responsible for Fe storage, chelators, and transporters. Generally, Cd uptake and allocation is associated with divalent metal cations (including Fe and Zn) transporters, but the details of this process are still unknown in rice. In addition to genetic variation, metal uptake is sometimes limited by its bioavailability in the soil. The availability of Fe, Zn, and Cd for plant uptake varies widely depending on soil redox potential. The typical practice of flooding rice increases Fe while decreasing Zn and Cd availability. On the other hand, moderate soil drying improves Zn uptake but also increases Cd and decreases Fe uptake. Use of Zn- or Fe-containing fertilizers complements breeding efforts by providing sufficient metals for plant uptake. In addition, the timing of nitrogen fertilization has also been shown to affect metal accumulation in grains. The purpose of this mini-review is to identify knowledge gaps and prioritize strategies for improving the nutritional value and safety of rice.