The increasing frequency and severity of High Nighttime Temperature (HNT) threatens to damage rice quality by inducing the chalky grain phenotype. To better understand the roles that small RNAs (sRNAs) play in HNT-induced chalkiness in rice, we sequenced sRNA libraries from the R6-stage caryopses samples and flag leaves of 8 rice genotypes differing in their HNT-induced chalkiness (low chalky [LC] or high chalky [HC]) under Control Nighttime Temperature (CNT) and HNT conditions. These efforts allowed us to deposit 84 high-quality sRNA libraries for 8 varieties. Additionally, high-quality degradome libraries were generated for the caryopses and flag leaves of the Cypress variety under both CNT and HNT conditions. Our sRNA sequencing data is likely to be useful in detecting potential relationships between sRNA regulation and the HNT-induced chalky phenotype, while the degradome sequencing data will be useful in identifying sRNA targets relevant to the tissues and conditions analysed. Both the sRNA and degradome sequencing libraries have been deposited in the Sequence Read Archive, so they can be further analysed in future studies investigating the importance of HNT-altered sRNAs not only on grain quality, but also for many other important agronomic traits.

Photosynthesis is a complex polygenic trait that directly influences crop yield and remains a challenging physiological trait to dissect genetically. This study is novel in its large-scale evaluation of photosynthetic performance across 181 diverse rice accessions, representing six subpopulations, under controlled conditions. By integrating photosynthetic measurements from the flag leaf at the booting stage with genome-wide association studies (GWASs) using 3.7 million high-quality single nucleotide polymorphism (SNP) markers, candidate genes were identified for photosynthesis. A total of 18 putative quantitative trait nucleotides (QTNs) [logarithmic odds (LOD) ≥ 8.0] were identified across the MLMM, FarmCPU, and BLINK models and are dispersed on all chromosomes except 5 and 10, including two QTNs (1-2050328 and 12-11380740) that were commonly identified in two models. Following QTN identification, gene mining analysis revealed 1,091 structural and regulatory genes in flanking regions. Subsequently, fine mapping using the gene haplotype analysis suggested 43 genes, including signaling/regulatory genes (receptor like kinases, F-box, RING, and auxin-responsive genes), gene regulators (histones, NAC/NAM, and PPR), membrane trafficking/transport (Exo70 and ADP-ribosylation factor), stress and defense components (heat shock protein, thionin, and MAC/perforin), and 19 uncharacterized proteins, of which seven genes were further selected as candidate gene using ortholog and regulatory analyses. The candidate genes may associate with photosynthesis, including carotenoid isomerase and various kinases, along with genes involved in stomatal regulation (OsABA4), sugar transport (sugar transporter 14 and UDP-glucose transporter), and leaf development (auxin-responsive genes), collectively contributing to efficient photosynthate production and assimilate translocation. Furthermore, the integration of genomic prediction analyses across GWAS, ridge regression best linear unbiased prediction (RRB), and bootstrap trees (BTS) models identified 44 common SNPs corresponding to these candidate regions, thereby enhancing the accuracy of genomic breeding value estimation across the population. To further explore the phenotypic response of photosynthesis based on subpopulation, five diverse rice accessions were selected for a detailed study of light response (A/Q), carbon dioxide response (A/Ci), and non-photochemical quenching (NPQ), enabling the assessment of photosynthetic variation across diverse genetic backgrounds. This study identified significant putative genomic regions, candidate genes, and a set of SNP markers associated with high photosynthesis in rice accessions, providing valuable resources for plant breeding and genomics-assisted breeding to enhance rice yield.

Background : Higher ambient temperatures during the cropping season, especially during nighttime, reduces rice grain quality by increasing chalkiness, primarily defined by altered starch metabolism. MicroRNAs (miRNAs) regulate various biological processes, including grain development and maturation. However, their role in high nighttime temperature (HNT)-induced grain chalkiness in rice is unknown. To address this phenomenon, an attempt was made to identify HNT-responsive miRNAs in developing caryopses and flag leaves. The miRNA expression levels were investigated between several high chalky (HC) and low chalky (LC) varieties to identify potential microRNAs involved in impacting grain chalkiness traits. Results : 138 small RNA-seq libraries were generated from the R6-stage caryopses and flag leaves from a panel of 13 rice varieties with varying chalkiness under HNT. Genetic variation among rice varieties for miRNAs expression was found. A comparison of miRNAs for differential regulation patterns between genetically closely related HC and LC varieties revealed specific miRNAs with consistently higher expression levels in one phenotype relative to the other. Notably, some of these miRNAs have predicted or confirmed effects in regulating grain quality and HNT responses. Furthermore, a degradome analysis of mRNA in caryopsis and flag leaf tissues revealed several novel miRNA-mRNA target pairs with some targets possibly involved in rice starch metabolism. Conclusions : This study revealed a number of differentially regulated miRNAs with potential roles towards alterations of grain chalkiness in rice under HNT stress. These miRNAs are potential candidates for future analyses and investigation regarding their effects on improving rice grain quality under HNT-stress conditions in field settings.

High temperature impairs starch biosynthesis in developing rice grains and thereby increases chalkiness, affecting the grain quality. Genome encoded microRNAs (miRNAs) fine-tune target transcript abundances in a spatio-temporal specific manner, and this mode of gene regulation is critical for a myriad of developmental processes as well as stress responses. However, the role of miRNAs in maintaining rice grain quality/chalkiness during high daytime temperature (HDT) stress is relatively unknown. To uncover the role of miRNAs in this process, we used five contrasting rice genotypes (low chalky lines Cyp, Ben, and KB and high chalky lines LaGrue and NB) and compared the miRNA profiles in the R6 stage caryopsis samples from plants subjected to prolonged HDT (from the onset of fertilization through R6 stage of caryopsis development). Our small RNA analysis has identified approximately 744 miRNAs that can be grouped into 291 families. Of these, 186 miRNAs belonging to 103 families are differentially regulated under HDT. Only two miRNAs, Osa-miR444f and Osa-miR1866-5p, were upregulated in all genotypes, implying that the regulations greatly varied between the genotypes. Furthermore, not even a single miRNA was commonly up/down regulated specifically in the three tolerant genotypes. However, three miRNAs (Osa-miR1866-3p, Osa-miR5150-3p and canH-miR9774a,b-3p) were commonly upregulated and onemiRNA (Osa-miR393b-5p) was commonly downregulated specifically in the sensitive genotypes (LaGrue and NB). These observations suggest that few similarities exist within the low chalky or high chalky genotypes, possibly due to high genetic variation. Among the five genotypes used, Cypress and LaGrue are genetically closely related, but exhibit contrasting chalkiness under HDT, and thus, a comparison between them is most relevant. This comparison revealed a general tendency for Cypress to display miRNA regulations that could decrease chalkiness under HDT compared with LaGrue. This study suggests that miRNAs could play an important role in maintaining grain quality in HDT-stressed rice.

Rice is the most important staple crop for the sustenance of the world’s population, and drought is a major factor limiting rice production. Quantitative trait locus (QTL) analysis of drought-resistance-related traits was conducted on a recombinant inbred line (RIL) population derived from the self-fed progeny of a cross between the drought-resistant tropical japonica U.S. adapted cultivar Kaybonnet and the drought-sensitive indica cultivar ZHE733. K/Z RIL population of 198 lines was screened in the field at Fayetteville (AR) for three consecutive years under controlled drought stress (DS) and well-watered (WW) treatment during the reproductive stage. The effects of DS were quantified by measuring morphological traits, grain yield components, and root architectural traits. A QTL analysis using a set of 4133 single nucleotide polymorphism (SNP) markers and the QTL IciMapping identified 41 QTLs and 184 candidate genes for drought-related traits within the DR-QTL regions. RT-qPCR in parental lines was used to confirm the putative candidate genes. The comparison between the drought-resistant parent (Kaybonnet) and the drought-sensitive parent (ZHE733) under DS conditions revealed that the gene expression of 15 candidate DR genes with known annotations and two candidate DR genes with unknown annotations within the DR-QTL regions was up-regulated in the drought-resistant parent (Kaybonnet). The outcomes of this research provide essential information that can be utilized in developing drought-resistant rice cultivars that have higher productivity when DS conditions are prevalent.

Sucrose concentration in soy-derived foods is becoming a seminal trait for the production of food-grade soybeans. However, limited scientific knowledge is reported on this increasingly important breeding objective. In this study, 473 genetically diverse soybean germplasm accessions and 8477 high-quality single nucleotide polymorphisms (SNPs) were utilized to pinpoint genomic regions associated with seed sucrose contents through a genome-wide association study (GWAS). A total of 75 significant SNPs (LOD ≥ 6.0) were identified across GLM, FarmCPU and BLINK models, including four stable and novel SNPs (Gm03_45385087_ss715586641, Gm06_10919443_ss715592728, Gm09_45335932_ss715604570 and Gm14_10470463_ss715617454). Gene mining near 20 kb flanking genomic regions of the four stable SNP markers identified 23 candidate genes with the majority of them highly expressed in soybean seeds and pod shells. A sugar transporter encoding major facilitator superfamily gene (Glyma.06G132500) showing the highest expression in pod shells was also identified. Moreover, selection accuracy, efficiency and favorable alleles of 75 significantly associated SNPs were estimated for their utilization in soybean breeding programs. Furthermore, genomic predictions with three different scenarios revealed better feasibility of GWAS-derived SNPs for selection and improvement of seed sucrose concentration. These results could facilitate plant breeders in marker-assisted breeding and genomic selection of sucrose-enriched food-grade soybean cultivars for the global soy-food industry.

Elevated nighttime temperatures resulting from climate change significantly impact the rice crop worldwide. The rice ( Oryza sativa L.) plant is highly sensitive to high nighttime temperature (HNT) during grain-filling (reproductive stage). HNT stress negatively affects grain quality traits and has a major impact on the value of the harvested rice crop. In addition, along with grain dimensions determining rice grain market classes, the grain appearance and quality traits determine the rice grain market value. During the last few years, there has been a major concern for rice growers and the rice industry over the prevalence of rice grains opacity and the reduction of grain dimensions affected by HNT stress. Hence, the improvement of heat-stress tolerance to maintain grain quality of the rice crop under HNT stress will bolster future rice value in the market. In this study, 185 F 12 - recombinant inbred lines (RILs) derived from two US rice cultivars, Cypress (HNT-tolerant) and LaGrue (HNT-sensitive) were screened for the grain quality traits grain length (GL), grain width (GW), and percent chalkiness (%chalk) under control and HNT stress conditions and evaluated to identify the genomic regions associated with the grain quality traits. In total, there were 15 QTLs identified; 6 QTLs represented under control condition explaining 3.33% to 8.27% of the phenotypic variation, with additive effects ranging from − 0.99 to 0.0267 on six chromosomes and 9 QTLs represented under HNT stress elucidating 6.39 to 51.53% of the phenotypic variation, with additive effects ranging from − 8.8 to 0.028 on nine chromosomes for GL, GW, and % chalk. These 15 QTLs were further characterized and scanned for natural genetic variation in a japonica diversity panel (JDP) to identify candidate genes for GL, GW, and %chalk. We found 6160 high impact single nucleotide polymorphisms (SNPs) characterized as such depending on their type, region, functional class, position, and proximity to the gene and/or gene features, and 149 differentially expressed genes (DEGs) in the 51 Mbp genomic region comprising of the 15 QTLs. Out of which, 11 potential candidate genes showed high impact SNP associations. Therefore, the analysis of the mapped QTLs and their genetic dissection in the US grown Japonica rice genotypes at genomic and transcriptomic levels provide deep insights into genetic variation beneficial to rice breeders and geneticists for understanding the mechanisms related to grain quality under heat stress in rice.

Abstract Background: Rice is the main staple food for the global population and drought is one of the limited factor in rice production. In this research, progeny of a cross between an adapted U.S. rice cultivars with a tropical japonica and an indica rice genotype, were screened for drought resistant (DR) traits to identify DR loci, that would be useful for breeding U.S. rice cultivars for a water saving agricultural system.Results: A recombinat inbred line (RIL) population, generated from selfed progeny of the cross between the drought resistant tropical japonica U.S. cultivar Kaybonnet and an indica drought sensitive cultivar ZHE733, was chosen for quantitative trait locus (QTLs) analysis of drought-resistance related traits. The DR traits were quantified by measuring different parameters of morphological traits, grain yield components and root architectural traits. K/Z RIL population of 198 lines were screened in the field at Fayetteville (AR), by giving controlled drought stress (DS) and well-watered (WW) treatment at the reproductive stage, consequently for three years and the effects of DS were quantify by measuring morphological traits and grain yield components. The effect of abscisic acid (ABA) sensitivity screen on parents and 198 lines at the V3 stage in culture media was quantified by measuring root architectural traits. QTL analysis was performed with a set of 4133 single nucleotide polymorphism (SNP) markers by using QTL IciMapping software version 4.2.53. A total of 41 QTLs and 184 candidate genes within the DR-QTL regions were identified for drought related traits. The potential candidate genes were validated by RT-qPCR of parental lines. The results of candidate DR genes revealed that the gene expression of 15 candidate DR genes with known annotations, and two candidate DR genes with unknown annotations within the DR-QTL regions were up-regulated in the drought resistant parent (Kaybonnet) compared to the drought sensitive parent (ZHE733) under DS conditions.Conclusions: In this study, we detected 41 QTLs and 184 candidate genes within the DR-QTL regions, and most of the candidate genes were up-regulated in Kaybonnet as the drought resistant parent. The findings of this research provide important information to develop drought-resistant rice varieties with greater productivity under DS conditions.

The railways operate in various varying environmental conditions. The working environments affects the tribology of the rail and wheel contact. Therefore, the tribological properties of rail and wheel contact become important to study in these conditions. Commonly, rail and wheel contact functions under mist and wet conditions. The present study is conducted to analyse the behaviour of friction force and wear under dry, water with MQL and wet condition. The MQL is used to generate the mist condition. The study is performed on pin-on-disk tribometer in which pin is made of rail track material and disk is made of wheel material. From the experiments it was found that the friction force and wear both decreases significantly for mist condition as compared to dry condition and is least for wet condition. It was also noted that if load is increased the friction force and wear depth are also increases under all three conditions.

Rice (Oryza sativa L.) is the primary food for half of the global population. Recently, there has been increasing concern in the rice industry regarding the eating and milling quality of rice. This study was conducted to identify genetic information for grain characteristics using a recombinant inbred line (RIL) population from a japonica/indica cross based on high-throughput SNP markers and to provide a strategy for improving rice quality. The RIL population used was derived from a cross of “Kaybonnet (KBNT lpa)” and “ZHE733” named the K/Z RIL population, consisting of 198 lines. A total of 4133 SNP markers were used to identify quantitative trait loci (QTLs) with higher resolution and to identify more accurate candidate genes. The characteristics measured included grain length (GL), grain width (GW), grain length to width ratio (RGLW), hundred grain weight (HGW), and percent chalkiness (PC). QTL analysis was performed using QTL IciMapping software. Continuous distributions and transgressive segregations of all the traits were observed, suggesting that the traits were quantitatively inherited. A total of twenty-eight QTLs and ninety-two candidate genes related to rice grain characteristics were identified. This genetic information is important to develop rice varieties of high quality.

Rice (Oryza sativa) is the staple food for more than half of the world population. Rice needs 2-3 times more water compared to other crops. Drought condition is one of the limited factor in rice production. Recombinant inbred line population derived from a cross between rice genotype tropical japonica Kaybonnet and indica ZHE733 named K/Z RIL population was used to identify candidate genes for chlorophyll content related to grain yield under drought condition. Chlorophyll content in the flag leaf of the rice plant is related to the grain yield since chlorophyll plays an important role in the photosynthesis. The K/Z RIL population was screened in the field at Fayetteville, Arkansas, USA by controlled drought stress treatment at the reproductive stage (R3), and the effect of drought stress was quantify by measuring chlorophyll content, flag leaf characteristics, and grain yield. Quantitative trait loci (QTL) analysis was performed with a set of 4133 single nucleotide polymorphism (SNP) markers by using QTL IciMapping software version 4.2.53. Candidate genes within the QTL regions were identified by using the MSU Rice Genome Annotation Project database release 7.0 as the reference. A total of eleven QTLs and forty-three candidate genes were identified for chlorophyll content related to the grain yield under drought condition. Most of the candidate genes involve in biological processes, molecular functions, and cell components. By understanding the genetic complexity of the chlorophyll content, this research provides information to develop drought-resistant rice varieties with greater productivity under drought stress condition.

To dissect the genetic complexity of rice grain yield (GY) and quality in response to heat stress at the reproductive stage, a diverse panel of 190 rice accessions in the United States Department of Agriculture (USDA) rice mini-core collection (URMC) diversity panel were treated with high nighttime temperature (HNT) stress at the reproductive stage of panicle initiation. The quantifiable yield component response traits were then measured. The traits, panicle length (PL), and number of spikelets per panicle (NSP) were evaluated in subsets of the panel comprising the rice subspecies Oryza sativa ssp. Indica and ssp. Japonica. Under HNT stress, the Japonica ssp. exhibited lower reductions in PL and NSP and a higher level of genetic variation compared with the other subpopulations. Whole genome sequencing identified 6.5 million single nucleotide polymorphisms (SNPs) that were used for the genome-wide association studies (GWASs) of the PL and NSP traits. The GWAS analysis in the Combined, Indica, and Japonica populations under HNT stress identified 83, 60, and 803 highly significant SNPs associated with PL, compared to the 30, 30, and 11 highly significant SNPs associated with NSP. Among these trait-associated SNPs, 140 were coincident with genomic regions previously reported for major GY component quantitative trait loci (QTLs) under heat stress. Using extents of linkage disequilibrium in the rice populations, Venn diagram analysis showed that the highest number of putative candidate genes were identified in the Japonica population, with 20 putative candidate genes being common in the Combined, Indica and Japonica populations. Network analysis of the genes linked to significant SNPs associated with PL and NSP identified modules that were involved in primary and secondary metabolisms. The findings in this study could be useful to understand the pathways/mechanisms involved in rice GY and its components under HNT stress for the acceleration of rice-breeding programs and further functional analysis by molecular geneticists.

The present investigation was aimed at estimating correlation and path coefficients using observations on 22 yield components and quality characters in thirty rice (Oriza sativa L.) genotypes. The genotypes were evaluated in RBD and ANOVA results revealed the highly significant mean sum of squares among the genotypes for all the characters. Correlation analysis revealed that grain yield showed highly significant and positive correlation with flag leaf length, number of grains per panicle, 100 grain weight, 100 kernel weight, kernel length after cooking and kernel elongation ratio. Path coefficient analysis revealed that 100 grain weight, 100 kernel weight after cooking, hulling%, number of grains per panicle and flag leaf length exerted high positive direct effect on grain yield and 100 grain weight, grain weight per panicle had negative direct effect towards grain yield. These relationships may be helpful in crop improvement, if selection favours high grain yield then the remaining characters which are positively associated will be automatically improved. The path-coefficient analysis helps to understand the causal factor better, because it divides total effects of paired traits into direct and indirect effects via other characters. These characters could be utilized as indices of selection for future breeding programme.

Medium range weather forecast and weather based agro advisories help in farming community by minimize the production losses due to unfavourable conditions. So, there is need to study reliability and suitability of the medium range weather forecasts for further improvement. In this study verification of medium range weather forecast of Malkangiri, Odisha during the period of 2017-18 are discussed in respect to rainfall and temperature. Usability based on quantity of rainfall was higher in winter season (100%) and very less in monsoon season (17.02%). Except monsoon season, the quantitative forecast of rainfall revealed higher reliability over percent forecast accuracy (ratio score). Higher Root Mean Square Error (RMSE) of rainfall in monsoon season (18.48) indicated lower accuracy in prediction. Annual usability of forecasted maximum temperature and minimum temperature were 71.11 and 76.19%, respectively. The highest percentage of usability for maximum and minimum temperature was observed in winter season. The RMSE for minimum temperature was found lower than maximum temperature indicating higher accuracy. Furthermore, there is scope of improvement in usability of rainfall mainly for monsoon season as well as temperature for more income of farming community of Malkangiri district of Odisha by following weather based agro advisories.

Plants in their natural habitats adapt to drought stress in the environment through a variety of mechanisms, ranging from transient responses to low soil moisture to major survival mechanisms of escape by early flowering in absence of seasonal rainfall. However, crop plants selected by humans to yield products such as grain, vegetable, or fruit in favorable environments with high inputs of water and fertilizer are expected to yield an economic product in response to inputs. Crop plants selected for their economic yield need to survive drought stress through mechanisms that maintain crop yield. Studies on model plants for their survival under stress do not, therefore, always translate to yield of crop plants under stress, and different aspects of drought stress response need to be emphasized. The crop plant model rice (Oryza sativa) is used here as an example to highlight mechanisms and genes for adaptation of crop plants to drought stress.