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Initial evaluations of the System of Rice Intensification in India and elsewhere focused mainly on its impacts on yield and income, and usually covered just one or two seasons. Researchers at the ICAR-Indian Institute of Rice Research have conducted a more comprehensive evaluation of SRI methods over six years (six wet and six dry seasons), comparing them with three alternatives: modified, partially mechanized SRI (MSRI) to reduce labor requirements; direct-seeded rice (DSR) as an alternative method for growing rice; and conventional transplanting of rice with flooding of fields (CTF). Grain yield with SRI methods was found to be about 50% higher than with CTF (6.35 t ha−1 vs. 4.27 t ha−1), while the MSRI yield was essentially the same (6.34 t ha−1), 16% more than with DSR (5.45 t ha−1). Water productivity with SRI methods was 5.32–6.85 kg ha-mm−1, followed by 4.14–5.72 kg ha-mm−1 for MSRI, 5.06–5.11 kg ha-mm−1 for DSR, and 3.52–4.56 kg ha-mm−1 for CTF. In comparison with CTF, SRI methods significantly enhanced soil microbial populations over time: bacteria by 12%, fungi by 8%, and actinomycetes by 20%. Biological activity in the rhizosphere was also higher as indicated by 8.5% greater dehydrogenase and 16% more FDA enzymes in soil under SRI management. Similarly, an indicator of soil organic matter, glucosidase activity, was 78% higher compared to CTF. SRI enhanced the relative abundance of beneficial microbial-feeding nematodes by 7.5% compared to CTF, while that of plant-pathogenic nematodes was 7.5% lower under SRI. Relative to conventional methods, SRI management reduced GHG emissions by 21%, while DSR reduced them by 23%, and MSRI by 13%, compared to standard rice-growing practice. Economic analysis showed both gross and net economic returns to be higher with SRI than with the other management systems evaluated. While the six-year study documented many advantages of SRI crop management, it also showed that MSRI is a promising adaptation that provides similar benefits but with lower labor requirements.

Rice (Oryza sativa L.) is an important source of nutrition for the world’s burgeoning population that often faces yield loss due to infestation by the brown planthopper (BPH, Nilaparvata lugens (Stål)). The development of rice cultivars with BPH resistance is one of the crucial precedences in rice breeding programs. Recent progress in high-throughput SNP-based genotyping technology has made it possible to develop markers linked to the BPH more quickly than ever before. With this view, a genome-wide association study was undertaken for deriving marker-trait associations with BPH damage scores and SNPs from genotyping-by-sequencing data of 391 multi-parent advanced generation inter-cross (MAGIC) lines. A total of 23 significant SNPs involved in stress resistance pathways were selected from a general linear model along with 31 SNPs reported from a FarmCPU model in previous studies. Of these 54 SNPs, 20 were selected in such a way to cover 13 stress-related genes. Kompetitive allele-specific PCR (KASP) assays were designed for the 20 selected SNPs and were subsequently used in validating the genotypes that were identified, six SNPs, viz, snpOS00912, snpOS00915, snpOS00922, snpOS00923, snpOS00927, and snpOS00929 as efficient in distinguishing the genotypes into BPH-resistant and susceptible clusters. Bph17 and Bph32 genes that are highly effective against the biotype 4 of the BPH have been validated by gene specific SNPs with favorable alleles in M201, M272, M344, RathuHeenati, and RathuHeenati accession. These identified genotypes could be useful as donors for transferring BPH resistance into popular varieties with marker-assisted selection using these diagnostic SNPs. The resistant lines and the significant SNPs unearthed from our study can be useful in developing BPH-resistant varieties after validating them in biparental populations with the potential usefulness of SNPs as causal markers.

Via national lockdowns, the COVID-19 pandemic disrupted the production and distribution of foodstuffs worldwide, including rice (Oryza sativa L.) production, affecting the prices in India’s agroecosystems and markets. The present study was performed to assess the impact of the COVID-19 national lockdown on rice prices in India, and to develop statistical machine learning models to forecast price changes under similar crisis scenarios. To estimate the rice prices under COVID-19, the general time series models, such as the autoregressive integrated moving average (ARIMA) model, the artificial neural network (ANN) model, and the extreme learning machine (ELM) model, were applied. The results obtained using the ARIMA intervention model revealed that during the COVID-19 lockdown in India, rice prices increased by INR 0.92/kg. In addition, the ELM intervention model was faster, with less computation time, and provided better results vs other models because it detects the nonlinear pattern in time series data, along with the intervention variable, which was considered an exogenous variable. The use of forecasting models can be a useful tool in supporting decision makers, especially under unpredictable crises. The study results are of great importance for the national agri-food sector, as they can bolster authorities and policymakers in planning and designing more sustainable interventions in the food market during (inter)national crisis situations.

Polished rice is one of the commonly consumed staple foods across the world. However, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising recombinant inbred lines (RILs) for grain Zn and single plant yield, 190 RILs developed from PR116 and Ranbir Basmati were evaluated in two environments (E1 and E2). A subset of 44 contrasting RILs for grain Zn was screened in another two environments (E3 and E4). Phenotypic data was collected for 10 traits, viz., days to 50% flowering, plant height, panicle length, number of tillers, single plant yield (SPY), test weight, Fe and Zn in brown (IBR, ZBR), and polished rice (IPR, ZPR). Stepwise regression analysis of trait data in 190 RILs and a subset of 44 RILs revealed the interdependence of ZPR, ZBR, IPR, and IBR and the negative association of grain Zn with single plant yield. Based on the additive main effect and multiplicative interaction (AMMI) and genotype and genotype × environment interaction (GGE) analyses of the subset of 44 RILs across four environments (E1–E4), six promising RILs were identified for ZPR with >28 ppm. Mapping of 190 RILs with 102 simple sequence repeats (SSRs) resulted in 13 QTLs for best linear unbiased estimates (BLUEs) of traits including advantage over check (AOC). Using genotype-based sequencing (GBS), the subset of 44 RILs was mapped with 1035 single-nucleotide polymorphisms (SNPs) and 21 QTLs were identified. More than 100 epistatic interactions were observed. A major QTL qZPR.1.1 (PV 37.84%) and another QTL qZPR.11.1 (PV 15.47%) were identified for grain Zn in polished rice. A common major QTL (qZBR.2.1 and qZPR.2.1) was also identified on chromosome 2 for grain Zn content across SSR and SNP maps. Two potential candidate genes related to transporters were identified based on network analyses in the genomic regions of QTL < 3 Mb. The RILs identified for grain Zn and SPY were nominated for national evaluation as under rice biofortification, and two QTLs identified based on BLUEs could be used in the rice biofortification breeding programs.

Polished rice is widely consumed staple food across the globe, however, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising genotypes for grain Zn, a total of 40 genotypes consisting 20 rice landraces, and 20 released high yielding rice varieties were evaluated in three environments (wet seasons 2014, 2015 and 2016) for nine traits including days to 50% flowering (DFF), plant height (PH), panicle length (PL), total number of tillers (TNT), single plant yield (SPY), Fe and Zn in brown (IBR, ZBR) and polished rice (IPR, ZPR). Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype × Environment Interaction (GGE) analyses identified genotypes G22 (Edavankudi Pokkali), G17 (Taraori Basmati), G27 (Chittimuthyalu) and G26 (Kalanamak) stable for ZPR and G8 (Savitri) stable for SPY across three environments. Significant negative correlation between yield and grain Zn was reaffirmed. Regression analysis indicated the contribution of traits toward ZPR and SPY and also desirable level of grain Zn in brown rice. A total of 39,137 polymorphic single nucleotide polymorphisms (SNPs) were obtained through double digest restriction site associated DNA (dd-RAD) sequencing of 40 genotypes. Association analyses with nine phenotypic traits revealed 188 stable SNPs with six traits across three environments. ZPR was associated with SNPs located in three putative candidate genes (LOC_Os03g47980, LOC_Os07g47950 and LOC_Os07g48050) on chromosomes 3 and 7. The genomic region of chromosome 7 co localized with reported genomic regions (rMQTL7.1) and OsNAS3 candidate gene. SPY was found to be associated with 12 stable SNPs located in 11 putative candidate genes on chromosome 1, 6, and 12. Characterization of rice landraces and varieties in terms of stability for their grain Zn and yield identified promising donors and recipients along with genomic regions in the present study to be deployed rice Zn biofortification breeding program.

Breeding for "weed competitive" cultivars is a prioritized goal under direct seeded rice (DSR) conditions for achieving higher grain yields. Early seedling vigour (ESV) is an imperative trait that imparts weed competitiveness through initial rapid growth and uniform crop establishment. African rice species Oryza glaberrima has been recognised as potential donors for weed competitive traits due to their early vegetative vigour. In the present study, 29 accessions of O. glaberrima were evaluated for early seedling vigour traits under laboratory and DSR conditions. Seedling vigour index-I and II estimated from the paper roll method under laboratory condition revealed that six O. glaberrima accessions (EC861796, EC861801, EC861804, EC861814, EC861819 and EC861820) had higher/similar seedling vigour indices than high vigour check Sabita. In addition, during Kharif 2017 and Rabi 2018, O. glaberrima accessions were phenotyped for nine ESV traits, e.g. seedling height, number of leaves/tillers, leaf area, shoot fresh/dry weight, absolute growth rate, specific leaf area and crop growth rate under DSR condition. Significant genetic variation and genotype × environment interaction was observed for ESV traits under DSR condition. The heritability estimates for ESV traits were ranging from low to high, indicating complex inheritance of the trait. The study identified six accessions of O. glaberrima (EC861787, EC861790, EC861792, EC861795, EC861819 and EC861820) as promising accessions with early seedling vigour based on mean performance in both seasons under direct seeded rice condition. Thus, our study demonstrated inherent nature of early seedling vigour in O. glaberrima and these promising accessions could be exploited for breeding weed-competitive rice cultivars. [ABSTRACT FROM AUTHOR]

Context: Broadening the gene pool of staple food crops by incorporating desirable genes from wild/relative species is way to achieve higher genetic gains. The African rice species Oryza glaberrima Steud. is a source of genes for genetic improvement of Oryza sativa L. to various biotic and abiotic stresses. Aim: The study was undertaken to identify genomic regions associated with yield and yield-related traits in interspecific backcross mapping populations derived from variety IR64 (O. sativa indica) × O. glaberrima. Methods: The BC1F2 and BC1F2:3 populations were phenotyped for days to 50% flowering, plant height, number of tillers, number of productive tillers, panicle length, spikelet fertility and grain yield under irrigated conditions. The BC1F2 population was genotyped with 99 genome-wide polymorphic SSR markers. Quantitative trait loci (QTLs) associated with yield-enhancing traits were identified through single marker analysis. Key results: Significant genetic variability was observed with moderate to high heritability in mapping populations. Genotyping revealed the presence of segregation distortion and skewed genome composition. Single marker analysis identified 20 QTLs linked to the studied traits. A QTL linked to grain yield, qGY-4.1 , derived from O. glaberrima was found in both populations with high phenotypic variance. The chromosome region around marker RM510 was identified as a QTL hotspot and putative candidate genes were identified. Conclusions: Our study demonstrates that O. glaberrima can serve as a valuable genetic resource for genetic improvement of yield-enhancing traits in O. sativa cultivars. Implications: The identified QTLs regions can be employed in molecular breeding. The promising introgression lines identified can be used as pre-breeding lines in future breeding programs. African rice species Oryza glaberrima as a source of genes for improvement of Oryza sativa is well established for various biotic and abiotic stresses. In this study, yield and yield-related QTLs derived from O. glaberrima were mapped in backcross mapping populations of IR64 × O. glaberrima. The outcomes of the study will help in harnessing useful genomic regions from O. glaberrima for genetic improvement of O. sativa. [ABSTRACT FROM AUTHOR]

Initial evaluations of the System of Rice Intensification in India and elsewhere focused mainly on its impacts on yield and income, and usually covered just one or two seasons. Researchers at the ICAR-Indian Institute of Rice Research have conducted a more comprehensive evaluation of SRI methods over six years (six wet and six dry seasons), comparing them with three alternatives: modified, partially mechanized SRI (MSRI) to reduce labor requirements; direct-seeded rice (DSR) as an alternative method for growing rice; and conventional transplanting of rice with flooding of fields (CTF). Grain yield with SRI methods was found to be about 50% higher than with CTF (6.35 t ha−1 vs. 4.27 t ha−1), while the MSRI yield was essentially the same (6.34 t ha−1), 16% more than with DSR (5.45 t ha−1). Water productivity with SRI methods was 5.32–6.85 kg ha-mm−1, followed by 4.14–5.72 kg ha-mm−1 for MSRI, 5.06–5.11 kg ha-mm−1 for DSR, and 3.52–4.56 kg ha-mm−1 for CTF. In comparison with CTF, SRI methods significantly enhanced soil microbial populations over time: bacteria by 12%, fungi by 8%, and actinomycetes by 20%. Biological activity in the rhizosphere was also higher as indicated by 8.5% greater dehydrogenase and 16% more FDA enzymes in soil under SRI management. Similarly, an indicator of soil organic matter, glucosidase activity, was 78% higher compared to CTF. SRI enhanced the relative abundance of beneficial microbial-feeding nematodes by 7.5% compared to CTF, while that of plant-pathogenic nematodes was 7.5% lower under SRI. Relative to conventional methods, SRI management reduced GHG emissions by 21%, while DSR reduced them by 23%, and MSRI by 13%, compared to standard rice-growing practice. Economic analysis showed both gross and net economic returns to be higher with SRI than with the other management systems evaluated. While the six-year study documented many advantages of SRI crop management, it also showed that MSRI is a promising adaptation that provides similar benefits but with lower labor requirements. [ABSTRACT FROM AUTHOR]

Soil is a crucial component for plant growth, as it provides water, nutrients, and mechanical support. Various factors, such as crop cultivation, microflora, nutrient addition, and water availability, significantly affect soil properties. Maintaining soil health is important, and one approach is the introduction of native organisms with multifaceted activities. The study evaluates the effects of introducing these microbes (Trichoderma asperellum strain TAIK1, Bacillus cabrialesii strain BIK3, Pseudomonas putida strain PIK1, and Pseudomonas otitidis strain POPS1) and their consortium, a combination of four bioagents, on soil health, plant growth, and the incidence of stem rot disease caused by Sclerotium oryzae in rice. Upon treatment of soil with the consortium of the four native bioagents mentioned above through seed treatment or soil application, variations/increases in the chemical properties of the soil were observed, viz., pH (8.08 to 8.28), electrical conductivity (EC) (0.72 to 0.75 d S m−1), organic carbon (OC) (0.57 to 0.68 %), available soil nitrogen (SN) (155 to 315 kg/ha), soil phosphorus (SP) (7.87 to 24.91 kg/ha), soil potassium (SK) (121.29 to 249.42 kg/ha), and soil enzymes (urease (0.73 to 7.33 µg urea hydrolyzed g−1 soil h−1), acid and alkaline phosphatase (0.09 to 1.39 and 0.90 to 1.78 µg of p-nitrophenol released g−1 soil h−1), and dehydrogenase (0.14 to 16.44 mg triphenyl formazan (TPF) produced g−1 soil h−1)), compared to untreated soil. Treatment of seeds with the consortium of four native bioagents resulted in a significant increase in plant height (39.16%), the number of panicles (30.29%), and average grain yield (41.36%) over control plants. Under controlled conditions, the bioagent-treated plants showed a 69.37% reduction in stem rot disease. The findings of this study indicate a positive correlation between soil properties (pH, EC, OC, SN, SP, SK, and soil enzymes) and plant growth (shoot and root length, fresh and dry weight) as well as a highly negative association of soil properties with stem rot disease severity. The results suggest that using native bioagents as a management strategy can control stem rot disease and enhance crop productivity, while reducing reliance on chemical management. These findings provide valuable insights into the development of sustainable agricultural practices that maximize productivity by minimizing negative environmental impacts, which promotes soil health, plant growth, and disease management. [ABSTRACT FROM AUTHOR]

The System of Rice Intensification (SRI) developed in Madagascar has spread to many parts of the world, including India. This study assessing insect pest prevalence on rice grown with SRI vs. conventional methods at multiple locations in India was prompted by reports that SRI-managed rice plants are healthier and more resistant to pest and disease damage. Field experiments were conducted under the All-India Coordinated Rice Improvement Project over a 5-year period. The split-plot design assessed both cultivation methods and different cultivars, hybrids and improved varieties. Across the eight locations, SRI methods of cultivation showed a lower incidence of stem borer, planthoppers, and gall midge compared to conventional methods. Whorl maggots and thrips, on the other hand, were observed to be higher. Grain yield was significantly higher with SRI management across all locations. Higher ash, cellulose, hemicellulose, as well as silica content in rice plants under SRI management could explain at least in part the SRI plants' resistance to pest damage. Analysis of guild composition revealed that in SRI plots, there were more natural enemies (insect predators and parasitoids) present and fewer crop pests (phytophages). A meta-analysis that considered other published research on this subject revealed a lower incidence of dead hearts, white ear-heads, and leaf folders, along with higher grain yield, in SRI plots. [ABSTRACT FROM AUTHOR]

Via national lockdowns, the COVID-19 pandemic disrupted the production and distribution of foodstuffs worldwide, including rice (Oryza sativa L.) production, affecting the prices in India's agroecosystems and markets. The present study was performed to assess the impact of the COVID-19 national lockdown on rice prices in India, and to develop statistical machine learning models to forecast price changes under similar crisis scenarios. To estimate the rice prices under COVID-19, the general time series models, such as the autoregressive integrated moving average (ARIMA) model, the artificial neural network (ANN) model, and the extreme learning machine (ELM) model, were applied. The results obtained using the ARIMA intervention model revealed that during the COVID-19 lockdown in India, rice prices increased by INR 0.92/kg. In addition, the ELM intervention model was faster, with less computation time, and provided better results vs other models because it detects the nonlinear pattern in time series data, along with the intervention variable, which was considered an exogenous variable. The use of forecasting models can be a useful tool in supporting decision makers, especially under unpredictable crises. The study results are of great importance for the national agri-food sector, as they can bolster authorities and policymakers in planning and designing more sustainable interventions in the food market during (inter)national crisis situations. [ABSTRACT FROM AUTHOR]

The demonstrations on improved rice production technology were organized in the Wanaparthy, Nagarkurnool, Yadadri Bhuvanagiri, and Rangareddy districts of Telangana state of India. These demonstrations were organized under the Scheduled Caste Sub Plan of the Indian Institute of Rice Research during the wet season of 2021. The biofortified varieties assume great significance to achieve nutrition security. Hence, the zinc biofortified rice variety, DRR Dhan 48 was demonstrated on the 142 farmer fields and the economic impact of these demonstrations was assessed with the 'difference in difference' approach. The results revealed that the production of rice under demonstration plots was more profitable with a higher benefit-to-cost ratio (B:C; 1.9) compared to that of the control plots (1.4). The independent two-sample t-test revealed that the productivity at the control plots was not statistically different from that of the demonstrations plots (p = 0.112) before the project was implemented, however, with the intervention in the form of the demonstration of improved rice production technology, the productivity differed significantly (p = 0.000) for the control and the demonstration plots for the intervention year. The results of the difference in differences estimator revealed that there was a positive impact of demonstrations on the yield of the beneficiaries. The mean productivity of demonstration plots and control plots were 5.52 t/ha and 4.5 t/ha, respectively. The farmers had an additional yield advantage of 22.6% over the control plots. The results indicated that the adoption of an improved package of practices would enable harnessing higher productivity levels and bridging the yield gaps in similar agroecosystems. Also, the results suggest the practical significance of the popularization of biofortified rice varieties for food and nutritional security. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa L.) is an important source of nutrition for the world's burgeoning population that often faces yield loss due to infestation by the brown planthopper (BPH, Nilaparvata lugens (Stål)). The development of rice cultivars with BPH resistance is one of the crucial precedences in rice breeding programs. Recent progress in high-throughput SNP-based genotyping technology has made it possible to develop markers linked to the BPH more quickly than ever before. With this view, a genome-wide association study was undertaken for deriving marker-trait associations with BPH damage scores and SNPs from genotyping-by-sequencing data of 391 multi-parent advanced generation inter-cross (MAGIC) lines. A total of 23 significant SNPs involved in stress resistance pathways were selected from a general linear model along with 31 SNPs reported from a FarmCPU model in previous studies. Of these 54 SNPs, 20 were selected in such a way to cover 13 stress-related genes. Kompetitive allele-specific PCR (KASP) assays were designed for the 20 selected SNPs and were subsequently used in validating the genotypes that were identified, six SNPs, viz, snpOS00912, snpOS00915, snpOS00922, snpOS00923, snpOS00927, and snpOS00929 as efficient in distinguishing the genotypes into BPHresistant and susceptible clusters. Bph17 and Bph32 genes that are highly effective against the biotype 4 of the BPH have been validated by gene specific SNPs with favorable alleles in M201, M272, M344, RathuHeenati, and RathuHeenati accession. These identified genotypes could be useful as donors for transferring BPH resistance into popular varieties with marker-assisted selection using these diagnostic SNPs. The resistant lines and the significant SNPs unearthed from our study can be useful in developing BPH-resistant varieties after validating them in biparental populations with the potential usefulness of SNPs as causal markers. [ABSTRACT FROM AUTHOR]

The brown planthopper (Nilaparvata lugens (Stål) is a major insect pest that is primarily present in Asia causing a significant impact on rice crop. Seventy-three rice genotypes were evaluated for molecular diversity based on known BPH resistance loci. A total number of 108 alleles were detected by 39 polymorphic markers with an average of 2.37 alleles per locus. The allele frequency which is useful in estimating the frequency of alleles, ranged from 0.054 to 0.9726, while the expected heterozygosity varied between 0.054 (RM494) and 0.688 (RM231) with an average of 0.431.The Polymorphic Information Content (PIC) values provided an estimation of the marker's discriminating power by ranged from 0.066 (RM496) to 0.621 (RM231) suggesting moderate level of polymorphism for the selected BPH specific SSR markers among the germplasm lines. Accounting the major allele frequency, heterozygosity and PIC content, the marker RM231 associated with QBph3.1 and regarded as the most informative one along with RM19291, RM335, RM469, RM518, RM8213, RM228, RH078 and RM589 for dissecting the molecular diversity of germplasm lines with respect to BPH resistance. Based on the marker data, the genotypes were classified into seven clusters that distinguished the lines clustering as resistant and susceptible separately. The information about the genetic diversity of these lines will be extremely useful for proper selection of parents related to BPH reaction, especially for gene mapping and for marker assisted selection. [ABSTRACT FROM AUTHOR]

A diverse set of 107 rice genotypes was evaluated for yield, shattering and dormancy traits. Analysis of variance revealed sizable variation while skewness and kurtosis values indicated near-normal distribution for most of the traits, thus quantitative nature controlled by many genes. A highly significant deviation from a normal distribution for dormancy and shattering % indicated their qualitative nature of inheritance. Four promising genotypes 'IRGC1723' (early with 65 days to flowering), 'IRGC 11108' and 'RNR 15459' (high grain number – 358 and low average shattering – <5%), 'RNR 11718' (high single plant yield – 56.73 g, low average shattering – <5% and dormancy period – 21 days) are identified. A significant positive correlation between shattering and dormancy confirms inter-relationship among domestication-related characteristics. The principal component analysis revealed the contribution of four PCs to maximum variability and hierarchical clustering grouped the genotypes into 18 divergent clusters. Five cultivars (Karimnagar Samba, Sheetal, PR 121, Pranahitha and Jagitial Samba) with a combination of low shattering ability (3.35–5.7%) and considerable dormancy period (13–20 days) falling in the same cluster can be used as donors for the improvement of rice genotypes with low shattering ability and incorporating a considerable period of dormancy so as to avoid pre-harvest sprouting due to delayed harvesting. Further, they can be crossed with 'Pratyumna' having less than 1 week dormancy period, a genotype of the cluster XVII with which they have a maximum genetic divergence of 51.4 and may serve as parents in the development of mapping populations for the identification of QTLs/genes for shattering and dormancy traits. [ABSTRACT FROM AUTHOR]

Polished rice is one of the commonly consumed staple foods across the world. However, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising recombinant inbred lines (RILs) for grain Zn and single plant yield, 190 RILs developed from PR116 and Ranbir Basmati were evaluated in two environments (E1 and E2). A subset of 44 contrasting RILs for grain Zn was screened in another two environments (E3 and E4). Phenotypic data was collected for 10 traits, viz., days to 50% flowering, plant height, panicle length, number of tillers, single plant yield (SPY), test weight, Fe and Zn in brown (IBR, ZBR), and polished rice (IPR, ZPR). Stepwise regression analysis of trait data in 190 RILs and a subset of 44 RILs revealed the interdependence of ZPR, ZBR, IPR, and IBR and the negative association of grain Zn with single plant yield. Based on the additive main effect and multiplicative interaction (AMMI) and genotype and genotype × environment interaction (GGE) analyses of the subset of 44 RILs across four environments (E1–E4), six promising RILs were identified for ZPR with >28 ppm. Mapping of 190 RILs with 102 simple sequence repeats (SSRs) resulted in 13 QTLs for best linear unbiased estimates (BLUEs) of traits including advantage over check (AOC). Using genotype-based sequencing (GBS), the subset of 44 RILs was mapped with 1035 single-nucleotide polymorphisms (SNPs) and 21 QTLs were identified. More than 100 epistatic interactions were observed. A major QTL qZPR.1.1 (PV 37.84%) and another QTL qZPR.11.1 (PV 15.47%) were identified for grain Zn in polished rice. A common major QTL (qZBR.2.1 and qZPR.2.1) was also identified on chromosome 2 for grain Zn content across SSR and SNP maps. Two potential candidate genes related to transporters were identified based on network analyses in the genomic regions of QTL < 3 Mb. The RILs identified for grain Zn and SPY were nominated for national evaluation as under rice biofortification, and two QTLs identified based on BLUEs could be used in the rice biofortification breeding programs. [ABSTRACT FROM AUTHOR]

To improve grain yield under direct seeded and aerobic conditions, weed competitive ability of a rice genotype is a key desirable trait. Hence, understanding and dissecting weed competitive associated traits at both morphological and molecular level is important in developing weed competitive varieties. In the present investigation, the QTLs associated with weed competitive traits were identified in BC1F2:3 population derived from weed competitive accession of O. glaberrima (IRGC105187) and O. sativa cultivar IR64. The mapping population consisting of 144 segregating lines were phenotyped for 33 weed competitive associated traits under direct seeded condition. Genetic analysis of weed competitive traits carried out in BC1F2:3 population showed significant variation for the weed competitive traits and predominance of additive gene action. The population was genotyped with 81 genome wide SSR markers and a linkage map covering 1423 cM was constructed. Composite interval mapping analysis identified 72 QTLs linked to 33 weed competitive traits which were spread on the 11 chromosomes. Among 72 QTLs, 59 were found to be major QTLs (> 10% PVE). Of the 59 major QTLs, 38 had favourable allele contributed from the O. glaberrima parent. We also observed nine QTL hotspots for weed competitive traits (qWCA2a, qWCA2b, qWCA2c, qWCA3, qWCA5, qWCA7, qWCA8, qWCA9, and qWCA10) wherein several QTLs co-localised. Our study demonstrates O. glaberrima species as potential source for improvement for weed competitive traits in rice and identified QTLs hotspots associated with weed competitive traits. [ABSTRACT FROM AUTHOR]

Polished rice is widely consumed staple food across the globe, however, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising genotypes for grain Zn, a total of 40 genotypes consisting 20 rice landraces, and 20 released high yielding rice varieties were evaluated in three environments (wet seasons 2014, 2015 and 2016) for nine traits including days to 50% flowering (DFF), plant height (PH), panicle length (PL), total number of tillers (TNT), single plant yield (SPY), Fe and Zn in brown (IBR, ZBR) and polished rice (IPR, ZPR). Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype × Environment Interaction (GGE) analyses identified genotypes G22 (Edavankudi Pokkali), G17 (Taraori Basmati), G27 (Chittimuthyalu) and G26 (Kalanamak) stable for ZPR and G8 (Savitri) stable for SPY across three environments. Significant negative correlation between yield and grain Zn was reaffirmed. Regression analysis indicated the contribution of traits toward ZPR and SPY and also desirable level of grain Zn in brown rice. A total of 39,137 polymorphic single nucleotide polymorphisms (SNPs) were obtained through double digest restriction site associated DNA (dd-RAD) sequencing of 40 genotypes. Association analyses with nine phenotypic traits revealed 188 stable SNPs with six traits across three environments. ZPR was associated with SNPs located in three putative candidate genes (LOC_Os03g47980, LOC_Os07g47950 and LOC_Os07g48050) on chromosomes 3 and 7. The genomic region of chromosome 7 co localized with reported genomic regions (rMQTL7.1) and OsNAS3 candidate gene. SPY was found to be associated with 12 stable SNPs located in 11 putative candidate genes on chromosome 1, 6, and 12. Characterization of rice landraces and varieties in terms of stability for their grain Zn and yield identified promising donors and recipients along with genomic regions in the present study to be deployed rice Zn biofortification breeding program. [ABSTRACT FROM AUTHOR]

A robust forecast of rice yields is of great importance for medium-to-long-term planning and decision-making in cereal production, from regional to national level. Incorporation of spatially correlated adjacent effects in forecasting models in general, results in accurate forecast. The Space Time Autoregressive Moving Average (STARMA) is the most popular class of model in linear spatiotemporal time series modelling. However, STARMA cannot process nonlinear spatiotemporal relationships in datasets. Alternately, Time Delay Neural Network (TDNN) is a most popular machine learning algorithm to model the nonlinear pattern in data. To overcome these limitations, two-stage STARMA approach was developed to predict rice yield in some of the most intensive national rice agroecosystems in India. The Mean Absolute Percentage Errors value of proposed STARMA-II approach is lower compared to Autoregressive Moving Average (ARIMA) and STARMA model in all examined districts, while the Diebold-Mariano test confirmed that STARMA-II model is significantly different from classical approaches. The proposed STARMA-II approach is promising alternative to classical linear and nonlinear spatiotemporal time series models for estimating mixed linear and nonlinear patterns and can be advanced tool for mid-to-long-term sustainable planning and management of crop yields and patterns in agroecosystems, i.e., food supply and demand from local to regional levels. [ABSTRACT FROM AUTHOR]

• Brown Planthopper is a serious threat to rice crop, posing a significant risk to food security. • To combat the damage, molecular breeding stands as an efficient approach by utilizing resistance genes. • Accordingly, a sophisticated marker assisted breeding technique was employed with SSRs and SNPs to introduce BPH genes from M229 and 10–3 donors into susceptible Telangana Sona. • Five backcross lines (BC 1 (a)−14, BC 1 (a)−19, BC 1 (b)−2, BC 1 (b)−4, BC 1 (b)−5) from both the crosses were identified as potential materials, displaying grain characteristics similar to Telangana Sona. Brown Planthopper (BPH) is one of the most destructive insect pests of rice that threatens food security. Molecular breeding through the use of resistance genes per se would be an economic and efficient way to combat the damage caused by BPH. Telangana Sona (TS) is an elite, popular and a high yielding rice variety susceptible to the infestation of BPH causing severe yield losses. In the current investigation, a marker-assisted backcross breeding approach using gene-specific Simple Sequence Repeats (SSRs) and designed Single Nucleotide Polymorphisms (SNPs) was employed to incorporate BPH resistance genes from the donor lines, M229 and 10–3 into TS. Foreground selection using gene-specific SSRs pinned down one plant (BC 1 (a)-19) from TS//TS/M229 cross with qBph-3–1 and Bph33(t) genes/QTLs, while, six plants of TS//TS/10–3 cross had Bph33(t) gene. Validation of BC 1 F 1 plants with designed SNPs altogether identified three (BC 1 (a)-14, BC 1 (a)-18, BC 1 (a)-19) from TS//TS/M229 and three lines (BC 1 (b)-2, BC 1 (b)-4, BC 1 (b)-5) from TS//TS/10–3 cross positive for snpOS00915, snpOS00922 and snpOS00923. All these lines were also found to be phenotypically resistant to BPH as screened using a modified mass tiller screening method. Altogether, foreground selection coupled with stringent phenotypic selection and agro-morphological evaluation led to the identification of two backcross lines (BC 1 (a)-14 and BC 1 (a)-19) from TS//TS/M229 and three (BC 1 (b)-2, BC 1 (b)-4, BC 1 (b)-5) from TS//TS/10–3 that had grain type characteristics similar to TS that can be potentially used as breeding material for further backcrossing and advancing for near isogenic lines development. The study demonstrates the potential efficacy of marker-assisted selection deployed with both SSRs and SNPs that can be employed in breeding for BPH-resistant varieties. [ABSTRACT FROM AUTHOR]

The brown planthopper (Nilaparvata lugens (Stål) is a major insect pest that is primarily present in Asia causing a significant impact on rice crop. Seventy-three rice genotypes were evaluated for molecular diversity based on known BPH resistance loci. A total number of 108 alleles were detected by 39 polymorphic markers with an average of 2.37 alleles per locus. The allele frequency which is useful in estimating the frequency of alleles, ranged from 0.054 to 0.9726, while the expected heterozygosity varied between 0.054 (RM494) and 0.688 (RM231) with an average of 0.431.The Polymorphic Information Content (PIC) values provided an estimation of the marker’s discriminating power by ranged from 0.066 (RM496) to 0.621 (RM231) suggesting moderate level of polymorphism for the selected BPH specific SSR markers among the germplasm lines. Accounting the major allele frequency, heterozygosity and PIC content, the marker RM231 associated with QBph3.1 and regarded as the most informative one along with RM19291, RM335, RM469, RM518, RM8213, RM228, RH078 and RM589 for dissecting the molecular diversity of germplasm lines with respect to BPH resistance. Based on the marker data, the genotypes were classified into seven clusters that distinguished the lines clustering as resistant and susceptible separately. The information about the genetic diversity of these lines will be extremely useful for proper selection of parents related to BPH reaction, especially for gene mapping and for marker assisted selection.

Identification and purification of the landrace Chittimuthyalu using stability and molecular heterozygosity can be useful for rice diversity. The present study reports the characterization of 12 genotypic variants of Chittimuthyalu in terms of (i) variation and correlation among agromorphological, grain quality and nutrient traits, viz., Zn and Fe; (ii) stability across years; and (iii) characterization and heterozygosity. A total of twelve genotypic variants were identified based on field-level agromorphological observations in the Chittimuthyalu landrace. For identification of a stable genotypic variant for grain Zn, genotype by environment (G × E) interaction was analyzed across three years using additive main effects and multiplicative interaction (AMMI) model and genotype main effects plus G × E (GGE) model for multienvironment data analysis along with principal component analysis (PCA). Correspondingly, twenty-five high polymorphism information content (PIC) RM markers were used for the identification of molecular heterozygosity in landrace. Stepwise regression analysis of phenotype revealed the interdependence of zinc in polished rice (ZPR), iron in polished rice (IPR), and single plant yield (SPY) and the positive association of grain Zn with IPR and SPY. Based on GGE and AMMI analyses of the variants, MCM3 was found to be stable across the environments for ZPR. Out of 46% polymorphic RM markers, seven markers (RM10149, RM13347, RM21749, RM13263, RM10361, RM12276 and RM474) were heterozygous. Heterozygous alleles were observed in eight variants (MCM2, MCM3, MCM5, MCM6 MCM7, MCM8, MCM10 and MCM12). The polymorphic information content (PIC) of the markers ranged from 0.58 to 0.88, with an average of 0.64. The percentage of the most common allele frequencies ranged from 4.2 to 95.8 across the markers. RM13347 showed nine marker trait associations with P ≤ 0.05 and R2 ranging from 2.3% to 14.3% with a mean of 7.74%. The present study has revealed the inherent heterogeneity in landraces in terms of their agromorphological, yield-related and nutritional quality traits. A promising genetic stock (MCM3) was identified as a donor for high grain ZPR and was registered as genetic stock. The identified genetic stock is being shared with breeders in the breeding programme and farmers for the multiplication of high grain Zn rice. ● The research has highlighted the heterogeneity in the landraces grown by farmers. ● In a single landrace "Chittimuthyalu", 12 genotypic variants were identified. ● Molecular characterization has shown the variability by heterozygous alleles. ● The purification of landraces before deployment in rice breeding is underscored. [ABSTRACT FROM AUTHOR]