High-yielding Rice Research Articles

Synthetic photorespiratory bypass improves rice productivity by enhancing photosynthesis and nitrogen uptake.

Photorespiration, often considered as a wasteful process, is a key target for bioengineering to improve crop yields. Several photorespiratory bypasses have been designed to efficiently metabolize 2-phosphoglycolate and increase the CO2 concentration in chloroplasts, thereby reducing photorespiration. However, the suppression of primary nitrate assimilation remains an issue when photorespiration is inhibited. In this study, we designed a carbon and nitrogen metabolism-coupled photorespiratory bypass, termed the GCBG bypass, in rice (Oryza sativa) chloroplasts. Our results demonstrated efficient assembly and expression of the GCBG bypass in rice chloroplasts, which affected the levels of typical metabolites and their derivatives of natural photorespiration and enhanced the photosynthetic efficiency. Metabolomic analyses revealed that oxaloacetate, produced from glycolate in chloroplasts, positively impacted amino acid synthesis, energy metabolism, and sugar synthesis. The engineered GCBG plants showed an average yield increase of 19.0% (17.8-20.2%) compared to wild-type plants under natural growth conditions, alongside improved nitrogen uptake, which compensated for 44.1% of yield losses under nitrogen-limited conditions. In summary, the GCBG bypass substantially improved the photosynthetic efficiency, biomass and yield in rice by integrating carbon and nitrogen metabolism. This study introduces a strategy for engineering high-yielding rice or other crops with improved photosynthetic efficiency and nitrogen uptake.

Unlocking Nutraceutical Potential: Metabolomic Analysis Reveals Therapeutic Compounds in Rice

Background Rice varieties enriched with potential bioactive compounds are poised to make a significant contribution to global health. It is anticipated that edible medications made from rice seeds will lead to novel therapeutics. Purpose High-yielding popular pigmented and nonpigmented rice varieties were selected for in-depth analysis of bioactive contents. Nutraceutical potential of high-yielding rice varieties often goes underexplored compared to low-yielding specialty rice varieties. This study addresses the gap by metabolomic profiling of popular rice varieties to uncover bioactive compounds with significant pharmaceutical and nutritional benefits. Methods Untargeted metabolomic profiling of the brown rice of pigmented and nonpigmented varieties was conducted by Orbitrap-high-resolution liquid chromatography and mass spectrometry, and primary and secondary metabolites were identified and annotated. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging (RS) assay was carried out to identify the variety with superior antioxidant activity. Correlation analysis by using Metaboanalyst software identified major metabolites with RS potential. Over-representation analysis was performed for the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and major pathways were identified for metabolites with nutraceutical potential in pigmented rice. Results Major metabolites with antioxidant, anti-inflammatory, and anticarcinogenic properties were identified from rice varieties. Bioactive compounds detected from brown rice included choline, didodecyl-3,3-thiodipropionate, conjugated linoleic acid, oleic acid, 13( S)-HOTrE, monoolein, nicotinic acid, pantothenic acid, isoquinoline, trigonelline, corymboside, ferulic acid, and 2,4-quinolinediol. The DPPH RS assay revealed superior antioxidant activity in the pigmented rice, with differential metabolites from the pathways of phenylpropanoid biosynthesis, arginine and proline metabolism, and biosynthesis of unsaturated fatty acids showing a significant correlation ( p < .01) with RS potential. Conclusion Catechin, (–)-epicatechin, (±)12(13)-DiHOME, 4-guanidinobutyric acid, and 5-methoxysalicylic acid are key metabolites that emphasize the antioxidant potential of red-colored rice as a functional food with significant health benefits. The study highlights the therapeutic promise of pigmented whole-grain rice.

DYNAMIC ASSESSMENT OF GROWTH, YIELD, AND QUALITY TRAITS IN HIGH-YIELDING RICE VARIETIES UNDER TIDAL AGROECOSYSTEMS

Introduction: Swamplands, including tidal and freshwater areas, offer significant potential for agricultural expansion in Indonesia, particularly for rice cultivation. However, challenges such as low productivity and quality hinder the full realization of this potential. While new high-yielding varieties (NHVs) like Inpara-3, Inpari-33, Inpari-47, Inpari-48, and Logawa have been developed to address these challenges, factors like pre-harvest conditions (NHV selection) and post-harvest processes (drying, milling, storage) significantly impact rice quality. Objective: This study aims to evaluate the performance of several new high-yielding varieties of rice in tidal lands based on growth, yield, and grain quality. Method: The study collected data on growth, yield, and quality parameters. Statistical analysis (ANOVA and Duncan's Multiple Range Test) was used to compare treatment means and identify correlations between variables. Results and Discussion: The study revealed that new high-yielding rice varieties (NHVs) demonstrated significant adaptability to tidal agroecosystems, with notable effects on plant height, panicle length, 1,000-grain weight, harvest age, and dry grain yield. Inpari-33, Logawa, and Inpari-47 showed superior performance, yielding 5.48 t/ha, 5.33 t/ha, and 5.29 t/ha, respectively, while also exhibiting good growth characteristics. All tested varieties fell into the third category of medium-quality rice due to a high percentage of broken grains, influenced by genetic traits and post-harvest processing. Research Implications: The study identifies Inpari-33, Logawa, and Inpari-47 as promising NHVs for tidal rice cultivation. By highlighting the potential of these varieties in challenging environments, the research contributes to improving rice production and food security in marginal areas.

Direct seeding rice: A solution to improve establishment of rice under unpredictable climate condition

Swampy is identified as a potential areas to boost national rice production, however, Fe exposure and lack of labour are some of main obstacles to get high yield of rice. Specific land preparation, puddling and levelling without exposing active Fe is required to maintain high yield. A field experiment aims to examine the effectiveness of perfect land levelling to increase yield under direct seeding method. The trial was arranged in large areas, each treatment was set in 0.5 ha, with 5 replications in 2021 dry-season in Central Kalimantan. The treatments were combination of land preparation and establishment system with direct seeding rice (DSR) or transplanting (TRP). The results showed that land levelling used the farming bulldozer improved the number of productive tillers lead to higher grain yield compare to that of hand tractor. Highest grain yield was produced in FB-TRP (land preparation done by Farming Bulldozer in combination with transplanting) at average 3326 kg/ha, followed by HT-TRP (Hand Tractor-Transplanting) at 3064 kg/ha. Whereas FB-DSR yielded at 2146 and FB-TRP at 1778 kg/ha. Good land levelling had greater effect on the seed germination and increase the number of tiller by 17.6% under direct seeding with farming bulldozer compare to hand tractor.

Yield performance of high-yield rice varieties in swamp lands of the West Kalimantan border area

The planting season has a significant impact on the rice yield in tidal type C. Farmers in Matang Danau Village, Paloh Sub-District, Sambas District, West Kalimantan Province, currently cultivate rice once a year during the rainy season (RS), using the Cilosari, which has a low yield of 2.35 t ha-1. To increase the cropping index (CI), water pumping can be utilized during the dry season (DS), along with the use of high-yield varieties. This research aimed to evaluate the yield performance of various high-yield rice varieties in the swamp lands of the West Kalimantan border area. Conducted during the DS (March to July 2018) and RS (October 2018 to February 2019), the research used a randomized complete block design with three replications. The varieties tested included Inpara 1, 2, 3, 4, 6, 8, 9, Inpari 32, and control varieties Margasari and Cilosari. Results indicated significant yield differences among the varieties under swamp conditions, with Inpara 1 achieving the highest yield of 6.6 t ha-1, while other varieties ranged from 3.98 to 5.90 t ha-1. Inpara 1 showed the most notable yield improvement compared to Margasari and Cilosari. Additionally, yields during the RS were 89.4% higher than those during the DS.

High-Yielding Rice Production through Ratooning in Southwestern Japan

High-Yielding Rice Production through Ratooning in Southwestern Japan

Trait Association and Genetic Variability Study in Rice MAGIC Lines for Yield Related Traits

The study was aimed to assess genetic variability and associations between grain yield and morphological traits in 50 multi-parent advanced generation intercross (MAGIC) lines generated by single seed descent utilizing eight diverse parents (to impart tolerance to biotic and abiotic stresses) were utilized in the study along with eight checks at Zonal agricultural and horticultural research station, Navile, Shivamogga during kharif 2022. Improvement in grain yield, a quantitative trait is one of the key objective of plant breeders which depends upon the magnitude of genetic variability existing in the genetic material utilized in the breeding programme. The analysis of variance revealed the presence of significant differences were found among lines for all traits. Moderate to high genotypic and phenotypic variation, heritability and genetic advance were recorded for plant height, tillers per plant, filled grains per panicle, test weight and grain yield. Correlation analysis revealed positive associations between grain yield and tillers per plant, panicle length, filled grains per panicle, panicle fertility and test weight. These findings emphasize the importance of indirect selection for these traits to improve grain yield in rice. The results suggest that breeders can utilize these traits as selection criteria to enhance grain yield, ultimately contributing to rice yield improvement programs. Our study provides valuable insights for rice breeders to develop high-yielding rice varieties with improved tolerance to biotic and abiotic stresses.

Effects of potassium fertilization on grain yield, taste quality, and starch characteristics of rice (Oryza sativa L.) grain.

There is limited information on the effect of potassium (K) on the taste quality of rice. Field experiments with five K fertilizer application rates (0, 60, 120, 180, and 240 kg K2O ha-1) were conducted in 2019 and 2020 using two cultivars (Xiadao No. 1 and Shenliangyou 5814) to study the effects of K fertilization on grain yield, taste quality, starch components, and protein components in grains. Compared with a no-potassium treatment (K0), K fertilization increased the grain yield significantly: by 57.29% for Xiadao No. 1 and 33.51% for Shenliangyou 5814. It did this mainly by increasing the number of rice spikelets per panicle and improving the seed-setting rate. K fertilizationimproved the taste value by 12.64% for Xiadao No. 1 and 10.83% for Shenliangyou 5814. Starch components, protein components, and viscosity parameters were also influenced by K fertilization. With increased K application, the amylose content and the ratio of amylose content to amylopectin content tended to increase. K fertilization increased the peak viscosity and cool paste viscosity, while decreasing the prolamin content and pasting temperature. Principal component analysis highlighted the importance of amylose content and the ratio of amylose content to amylopectin content in determining taste value, texture, and appearance. Applying 180 kg K2O ha-1 of K fertilizer ensured high rice yields and taste quality, providing a basis for the production of high-yield and high-quality rice. © 2024 Society of Chemical Industry.

The Impact of Split Nitrogen Fertilizer Applications on the Productivity and Nitrogen Use Efficiency of Rice

The application of nitrogenous fertilizer in reduced (“split”) doses of its total is suggested as a means to increase nitrogen use efficiency and rice productivity whilst reducing its environmental impact. Field trials conducted in 2022 and 2023 aimed to assess the impact of split nitrogen fertilizer applications on the productivity and nitrogen use efficiency of rice. This experiment included three nitrogen treatments (N1: control (no nitrogen); N2: 50% basal + 25% at tillering stage + 25% at panicle initiation stage (conventional method); N3: 33.33% basal + 33.33% at tillering stage + 33.33% at panicle initiation stage (equal split of nitrogen)) and four high-yielding rice varieties (V1: Super Gold 2019; V2: Super Basmati 2019; V3: Noor Basmati 2017; V4: Kissan Basmati 2016). The results indicated that the N3 treatment, with an equal split of nitrogen, combined with the V4 variety (Kissan Basmati 2016) produced the most favorable outcomes. The results indicated that the N3 treatment, particularly when applied to Kissan Basmati (V4), produced, statistically, the highest leaf area index (32.98%, 29.59%), 1000-grain weight (32.84%, 46.97%), grain yield (30.02%, 38.09%), agronomic nitrogen use efficiency (9.21%, 11.63%), and partial factor productivity (29.98%, 38.11%) compared to the control for the study periods of 2022 and 2023, respectively. Moreover, the grain yield demonstrated a strong positive correlation with growth traits and other yield components, except for plant height. The results showed that the application of three equal nitrogen doses significantly increases rice production, and therefore, in this yield context, improves nitrogen use efficiency.

Leaf senescence characteristics and economic benefits of rice under alternate wetting and drying irrigation and blended use of polymer-coated and common urea.

Water-saving irrigation and the mixed application of controlled-release nitrogen fertilizer (CRNF) and common urea (CU; with a higher nitrogen release rate) have shown promise in improving rice yield with high resource use efficiency. However, the physiological mechanism underlying this effect remains largely unknown. This study involved a field experiment on rice in Jingzhou City, Central China, in 2020 and 2021. Two irrigation regimes were employed [alternate wetting and drying irrigation (AWD) and conventional flood irrigation (CI)], with three nitrogen (N) compounding modes [00% CU (N1), 60% CRNF + 40% CU (N2), and 100% CRNF (N3)] with an equal N rate of 240kg ha-1. The results indicated a significant interactive effect of watering regimes and N compounding modes on net photosynthetic rate (P n), leaf area index (LAI), and SPAD values; activities of superoxide dismutase (SOD), peroxidases (POD), catalase (CAT), glutamine synthetase (GS), glutamine 2-oxoglutarate amidotransferase (GOGAT), and nitrate reductase (NR); and the contents of malondialdehyde (MDA) and soluble protein in rice leaves. Compared with N1, N2 and N3 increased the P n, LAI, and SPAD values; activities of SOD, POD, CAT, NR, GS, and GOGAT; and soluble protein content but decreased MDA content in the post-growth (heading and maturity) stages by 8.7%-31.2% under the two irrigation regimes. Compared to CI (traditional irrigation), AWD had higher P n, LAI, and SPAD values; activities of SOD, POD, CAT, NR, GS, and GOGAT; and soluble protein content (increased by 12.1%-38.0%, and lower MDA content (reduced by 13.1%-27.6%) irrespective of N compounding modes. This suggested that AWD combined with N2 and N3 could delay the leaf senescence of rice, thus achieving a larger grain yield. Moreover, AWD significantly decreased water costs (irrigation amount) and labor costs (irrigation frequency), thus increasing total income. N2 decreased fertilizer costs with a higher or comparable total income compared with N3. Therefore, the AWDN2 treatment achieved the highest net income (13,907.1 CNY ha-1 in 2020 and 14,085.7 CNY ha-1 in 2021). AWD interacted with 60% CRNF + 40% (N2) to delay leaf senescence by improving photosynthesis, antioxidant defense system, osmoregulation, and N assimilation, contributing to high grain yield and net income in rice.

Strong Source and Fluent Flow May Increase Grain Weight and Yield in Water‐Saving and Drought‐Resistance Rice: A 5‐Year Field Study

ABSTRACTWater‐saving and drought‐resistance rice (WDR) is a new type of cultivated rice, which not only has the characteristics of high yield and quality of rice, but also has the properties of water‐saving and drought‐resistance of upland rice. However, the source, flow and sink basis of its high yield were still unclear. It was of great significance for the breeding of high‐yielding WDR varieties and cultivation regulation to clarify the characteristics of the source, flow, and sink of WDR yield formation and its regulation effects. In this study, WDR varieties (more than 20) with three groups of different grain weight types: small grain weight type (SGWT, grain weight < 22.5 mg), medium grain weight type (MGWT, 22.5 mg < grain weight < 25 mg) and large grain weight type (LGWT, grain weight > 25 mg), were selected as materials. The contribution of grain weight to the yield, the changes of source (flag leaf length and width), flow (stem length and diameter), and sink (grain length and width) and the regulation effects of grain fertiliser application rate (GFAR) on grain weight in WDR were studied through a 5‐year field cultivation. The results showed that (1) the average yield of LGWT was significantly higher than that of SGWT and MGWT varieties, with an increase of 5.23%–9.88% and 2.06%–3.08%, respectively. Larger grain weight was the primary feature of high‐yielding WDR varieties. (2) There was a significant positive correlation between grain weight and, flag leaf width (source) and stem diameter (flow) at the middle grain filling stage (25 days after heading) (r = 0.467*–0.688**). (3) Compared with no GFAR treatment, the applying GFAR treatments (GFAR at 25 and 50 kg ha−1) increased the stem diameter, flag leaf width, grain weight and yield of Huhan1505 (SGWT), Huhan1517 (MGWT) and Hanyou756 (LGWT) to varying degrees, and the increase of SGWT was greater. Larger flag leaf width (strong source) and wider stem diameter (fluent flow) were material foundation for high yield of WDR. Promoting source strength and smooth flow at the middle grain filling stage was conducive to promoting the increase of grain weight and yield of WDR.

Support Vector Machine-Radial Basis Function Kernel and K-Nearest Neighbor Differences for Classification Superior Varieties of Rice in Indonesia

Rice is the primary food source for the Indonesian population, making it a priority commodity in Indonesia. Rice production plays a significant role in Indonesia's economic development, with high-yield rice varieties being crucial for enhancing national rice output. Ensuring food security requires the selection of superior rice varieties with optimal quality. This study evaluates various high-yield rice varieties, including INPARA, INPARI, INPAGO, and HIPA, based on characteristic data collected in 2023. Machine learning algorithms, increasingly central to data analysis, were applied, leveraging labeled data suitable for supervised learning methods. During the pre-processing stage, it was determined that the data did not meet the linearity assumption. Thus the Support Vector Machine (SVM) algorithm was modified with the Radial Basis Function (RBF) kernel to better handle non-linear data. Additionally, the K-Nearest Neighbor (KNN) algorithm, a traditional method, was used for comparison. The results indicate that SVM with the RBF kernel achieved faster processing times and the accuracy value reaches 96%, nearly 10% higher than the KNN algorithm.

Unraveling the genetic diversity, population structure, and stability for yield-related traits of rice genotypes in mid-hills of northeastern India.

The cultivation of nearly 10,000 indigenous rice landraces in the North-Eastern Hill (NEH) region by various ethnic groups creates opportunities for the utilization of unique landraces through systematic evaluation of genetic variability. In the present study, a set of 102 rice landraces were assessed based on morphological and SSR markers, and five checks in augmented design vis-à-vis high-yielding rice genotypes with stable performance were identified. The presence of high estimates of heritability, genotypic coefficient of variation, and genetic advance over mean indicated the predominance of additive gene action, which necessitated the effectiveness of selection in augmenting productivity. A total of 83.73% of the total variation was accounted by the first five principal components. A total of 132 alleles were detected, with an average of 3 alleles per locus. The PIC values ranged from 0.01 to 0.70, with an average of 0.40. Based on FST value (5.1%), significant differences between the genotypes of Arunachal Pradesh and Sikkim were observed. The percentage of variation among the population, among individuals within the population, and within individuals was 5.14, 75.66, and 19.2%, respectively. Both Nei's genetic distance and model-based clustering have differentiated the genotypes into five distinct clusters. Principal coordinate analysis illustrated that the genotypes of Manipur were scattered in all quadrants, showing that they are highly diverse, while the genotypes of Nagaland, Sikkim, and Meghalaya were found together, which represent the chance of mixing of the population at a certain point in time. Markers, namely RM 474, OSR 13, RM 413, and RM 259, were found to be associated with key traits for increasing yielding ability of plant. In a stability evaluation based on AMMI analysis and multi-trait genotype-ideoptype distance matrix (MGIDI), genotypes, namely Jyotrirmayie, RCPL 1-411, Tsamum firri, Ching Phouren, Rato Bhan Joha, MN-47, and Tara bali, were selected with higher yield potential.

Positive and Negative Effects of Inter‐Annual Climate Variability on Rice (Oryza sativa L.) Crop in Agro‐Climatic Zones of Punjab

ABSTRACTGlobally, climate changes have significantly shifted the phenological phases and stages of rice, altered the duration of the growing season and negatively affected rice productivity due to flooding and drought. However, in the present study, the positive and negative impacts of inter‐annual climate variability on rice crops during phenological stages in agro‐climatic zones of Punjab for the period from 1989 to 2018. Initially, first difference approach was applied to minimise the impact of technological factors. Then, skewness and kurtosis tests were used to check the normalisation of the data. The standardisation method was used to normalise the data. Pearson correlation was used to determine the significant effects of climate variables on rice yield. The residuals were formed to confirm the effects of inter‐annual climate variability on rice yield in the phenological phases. The analysis revealed that a high variability of rice yields was investigated in the western region compared to the southern and western regions. The results showed a negative impact of heavy rainfall (flooding) on the years with low yields (2010, 2013 and 2016) in the Central region. Similarly, the years with low rice yields (1996, 2010, 2013 and 2014) in the Southern region were negatively affected by flooding at the time of sowing. A positive effect of rainfall was observed in the years with high rice yields (1995, 2002, 2009 and 2018) in the Western region. In contrast, the low‐yielding years 1994, 2003 and 2010 were negatively affected by flooding in the same years during the tillering stage. A high interannual maximum temperature variability was analysed in the Southern > Western > Central regions, leading to yield losses due to biotic stress during tillering and stem elongation stages. This is due to the immense reason of drought stress. The minimum temperature negatively affects the low‐yield years (2001, 2008, 2013 and 2016) in the central zone and the low‐yield years (2014, 2015 and 2016) in the southern zone during the reproductive stage. This research will help to develop new rice varieties that are more productive at high temperatures and require less water, leading to sustainable development in arid and semi‐arid regions.

Two splicing variants of amino acid transporter-like 4 (OsATL4) negatively regulate rice tillering and yield by mediating the transport of amino acids

Amino acids are the primary form of nitrogen utilization in higher plants, mainly transported by amino acid transporters. In this study, we analyzed the natural variation of amino acid transporter-like 4 (OsATL4) in rice germplasm resources, identified its spatiotemporal expression characteristics, determined its substrate transport, and validated its function using transgenic plants. We found that the promoter sequence of OsATL4 varied across 498 rice varieties. The expression level of OsATL4 was higher in japonica rice, which was negatively correlated with tiller number and grain yield. OsATL4 was highly expressed in the basal part, leaf sheath, stem, and young panicle, with its two splicing variants localized to the cell membrane. OsATL4a (the long splicing variant) had a high affinity for transporting Ser, Leu, Phe, and Thr, while OsATL4b (the short splicing variant) had a high affinity for transporting Ser, Leu, and Phe. Blocking OsATL4 promoted axillary bud outgrowth, rice tillering, and grain yield, whereas overexpression lines exhibited the opposite phenotype. Exogenous application of low concentrations of Ser promoted axillary bud outgrowth in overexpression lines, while high concentrations of Ser inhibited it. Conversely, the mutant lines showed the opposite response. Altered expression of OsATL4 might affect the expression of genes in nitrogen, auxin, and cytokinin pathways. We propose that two splicing variants of OsATL4 negatively regulate rice tillering and yield by mediating the transport of amino acids, making it a significant target for high-yield rice breeding.

Seasonal methane emissions and agronomic performance of Indonesia’s high-yielding rice cultivars on the north coastal rice fields of Central Java, Indonesia

Seasonal methane emissions and agronomic performance of Indonesia’s high-yielding rice cultivars on the north coastal rice fields of Central Java, Indonesia

<b>Performance of Candidate Varieties of Basmati Rice in Uniform Yield Trials</b>

The primary focus of rice breeding research is now on developing high-yielding rice varieties with early maturing and physio-chemical features, such as improved cooking quality, aroma, and extra-long grain. This shift in focus is driven by the growing global demand for high-quality rice. Using traditional breeding methods to trait pyramid these extremely important traits while maintaining yield and quality is a challenging task. Good grain quality(aromatic), fertilizer responsiveness, and high-yielding varieties can help the farmers in Pakistan to increase their revenue despite global population growth and changing international market patterns. At the Rice Research Institute, Kala Shah Kaku (RRI KSK), new, improved, high-yielding, extra-long grain lines with the qualities of early maturity, small stature, and good cooking with aroma are being developed through traditional breeding methods. The present study aimed to assess the genetic variability of these lines in terms of paddy yield and to discover superior high-yielding cultivars suitable for widespread cultivation. There were notable variations in paddy yield among the different entries in the pooled analysis. The highest average paddy yield (5010 Kg/ha) was seen in entry 10640-10-1-1-1, followed by entry 10684-3-1-2 (4990 Kg/ha) and PK 10434-6-2-1 (4550 Kg/ha) and suggested for general cultivation based on their mean paddy yield. A strong positive correlation was seen between the grain thickness grading of over 2.2 mm and the number of panicles per plant. The overall quality of the Uniform Yield Trials of Fine rice samples can be reported as excellent for PK 10306-15-5, PK PB-8 and PK 10678-2-1-1 over check Basmati-515. There will be a simultaneous increase in grain yield with improvements in these qualities.

GW3, encoding a member of the P450 subfamily, controls grain width by regulating the GA4 content in spikelets of rice (Oryza sativa L.).

A stable QTL, GW3, controlling grain width was identified in two populations. Its causal gene LOC_Os03g04680 was verified by gene-based haplotype analysis, expression analysis, gene knockout and complementation transgenic tests. Grain width (GW) is one of the key traits affecting grain size and determines grain yield and appearance quality in rice. Mining gene loci and elite alleles controlling GW is necessary. The GW phenotypes of the two populations were investigated in three environments, which showed abundant phenotypic variation. GW3, encoding a P450 subfamily protein, was identified and validated as a causal gene by gene-based haplotype analysis, expression analysis, gene knockout and complementation transgenic tests. The accessions with large GW values had high gene expression levels. In addition, the GW of the accessions with the GG allele was significantly greater than that of the accessions with the AA allele. The Hap 1 and Hap 3 were identified as elite haplotypes, which can increase GW. The expression levels of OsKO1, OsGA3ox1, OsGA20ox1 and OsGA20ox2 in the young panicle of A7444 were significantly greater than those in the young panicle of the mutants, indicating that GW3 may be involved in the gibberellins (GA) biosynthesis pathway to regulate GW. GA4 content detection and electron scanning analysis revealed that GA4 regulates GW by affecting glume cell size. These results provide new insights for studying the genetic mechanism of rice GW and provide a material basis for breeding high-yield rice varieties.

Estimating Total Rice Biomass and Crop Yield at Field Scale Using PlanetScope Imagery Through Hybrid Machine Learning Models

Near real-time crop monitoring has been a challenging due to the lack of high-resolution remote sensing images suitable for agricultural applications. The PlanetScope constellation, comprising approximately 130 Dove satellites, collects images of the entire Earth daily, with a resolution of 3.7 m. The high-resolution images from the PlanetScope satellite, along with vegetation indices, geo-environmental data, and soil and crop parameters, were utilized and analysed using machine learning models to enhance the accuracy of predicting total biomass and rice crop yield at the field scale. The study area, covering nearly 214 sample rice plots, was located in the Tarekswar block of Hooghly, West Bengal, India. Alongside ten vegetation indices and three Principal Component Analysis (PCA) soil nutrient levels, approximately thirty-six factors were analyzed to predict rice total biomass and crop yield using ten machine learning (ML) models, namely Random forest (RF), Extreme Gradient Boosting (XGB), Support Vector Machine (SVM), Bagging Tree (Treebag), Generalized Additive Models (gamSpline), Elastic Net (enet), Ordinary regression with LASSO penalty (rqlasso), Tree Models from Genetic Algorithm (evtree), Bayesian Regularized Neutral Networks (brnn), cubist models, and there hybrid of ensembles. Boruta and multi-collinearity analysis were also conducted for the selected factors to explore their influence levels. The study area exhibited robust rice yields ranging from 5 to 10 t/ha, accompanied by healthy biomass growth. Four ML models ─cubist, random forest, enet, and the hybrid model—showed promising predictions with R2 > 0.88. Most models classified less than 20 ha of the study area as falling into the “very-low suitable class”, showing the region’s suitability for rice cultivation due to its highly fertile alluvial soil. Boruta sensitive analysis revealed that nearly 24 individual factors significantly influenced the final crop yield including, organic carbon (OC), phosphorus (P), electrical conductivity (EC), mechanization level, and the majority of the vegetation indices. A critical analysis carried out through the Map query tool showed that five vegetation indices estimated via PlanetScope displayed strong correlations (exceeding 89%) in identifying areas with high to very high rice yields. The study can serve as a guideline for near-real-time crop monitoring in the near future, using high-resolution PlanetScope images.

High-yield rice with rich nutrition and low toxicity can be obtained under potato-rice cropping system.

Rice is often rotated with dryland crops to produce sufficient foodstuff, as rice is the main food crop of humans. In order to verify whether under the intensive rice-based cropping system, high yield and good quality of rice can be achieved simultaneously to ensure food security. Five long-term paddy-upland rotations - wheat-rice (WR), rapeseed-rice (RR), garlic-rice (GR), broad beans-rice (BR) and potato-rice (PR) - were conducted from 2014 to investigate rice yield, along with the profiling of 24 elements in rice grain. Mg, Zn, Cu, As, Mo and Sb concentrations were highest in the aleurone layer, and Ag and Cd concentrations showed little variation among different parts of the rice grain. Al, Ti, V, Si, Fe and Tl concentrations in the endosperm under GR were higher, while the Se concentration under PR was the highest. Furthermore, the yield of GR and PR were higher than the other three rotations with N supplementation, and the sustainable yield index of PR and WR were larger than 0.8. When we consider the concentration of toxic (As, Cd and Pb) and nutrient elements (Ca, Fe, Zn, Se, Cu and Mg) in the endosperm and grain yields, PR can simultaneously achieve high yield, high nutrition and low toxicity with different nitrogen treatments. Here we provide novel insights regarding the selection of rice-based cropping systems, focused on producing nutritious and safe rice with high grain yield. © 2024 Society of Chemical Industry.