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The nutritional quality of rice is a major concern, along with the need to enhance productivity to feed the continuously growing population. Therefore, there is a requirement to breed high-yielding rice varieties with improved nutritional quality that can help combat malnutrition, a global health issue. Undoubtedly, breeding approaches have played a significant role in increasing rice yield while enhancing its nutritional content. In addition to traditional breeding techniques, other recent approaches, such as genetic engineering, gene editing, omics methods, and agronomic practices, must also be employed to meet the nutritional needs of the current population. In this review, we offered detailed information on the development of nutritionally improved rice varieties through the enhancement of protein content, micro- and macronutrients, vitamins, and oil quality using genetic engineering approaches. We also identified QTLs associated with amino acids, proteins, and micronutrients in rice. Furthermore, omics approaches provide a range of tools and techniques for effectively exploring resources and understanding the molecular mechanisms involved in trait development. Omics branches, including transcriptomics, proteomics, ionomics, and metabolomics, are efficiently utilized for improving rice nutrition. Therefore, by utilizing the information obtained from these techniques and incorporating all of these recent approaches, we can effectively modify the rice genome, directly enhancing the nutritional value of rice varieties. This will help address the challenges of malnutrition in the years to come. [ABSTRACT FROM AUTHOR]

FLO2 is involved in grain development and storage substance synthesis in rice, and therefore can regulate grain size and quality. In this study, we identified 4 new flo2 allelic mutants with nonsense and frameshift mutation in the exon of 6, 10, 11 and 21 and 5 new flo2 allelic mutants with alternative splicing and frameshift mutation at the splicing site of intron 13, 14, 16 and 17. Compared with wild-type rice, the outer endosperm of flo2 mutants was transparent, and the inner endosperm was floury. Different mutation sites and types of FLO2 significantly decreased kernel width, thickness and weight to some extent. The contents of storage protein, starch, amylose and amylopectin showed significant decrease at different levels among 9 flo2 mutants. The expressions of most storage protein synthesis genes and starch synthesis-related genes were significantly down-regulated, and exhibited different ranges of variation among different flo2 mutants. This study could add helpful information for the roles of flo2 alleles in rice quality regulation and provide abundant germplasm resources for rice quality breeding. [ABSTRACT FROM AUTHOR]

• For the first time, we apply the principle of three-line hybrid rice breeding to the field of feature fusion. • We propose a feature fusion method that can automatically learn and dynamically update the weights. • Solve the problems of nonlinearity and high data dimensionality in the field of software defect prediction. Software defect prediction (SDP) plays a crucial role in ensuring the security and quality of software systems. However, it faces challenges posed by high-dimensional features present in software defect datasets and the limited effectiveness of traditional nonlinear dimensionality reduction methods in extracting essential feature information. To address these issues, we propose a novel approach called learnable three-line hybrid feature fusion (LTHFFA), which incorporates the principle of three-line hybrid breeding into feature fusion for the first time. In this method, three distinct dimensionality reduction techniques are initially employed to obtain three separate sets of features. Subsequently, a learnable weight factor feature fusion method is proposed to facilitate automatically learn and dynamically update of feature weights. By integrating the three feature sets based on the principle of three-line hybrid breeding, we derive learnable three-line hybrid fusion features. These features are then utilized in the context of software defect prediction. Experimental results demonstrate the superior performance of LTHFFA compared to nine other dimensionality reduction methods across seventeen publicly available software defect datasets. LTHFFA exhibits the ability to effectively integrate multiple feature sets, reduce feature redundancy, and enhance predictive accuracy. Moreover, statistical analysis using Friedman ranking and Holm's post-hoc test confirms the significant advantage of LTHFFA over alternative dimensionality reduction methods. [ABSTRACT FROM AUTHOR]

Over the past 30 years, super rice played an important role in boosting rice yield. The phenotype of erect panicle (EP) architecture controlled by dense and erect panicle 1 (dep1) is the typical characteristic of super rice, and the phenotype has been used in rice breeding for nearly a century. In this review, the molecular genetic basis of EP phenotype, and mechanism of how dep1 affects rice carbon, nitrogen metabolism and grain quality (grain shape and taste quality) were discussed. In addition, we discussed the possible improvement strategies of rice yield and quality. This review provides a quick overview of the whole process for rice quality formation, as well as suggestions and ideas for future research on rice quality improvement. [ABSTRACT FROM AUTHOR]

Higher-yield and superior-quality rice are the major goals in rice breeding and nitrogen management. Genetic modification combined with optimal nitrogen (N) fertilization is expected to realize it. Modification in transaldolase (TAL) expression alters both the number and pattern of vascular bundles in rice plants, but its interactions with N rate remains unknown. We employed three representative lines with different expression levels of TAL in the same genetic background (Wuyunjing 7, WT), and analyzed their responses in dry matter accumulation (DMA), carbohydrate transport, grain filling, yield, yield components, and grain quality under a wide range of N rate. Increased expression of TAL (OE) promoted rice yield by producing more spikelets per panicle and higher 1000-grain weight, while decreased expression of TAL lowered the seed setting rate and grain weight significantly. Under a fixed N rate, when TAL expression was altered, the direct path coefficients of the seed setting rate and 1000-grain weight to the yield were higher than other yield components, especially at a high N rate. Decreased expression of TAL (RNAi) significantly reduced the starch and non-structural carbohydrates (NSC) contents in the stems, but enhanced the soluble sugar retention, whereas increased expression of TAL enhanced the translocation of NSC. The grain weight at maturity and mean grain-filling rate (mg d−1) increased significantly along with the TAL expression, but their differences among RNAi, WT and OE narrowed at higher N rate. Decreased expression of TAL enhanced the apparent amylose content (ACC) and protein (PC), reduced the starch granule size, and caused a loose starch arrangement and elevated chalkiness, as a consequence, significantly reduced the peak viscosity, hot viscosity, final viscosity, and taste value in a N rate dependent manner. The taste values of OE and WT were similar and the highest value was attained under a moderate N rate. TAL expression plays an important role in the regulation of assimilate supply, grain filling, yield formation, and grain quality. Increased expression of TAL alleviates competition effect among the yield components and enhances the yield potential, especially under moderate to high N rate. Higher TAL expression combined with a moderate N rate improves ECQ. TAL expression and N rate interacts to regulate yield components and quality. This finding provides meaningful knowledge to administering N rate and genetically modifying TAL expression in a rice variety. • Altered TAL gene expression impacts seed setting and grain weight dependent on N-rate. • High TAL level improves grain filling and final weight via more assimilate supply. • Higher TAL under mild N rate improves taste value by amylose and protein contents. [ABSTRACT FROM AUTHOR]

• A novel method for intelligent analysis of rice yield traits was developed based on LED transmission imaging and cloud computing. • A low-cost, non-radiation, and efficient imaging method had been proposed based on 624.4 nm red light, which was able to acquire high-contrast images of filled and unfilled grains. • A robust and accurate rice grain detection model had been developed to identify filled and unfilled rice grains in red-light images, and the specified algorithms had been designed to achieve high accuracy measurement of rice yield traits. • Qt-based local software and web-based application had been designed, which provided novel and convenient tools for rice breeding and genetic analysis. Rice yield traits extraction is necessary for rice breeding and genetic analysis, in which the discrimination of filled and unfilled grain was the bottleneck. The traditional methods including wind separating and water sinking are inefficient, unreliable, and poorly reproducible, meanwhile the machine vision methods based on X-ray and 3D structured imaging have the disadvantages of high cost, ionizing radiation, and poor scalability. To address the above problems, this study has proposed a novel method for intelligent analysis of rice yield traits based on LED transmission imaging and cloud application. The study has found that the red-light LED transmission imaging was able to obtain high-contrast images of filled and unfilled grains and had the advantages of radiation-free, low-cost, and high-efficiency imaging. Using 3,200 rice grain images as the training set, the results showed that the YOLOv5 model outperformed the Faster RCNN, RetinaNet, SSD, and Cascade RCNN models, and its filled and unfilled grain recognition precision was 98.94% and 90.96% on the 800 test sets, while the recall rate was 97.91% and 94.94%. To further improve the recognition accuracy of the YOLOv5 model, five model optimization methods were adopted in the study, including TPH, CBAM, adding a small target detection layer, using Bi-FPN and Multi-NMS. The results proved that the accuracy of unfilled grain recognition had significantly improved, the recognition precision increased by 4.54% to 95.44%, and the recall rate increased by 0.77% to 95.71%. Finally, this study has designed the specified algorithms based on the recognized rectangular box, which could accurately measure filled and unfilled grain numbers, seed setting rate and grain shape parameters. Moreover, the study has designed a local Qt software and a cloud-based website, which can support the simultaneous input of multiple images with high real-time performance and good scalability, providing a practical novel tool for rice breeding and genetic analysis. [ABSTRACT FROM AUTHOR]

The grain chalkiness of rice ( Oryza sativa L.), which determines the rice quality and price, is a major concern in rice breeding. Reactive oxygen species (ROS) plays a critical role in regulating rice endosperm chalkiness. Ascorbic acid (Asc) is a major plant antioxidant, which strictly regulates the levels of ROS. l -galactono-1, 4-lactone dehydrogenase (L-GalLDH, EC 1.3.2.3) is an enzyme that catalyzes the last step of Asc biosynthesis in higher plants. Here we show that the L-GalLDH-suppressed transgenic rice, GI-1 and GI-2, which have constitutively low (between 30% and 50%) leaf and grain Asc content compared with the wild-type (WT), exhibit significantly increased grain chalkiness. Further examination showed that the deficiency of Asc resulted in a higher lipid peroxidation and H 2 O 2 content, accompanied by a lower hydroxyl radical scavenging rate, total antioxidant capacity and photosynthetic ability. In addition, changes of the enzyme activities and gene transcript abundances related to starch synthesis were also observed in GI-1 and GI-2 grains. The results we presented here suggest a close correlation between Asc deficiency and grain chalkiness in the L-GalLDH-suppressed transgenics. Asc deficiency leads to the accumulation of H 2 O 2 , affecting antioxidant capacity and photosynthetic function, changing enzyme activities and gene transcript abundances related to starch synthesis, finally leading to the increased grain chalkiness. [ABSTRACT FROM AUTHOR]

Rice quality is an essential component of developing new varieties. Simple, high throughput techniques for several indicators of quality were developed long ago, but every breeder knows that two grains can be equal by those tests, but totally different in the mouth of consumer. Further, recent data show that evaluation of rice in terms of cooking and eating quality is not standardised around the world. These two issues pose a problem for breeders who need accurate information to facilitate consumer acceptance of released varieties and a common language to enable dialogue in global rice trading. In order to address these issues we suggest bringing new innovative science to rice quality, such as rheology, tribology and the omics, through greater investment in research. In addition, we suggest collaboration between grain quality specialists to harmonise methods and to bring innovation to developing new scientific outcomes into high-throughput, robust and trait-relevant methods to provide rice improvement programmes with timely and useful information to enable selection. [ABSTRACT FROM AUTHOR]

Insect pests and weeds are the two major biotic factors affecting crop yield in the modern agricultural system. In this study, a brown planthopper (BPH) resistance gene (BPH9) and glufosinate tolerance gene (bar) were stacked into a single T-DNA cassette and transformed into an indica rice (Oryza sativa L.) line Guangzhan 63-4S. A stable transgenic line H23 with a single T-DNA insert was generated, with the T-DNA cassette located on chromosome 3. Field resistance trial using H23 revealed high tolerance to glufosinate and excellent resistance to BPH. These results propose H23 as valuable germplasm for BPH-resistance and glufosinate-tolerance breeding in rice. [ABSTRACT FROM AUTHOR]

This study examined the effects of the combinations of Waxy (Wx) and starch branching enzyme IIb (BEIIb) alleles on starch fine structure and functional properties in indica rice cultivars. The results showed that be2b mutant starches with BEIIb deficiency had higher amylose content, shorter amylose long chains, a higher proportion of amylopectin long chains and molecular order, but a lower proportion of amylopectin short chains and relative crystallinity, resulting in higher gelatinization temperature but lower enthalpy and paste viscosity. Compared with the rice lines carrying Wx b allele, Wx a allele contributed to relatively higher amylose content, longer amylopectin chains, less short-range ordered structure and lower relative crystallinity, leading to a little lower gelatinization enthalpy. This study provides new insight into structure-function relations among rice lines with different allele combinations of starch synthesis related genes, which is a useful strategy for rice quality breeding. [Display omitted] [ABSTRACT FROM AUTHOR]

• Protein content explained 38.6% of the variation in indica rice taste value. • The RVA profile was mainly affected by protein, amylose, and amylopectin content. • The aforementioned parameters explained 60.5% of the variation in rice taste value. • Varieties with high taste values had high PKV and BDV and low HPV, SBV, and CPV. • Changes in rice chemical composition affected RVA profile and altered taste value. Yield, taste quality, and cultivar utilisation improvements are important research topics in indica rice breeding. Herein, we compared the relative effectiveness and relationship of three taste evaluation methods, namely, chemical composition, Rapid Visco Analyser (RVA), and taste analyser. We assessed associations among these methods using 36 indica varieties commonly grown in Yunnan, Sichuan, and Guizhou, China. Temperature and sunlight duration during grain filling influenced rice cooking quality. Varieties with high taste quality had low amylose and protein contents; high peak viscosities and breakdowns; and low hold viscosities, setbacks, and final viscosities. Protein and combined protein and amylose explained 38.6% and 62.1% of the variation in taste value, respectively. The RVA profile was affected by protein, amylose, and amylopectin contents and explained 60.5% of the taste-value variation. This study lays the foundation for taste evaluation of high-quality rice varieties early in the breeding process, which can improve cultivation and marketing potential. [ABSTRACT FROM AUTHOR]

• Brown rice was milled into four layers to analyze endosperm composition. • Different compositions affected rice taste in different layers. • Apparent amylose content (AAC) and soluble sugar affected L3. • Protein content (PC) and amino acid affected L2. • Factors affecting rice taste ranked: AAC > soluble sugar > minerals > amino acids > PC. Clarifying the association of differences in endosperm biochemical composition with nutrient and edible quality can guide rice breeding and cultivation. In this study, very-low-amylose-content (LAC), Japanese good-taste (JTC), Northeast China good-taste (CTC), and Northeast China high-yield (CHC) cultivars were milled to obtain four layers (L1-L4) from outside-in, and then analyzed for apparent amylose content (AAC), protein content (PC), amino acids, soluble sugars, and minerals. The association of these compositions and Rapid-Visco analysis values with taste was also examined. LAC had low AAC, high amino acid and mineral content, and the highest taste value. Taste was significantly affected by AAC and soluble sugar in L3, and by PC in the L2 layer. High levels of amino acid in L2 and L3 improved the taste, as did Mg, P, and Ca in L1. On the whole, starch factors had the highest contribution to taste, followed by minerals, amino acids, and PC. [ABSTRACT FROM AUTHOR]