Darlene Lonjas Sanchez

The Americas (North, Central, and South America) have expanded rice production and cultivation substantially for both domestic consumption and international trade (Abeysekara & Rathnayake, 2024). B...

‘NeoTrinity’ ( Oryza sativa L.; Reg. no. GP‐156, PI 710320) is a blast‐resistant, premium‐quality, long‐grain rice germplasm developed by the Texas A&M AgriLife Research and Extension Center, Beaumont, TX, through marker‐assisted backcrossing by introgressing the blast resistance Pib gene into the ‘Trinity’. Foreground selection identified 44 of 139 BC ₂ F ₂ plants as homozygous for Pib . Background selection showed that these lines shared 82%–95% genetic similarity with Trinity, given the shared pedigree between Trinity and the Pib donor, ‘Saber’. All their trait marker alleles were identical to Trinity except for the introgressed Pib gene. Agronomic and disease evaluations in 2024 and 2025 identified 17 Texas inbred lines (TILs) with grain yields ranging from 6039 to 7247 kg ha ⁻¹ , comparable to Trinity. These TILs were semidwarf, non‐lodging, and headed ∼1 week later than Trinity. Under high blast disease pressure in 2025, the TILs had lower neck blast ratings, ranging from 0.0 to 2.5, with a mean of 1.1, compared with Trinity's rating of 5.0. Three high‐yielding and highly blast‐resistant TILs (TIL24099, TIL24109, and TIL24088) were advanced for grain quality evaluation. The chalky grain percentages of the three TILs (1.2%–3.9%) were lower than those of ‘Presidio’ (6.0%) and Trinity (7.0%). TIL24088 showed stable whole milled rice recovery across years, and its grain dimensions were most similar to those of Trinity. TIL24088 was selected for release as NeoTrinity because it combines high grain yield, improved grain quality, and superior blast resistance.

Rice ( Oryza sativa L.) tiller angle is an important trait that influences plant architecture, canopy light interception, and yield potential. In this study, we proposed a deep learning‐based pipeline for automated measurement of rice tiller angle and plant base width using unmanned aerial vehicle (UAV) imagery. Our method leverages keypoint detection models to estimate tiller angles efficiently and accurately. We collected and annotated a dataset of UAV‐captured rice plant images for tiller angle estimation. We demonstrated that our approach provides scalable and precise measurement for keypoints under real‐world field conditions, achieving a mean average precision (mAP)@50 of 0.982 and a mAP@50:95 of 0.859 on the test set. Predicted tiller angle distribution aligns well with human annotations, with a mean absolute error of 5.3° across a range of 10.7°–27.8° and a Pearson's correlation coefficient of 0.64, offering acceptable accuracy for tiller angle measurement in real‐world agricultural settings. Additionally, the predicted plant base width ranges from 2.8 to 5.5 cm, with a mean absolute error of 1.02 cm compared to human annotations, highlighting the model's capability for precise spatial analysis. Significant differences in tiller angle and plant base width were detected among 27 rice genotypes. These results validate the proposed pipeline's potential for accurate and efficient differentiation of plant architecture traits. This research is the first to measure the rice tiller angle directly from UAV images. It lays a foundation for automated phenotyping of plant architecture traits and has the potential for integration into plant phenotyping frameworks to further promote artificial intelligence‐driven rice research and production.

The demand for medium‐grain rice ( Oryza sativa L.) in the United States is increasing; therefore, developing high‐yielding, high‐grain quality, and abiotic stress‐tolerant medium‐grain rice is crucial to meet the rising demand. In this study, medium‐grain rice mutants were developed by irradiating long‐grain Presidio rice cultivar. The long‐grain Presidio and its 76 sixth‐generation (M ₆ ) medium‐grain mutants were genetically characterized using single‐nucleotide polymorphisms (SNPs) associated with 10 traits related to grain quality, grain filling, and abiotic stress tolerance‐. Out of the 76 M ₆ Presidio mutants genotyped, 57 mutants homozygous for the medium‐grain allele (GG) of GS3 were selected for further analysis. All mutants and the wild‐type Presidio had the OsISA1 allele (Ex17GG) for low chalkiness. The In1T/G, Ex6A/C, and Ex10C/T SNPs of the Wx locus subdivided the mutants into low‐ and intermediate‐amylose classes. Ex10C/T SNP was used to categorize into either soft or hard gel with weak or strong pasting viscosity. The Ex8C/T SNP of SSIIa classified the mutants into two groups (low and intermediate) based on their gelatinization temperatures. Five promising medium‐grain Presidio mutants (TIL21271‐7‐2, TIL21271‐7‐4, TIL21271‐7‐5, TIL21271‐7‐6, and TIL21271‐7‐8) with high grain filling rate allele of GFR1 and favorable alleles for qSCT1 and OsLPTL159 (cold tolerance), TT1 (heat tolerance), qAG1 and qAG3 (anaerobic germination tolerance), and qDTY1.1 , qDTY3.2 , and qDTY12.1 (drought tolerance) were identified. This study demonstrates the high potential of mutation breeding in developing mutants with favorable alleles on genes for grain yield, quality, and stress tolerance.

This study aimed to develop and genetically characterize thermosensitive genic male-sterility (TGMS) lines for use in hybrid rice (Oryza sativa L.) breeding. Male-sterile F₂ to F₄ generation lines were screened during the high-temperature summer season, and ratoon crops of selected male-sterile rows were harvested for pure seed. Sixty-six F₅ TGMS lines were genotyped using DNA markers controlling 16 traits from the LSU80 QA/QC Rice PlexSeq SNP Panel. Ten TGMS lines with desirable traits that included semidwarf, glabrous, non-aromatic, long-grain, narrow brown leaf spot resistance, and blast resistance genes were selected for further genotypic characterization using markers for low chalkiness (chalk5), wide compatibility (S5-n), cold tolerance (qSCT-11 and qCST-12), and anaerobic germination (AG1 and AG2). TGMS lines TIL21051S and TIL21052S possess favorable alleles for each of the genes evaluated in this study and are desirable parents for two-line hybrid breeding in the southeast United States. TIL21044S, TIL21095S, TIL21060S, and TIL21066S each contain three blast resistance genes and have potential as parental lines. TIL21014S-2, TIL21015S, and TIL21016S-1 include the fgr allele for aroma and can also be used as parental lines for aromatic two-line hybrids.

Basmati rice is a premium aromatic rice that consumers choose primarily because of its distinct aroma and excellent grain quality. The grain quality of Basmati rice (GQBR) reflects the perspectives of producers, processors, sellers, and consumers related to the production, processing, marketing, and consumption of Basmati rice. Consumers, an invaluable part of the production demand and value chain of the Basmati rice industry, have the freedom to choose from different types of aromatic rice. Consumers expect their preferred Basmati rice to possess all superior rice grain qualities, including the physical, biochemical, and physiological properties. Gene functional analysis explained that a 10-base pair deletion in the promoter region of the OsSPL16 gene causes the slender grains in Basmati rice, whereas an 8-base-pair deletion in exon 7 of the OsBadh2 gene (located in the fgr region on rice chromosome 8) results in the distinct aroma. Furthermore, a combination of the genetic characteristics of the gw8 and gs3 genes has led to the creation of a long-grain Basmati-type rice cultivar. It has also been demonstrated that agricultural, genetic, and environmental conditions significantly influence GQBR. Hence, research on improving GQBR requires a multidimensional approach and sophisticated elements due to the complexity of its nature and preference diversity. This review covers the basic definitions of grain quality traits, consumer preference criteria, influencing factors, and strategies for producing superior-quality Basmati rice in the United States. This knowledge will be useful in improving the grain quality of Basmati and Basmati-type rice, as well as developing appropriate breeding programs that will meet the preferences of different countries and cultures.

Background: Grain yield is a complex trait that results from interaction between underlying phenotypic traits and climatic, edaphic, and biotic variables. In rice, main culm panicle node number (MCPNN; the node number on which the panicle is borne) and maximum node production rate (MNPR; the number of leaves that emerge per degree-day > 10°C) are primary phenotypic plant traits that have significant positive direct effects on yield-related traits. Degree-days to heading (DDTH), which has a significant positive effect on grain yield, is influenced by the interaction between MCPNN and MNPR. The objective of this research is to assess the phenotypic variation of MCPNN, MNPR, and DDTH in a panel of diverse rice accessions, determine regions in the rice genome associated with these traits using genome-wide association studies (GWAS), and identify putative candidate genes that control these traits.Results: Considerable variation was observed for the three traits in a 220-genotype diverse rice population. MCPNN ranged from 8.1 to 20.9 nodes in 2018 and from 9.9 to 21.0 nodes in 2019. MNPR ranged from 0.0097 to 0.0214 nodes/degree day > 10°C in 2018 and from 0.0108 to 0.0193 nodes/degree-day > 10°C in 2019. DDTH ranged from 713 to 2,345 degree-days > 10°C in 2018 and from 778 to 2,404 degree-days > 10°C in 2019.Thirteen significant (P< 2.91 x 10^-7) trait-single nucleotide polymorphism (SNP) associations were identified using the multilocus mixed linear model for GWAS. Significant associations between MCPNN and three SNPs in chromosome 2 (S02_12032235, S02_11971745, andS02_12030176) were detected with both the 2018 and best linear unbiased prediction (BLUP) datasets. Nine SNPs in chromosome 6 (S06_1970442, S06_2310856, S06_2550351, S06_1968653, S06_2296852, S06_1968680, S06_1968681, S06_1970597,andS06_1970602) were significantly associated with MNPR in the 2019 dataset. One SNP in chromosome 11 (S11_29358169) was significantly associated with the DDTH in the BLUP dataset.Conclusions: This study identifies SNP markers that are putatively associated with MCPNN, MNPR, and DDTH. Some of these SNPs were located within or near gene models, which identify possible candidate genes involved in these traits. Validation of the putative candidate genes through expression and gene editing analyses are necessary to confirm their roles in regulating MCPNN, MNPR, and DDTH. Identifying the underlying genetic basis for primary phenotypic traits MCPNN and MNPR could lead to the development of fast and efficient approaches for their estimation, such as marker-assisted selection and gene editing, which is essential in increasing breeding efficiency and enhancing grain yield in rice. On the other hand, DDTH is a resultant variable that is highly affected by nitrogen and water management, plant density, and several other factors.

Apparent amylose and protein concentrations (AAC and PC) affect the milling, cooking, and eating quality of rice. This study was conducted to assess the phenotypic and genotypic variation and to identify genomic regions and putative candidate genes associated with AAC and PC in milled rice grain. Two hundred and seventeen and 207 diverse rice accessions were grown at the Texas A&M AgriLife Research Center in 2018 and 2019, respectively. Milled rice samples were analyzed for AAC and PC using the iodine colorimetry and Dumas method, respectively. Genome-wide association studies (GWAS) for AAC and PC were conducted using 872,556 single nucleotide polymorphism (SNP) markers following the mixed linear model. Significant variation among the accessions was found for both variables each year. Associations between 32 SNPs with PC and seven SNPs with AAC were detected. Gene models linked to these SNPs have a wide range of biological functions, including protein and carbohydrate metabolism, DNA methylation, and response to abiotic and biotic stresses. Seven of the identified SNPs colocalized with previously reported quantitative trait loci (QTL) for protein concentration. Fine-mapping of significant genomic regions and gene validation are necessary for this information to aid in marker-assisted breeding for improved grain quality.

We present GWASpro, a high-performance web server for the analyses of large-scale genome-wide association studies (GWAS). GWASpro was developed to provide data analyses for large-scale molecular genetic data, coupled with complex replicated experimental designs such as found in plant science investigations and to overcome the steep learning curves of existing GWAS software tools. GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model. GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10 000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators. GWASpro is freely available at https://bioinfo.noble.org/GWASPRO. Supplementary data are available at Bioinformatics online.