Water saving rice cultivation using sheet-pipe subsurface irrigation.

Water saving in rice cultivation has assumed paramount importance, especially in the context of climate change. The introduction of sheet-pipe technology in Indonesia heralded as an innovative subsurface irrigation and drainage system, is poised to revolutionize how to manage this vital resource. Our study was designed with two primary objectives: first, to investigate how rice plants respond when water levels are deliberately reduced using the sheet-pipe technology; and second, to comprehensively analyze water productivity and water use efficiency in comparison to conventional flooded rice cultivation systems. We conducted two distinct experiments: one employing sheet-pipe subsurface irrigation (SSI) and the other utilizing conventional flooded irrigation (CFI). In the SSI setup, the water level was maintained at a depth of 5-10 cm below the soil surface 20 days after transplanting to harvesting. With this setting, the soil moisture was maintained at around 85-95 degrees of saturation. On the other hand, the CFI approach involved water flowing directly over the soil surface, with the water level consistently maintained at a mere 2-3 cm above it. Interestingly, while the SSI method did lead to a reduction in yield, it has significant benefits. Our results showed that a reduction in yield was observed for the SSI 15.5-18.6 % lower compared to the conventional method (CFI). However, the SSI is environmentally benefit compared to the conventional method by reducing 37.5-50.5 % in water irrigation, increasing water use efficiency (WUE) up to 70.8 %, and improving 3.2-10.4 % in water productivity. Our findings reveal that optimizing water conservation may have a disadvantageous effect on rice yield, indicating the importance of optimal water level. Future research to find the optimal water level that balances yield production and environment is required, especially to adapt to dry and warming climate change in the future.

Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel.

Vitamin A deficiency remains prevalent on a global scale, including in regions where maize constitutes a high percentage of human diets. One solution for alleviating this deficiency has been to increase grain concentrations of provitamin A carotenoids in maize (Zea mays ssp. mays L.)-an example of biofortification. The International Maize and Wheat Improvement Center (CIMMYT) developed a Carotenoid Association Mapping panel of 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. Several major genes have been identified for these traits, 2 of which have particularly been leveraged in marker-assisted selection. This project assesses the predictive ability of several genomic prediction strategies for maize grain carotenoid traits within and between 4 environments in Mexico. Ridge Regression-Best Linear Unbiased Prediction, Elastic Net, and Reproducing Kernel Hilbert Spaces had high predictive abilities for all tested traits (ß-carotene, ß-cryptoxanthin, provitamin A, lutein, and zeaxanthin) and outperformed Least Absolute Shrinkage and Selection Operator. Furthermore, predictive abilities were higher when using genome-wide markers rather than only the markers proximal to 2 or 13 genes. These findings suggest that genomic prediction models using genome-wide markers (and assuming equal variance of marker effects) are worthwhile for these traits even though key genes have already been identified, especially if breeding for additional grain carotenoid traits alongside ß-carotene. Predictive ability was maintained for all traits except lutein in between-environment prediction. The TASSEL (Trait Analysis by aSSociation, Evolution, and Linkage) Genomic Selection plugin performed as well as other more computationally intensive methods for within-environment prediction. The findings observed herein indicate the utility of genomic prediction methods for these traits and could inform their resource-efficient implementation in biofortification breeding programs.

An overview of image-based phenotyping as an adaptive 4.0 technology for studying plant abiotic stress: A bibliometric and literature review.

Improving the tolerance of crop species to abiotic stresses that limit plant growth and productivity is essential for mitigating the emerging problems of global warming. In this context, imaged data analysis represents an effective method in the 4.0 technology era, where this method has the non-destructive and recursive characterization of plant phenotypic traits as selection criteria. So, the plant breeders are helped in the development of adapted and climate-resilient crop varieties. Although image-based phenotyping has recently resulted in remarkable improvements for identifying the crop status under a range of growing conditions, the topic of its application for assessing the plant behavioral responses to abiotic stressors has not yet been extensively reviewed. For such a purpose, bibliometric analysis is an ideal analytical concept to analyze the evolution and interplay of image-based phenotyping to abiotic stresses by objectively reviewing the literature in light of existing database. Bibliometricy, a bibliometric analysis was applied using a systematic methodology which involved data mining, mining data improvement and analysis, and manuscript construction. The obtained results indicate that there are 554 documents related to image-based phenotyping to abiotic stress until 5 January 2023. All document showed the future development trends of image-based phenotyping will be mainly centered in the United States, European continent and China. The keywords analysis major focus to the application of 4.0 technology and machine learning in plant breeding, especially to create the tolerant variety under abiotic stresses. Drought and saline become an abiotic stress often using image-based phenotyping. Besides that, the rice, wheat and maize as the main commodities in this topic. In conclusion, the present work provides information on resolutive interactions in developing image-based phenotyping to abiotic stress, especially optimizing high-throughput sensors in image-based phenotyping for the future development.

Combining ability of tropical × temperate maize inducers for haploid induction rate, R1-nj seed set, and agronomic traits.

In vivo maternal haploid induction in isolation fields is proposed to bypass the workload and resource constraints existing in haploid induction nurseries. A better understanding of combining ability and gene action conditioning traits related to hybrid inducers is necessary to set the breeding strategy including to what extent parent-based hybrid prediction is feasible. This study aimed to evaluate the following in tropical savanna in the rainy and dry seasons for haploid induction rate (HIR), R1-nj seed set, and agronomic traits: 1) combining ability, line per se, and hybrid performance of three genetic pools; 2) genetic parameters, the modes of gene action, and heterosis; and 3) the relationships of inbred-general combining ability (GCA) and inbred-hybrid performance. Fifty-six diallel crosses derived from eight maize genotypes were evaluated in the rainy season of 2021 and the dry season of 2021/2022. Reciprocal cross effects including the maternal effect barely contributed to the genotypic variance for each trait observed. HIR, R1-nj seed set, flowering dates, and ear position were highly heritable and additive inherited, while ear length showed dominant inheritance. The equal importance of additive and dominance effects was found for yield-related traits. Temperate inducer BHI306 was the best general combiner for the HIR and R1-nj seed set, followed by two tropical inducers, KHI47 and KHI54. The ranges of heterosis were trait-dependent and slightly influenced by the environment, where hybrids in the rainy season consistently had higher heterosis than those in the dry season for each trait observed. Both hybrid groups derived from tropical × tropical and tropical × temperate inducers showed taller plants, larger ear size, and higher seed sets than the corresponding parents. However, their HIRs were still below the standard check of BHI306. The implications of genetic information, combining ability, and inbred-GCA and inbred-hybrid relationships on breeding strategies are discussed.