A rice grain’s proximate composition determines its nutritional potential. Macronutrient quantification is essential to identify superior genotypes and direct breeding efforts to reach more people who are vulnerable. Conventional methods to determine proximate composition are highly accurate; however, they remain time-consuming, costly, and destructive. Near-infrared (NIR) spectroscopy enables proximate composition analysis in a non-destructive, rapid, inexpensive, and practical manner, providing results similar to well-established conventional methods. This study aimed to evaluate the feasibility of NIRs-based selection to identify more nutritious rice genotypes. A collection of 155 rice genotypes grown in Southern Brazil was used. After harvest, grains were hulled, polished, and milled. NIRs was used to determine moisture, starch, protein, fat, ash, and fiber contents in rice flour. It was possible to differentiate genotypes with higher and lower levels of the investigated components. Similar and distinct values were observed in comparison to other studies, indicating the accuracy of NIRs and the effect of genotype and environment, respectively. Starch is correlated negatively with protein and fat, preventing the identification of genotypes with high levels of these three components. PCA enabled the separation of the genotypes but highlighted the complexity of sample distribution. NIRs is an effective and accurate method to determine the proximate composition of rice, enabling the selection of more nutritious genotypes.

Resumo: Este artigo explora os desafios socioambientais da agricultura enfrentados pelos Países Africanos de Língua Portuguesa após a independência, destacando o papel crucial do melhoramento genético deplantas na sustentabilidade agrícola. A herança colonial, ao incentivar a monocultura voltada para aexportação, dificultou a diversificação produtiva e contribuiu para a degradação dos solos. Todavia,mesmo após a independência, a escassez de investimentos em pesquisa e infraestrutura impediu que a agricultura se adaptasse adequadamente às condições locais e aos efeitos das mudanças climáticas.Desse modo, o melhoramento genético de plantas surge como uma alternativa fundamental,proporcionando o desenvolvimento de cultivares mais resilientes e produtivas, capazes de resistir a solos empobrecidos e variações hídricas. No entanto, a implementação dessa estratégia ainda enfrenta obstáculos, como a falta de especialistas e a fragilidade das políticas públicas. Investimentos em pesquisa, infraestrutura e políticas eficazes são essenciais para garantir a segurança alimentar epromover a resiliência agrícola. Palavras-chave: Mudanças Climáticas; Segurança Alimentar; Inovação Tecnológica; Melhoramento Genético; Biotecnologia.

Rice (Oryza sativa L.) is a staple food for more than half of the world's population, but its production is threatened by salinity, which affects its development in both early and reproductive stages. Gamma radiation-induced mutation has been used to generate genetic variability and develop cultivars better adapted to saline conditions. However, selecting tolerant mutants is challenging due to the genetic complexity of salinity response and the need for large populations. In this study, 100 rice mutants (M5 and M6) and two control cultivars (sensitive and tolerant) were evaluated under salt stress (NaCl 120 mM) in a greenhouse, assessing shoot and root growth and dry weight. Despite the variability generated, no mutant outperformed the tolerant cultivar in all traits analyzed, highlighting the difficulty of selecting promising individuals from small populations. Furthermore, environmental factors may have contributed to inconsistencies between generations, reinforcing the need for large-scale screening. The most effective strategy involves initial field selection, validation under controlled conditions, and further agronomic reassessment. Technologies such as remote sensing-based phenotyping could improve efficiency, but they remain costly. Future studies should integrate new methodologies and keep the selection of salt-tolerant mutants in early generations (M2 and M3) from large populations, alongside yield evaluation to confirm their agronomic applicability under salinity conditions.