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Maize is a crop of significant economic importance. In the northeast region of Brazil, it serves as the foundation of family support for the majority of farmers. However, achieving high levels of productivity requires an adequate water supply throughout its growth cycle. The northeast semi-arid region experiences low rainfall and high potential evapotranspiration, directly affecting maize development and leading to severe declines in productivity. In this study, genetic selection and proteomic analysis are proposed as a strategy to identify the tolerance of maize cultivars against water stress. The experiments were conducted under two water regimes using randomized block designs with three replicates. Development and productivity traits were evaluated, and genetic parameters were estimated using mixed linear models. Selection for water stress tolerance was based on the harmonic mean of the relative performance of genotypic values. Total protein extraction from maize leaves followed the protocol established by the phenol method, and peptides were analyzed through mass spectrometry. The AG8677P cultivar demonstrated remarkable productivity under drought stress conditions, and proteins related to various fundamentally important biological processes for the tolerance mechanism were identified. The combination of genetic selection with proteomic analysis proves to be an efficient strategy, even in the face of limited resources and a small number of treatments.

Assessing the differential behavior of a group of genotypes in various environments is fundamentally important in any breeding program. As sugarcane is the most important crop in the state of Pernambuco, it is of great relevance to study its performance in different cultivation sites to assist in the recommendation of new cultivars that increase the productivity of the cane fields. In view of the new demand from the sugar-energy sector for cultivars with high energy potential, this work aimed to select and recommend new genotypes with high fiber and sucrose percentage in the sugarcane microregions of the state of Pernambuco. The methodologies used to classify genotypes for adaptability and stability were as follows: simple linear regression, the modified centroid method, additive main effects, multiplicative interaction analysis, and linear mixed models. Genotypes with higher productivity and specific adaptability to the tested microregions were identified. The methodologies applied were efficient and complementary in recommending genotypes with favorable prospects for increasing sugar productivity, cogeneration of electric energy and the production of renewable fuels. Genotypes 6, 7, 9, 14, 16, and 18 stand out in terms of the productivity of sugar and fiber, with high potential to be released as commercial cultivars.

In the Northeast of Brazil, sugarcane cultivar RB962962 is harvested at the end of the cycle, between December and February, with a high sugar yield per area. Recommended for sandy soils of medium texture and fertility, it is resistant to the major diseases and fast-growing in plant and ratoon crops.