Licania tomentosa is a widely distributed species in Brazil, commonly used in urban landscaping and environmental restoration. Despite its potential, understanding the relationship between fruit maturation and seedling quality remains limited. This study aimed to evaluate the relationship between maturation stages - classified by epicarp coloration - and seedling performance through RGB colorimetric analysis, fruit morphometry, and the application of machine learning algorithms. Fruits were collected from mother trees and classified into four color stages based on the Munsell color chart. Digital images were analyzed to extract RGB values and morphometric parameters of the fruits using ImageJ® software. Subsequently, seedling emergence, biometric attributes, biomass accumulation, and the Dickson Quality Index (DQI) were evaluated. Yellow-Red fruits produced seedlings with higher emergence rates, greater shoot and root biomass accumulation, and higher DQI values, indicating greater seedling vigor. In contrast, Greenish Green-Yellow fruits resulted in less vigorous seedlings. The Red band was the main indicator of changes in the fruits. Morphometric parameters alone were insufficient to discriminate the maturation stages. Linear Discriminant Analysis correctly classified 90.48 % of the fruits according to their maturation stage. The integration of colorimetric data with machine learning proved to be an effective, non-destructive, and low-cost approach for optimizing seed selection. To enhance the predictive accuracy of the model it is recommended to expand the dataset under natural conditions and explore alternative color systems and complementary fruit traits.

Water deficit during the early development of cowpea (Vigna unguiculata (L.) Walp.) can compromise seedling establishment and reduce crop uniformity. This study aimed to evaluate morphological responses and biomass allocation in eight cowpea genotypes, including four commercial cultivars and four landraces, under two water conditions (control and deficit). A randomized block design was applied in a 2 × 8 factorial scheme. Morphological traits of roots and shoots, including length, surface area, volume, and diameter, were measured using image-based analysis. Dry biomass and root-to-shoot ratio were determined through gravimetric methods. Significant genotype-by-environment interactions were observed. Commercial cultivars tended to maintain structural attributes such as stem and root diameter, while landraces, particularly “Marronzinha” and “Verdinha”, exhibited greater plasticity in root morphology and biomass accumulation under water restriction. Although the methodology allowed efficient early phenotyping, limitations such as the short stress duration and use of two-dimensional imaging may restrict broader inferences. Future studies should incorporate extended drought periods, field validation, and physiological assessments to enhance the identification of drought-resilient genotypes.

Coffee yield is influenced by climatic factors, with temperature and water availability being key determinants. This study aimed to evaluate the effects of climate variability on the yield of Arabica coffee ( Coffea arabica L.) cultivars across phenological phases and to validate an agrometeorological model at local and regional scales using yield–climate time‐series data from the Volcanic Region of Poços de Caldas. The Arabica coffee cultivars Mundo Novo 376/4, Catuaí IAC 144, and Bourbon Vermelho were evaluated across four phenological phases. Pearson's correlation coefficients were applied for each phenological phase and production year between yield and climatic variables, along with the Mann–Kendall test to detect monotonic trends in climatic data. The agrometeorological model was evaluated at different analytical scales and under distinct cultivars and yield scenarios, using historical data from 2011 to 2024. The grain‐filling phase was the most sensitive to increasing temperature, while flowering showed a rising warming trend, increasing its vulnerability. Cultivars differed in their thermal and water tolerance, with Bourbon Vermelho showing high vegetative resilience but marked reproductive susceptibility. The model performed well at the regional scale ( R ² = 0.93; RMSE = 453 kg ha ⁻¹ ), particularly within the Volcanic Region, but exhibited limited accuracy at the plot scale due to local variability. Estimated yield losses were mainly associated with water deficit, followed by frost events, while thermal penalties were minimal. These results highlight the need to improve climate‐resilience strategies and mitigate the impacts of climate change on coffee cultivation.

Unlike conventional crops, medicinal plants require continuous physiological monitoring, since their pharmacological compounds are synthesized through stress-sensitive secondary metabolism. In this context, accurate and non-destructive methods for determining chlorophyll content could be valuable tools for assessing the physiological status of these species. Thus, Mikania laevigata Sch. Bip. ex-Baker, widely used in herbal medicine, can benefit from chlorophyll monitoring to enhance its cultivation. This work was developed in order to evaluate the potential of the ClorofiLOG® index as a non-destructive predictor of leaf pigment concentrations in M. laevigata during the vegetative stage. Plants were cultivated for 60 days in greenhouse conditions, and both destructive (spectrophotometric) and non-destructive pigment measurements were collected from medium leaves. Linear regression equations were adjusted between the index and the concentrations of chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids. The adjusted models yielded high coefficients of determination for total chlorophyll and chlorophyll b, with a moderate value for carotenoids. Predictive performance of the adjustments, assessed by the ratio of performance to deviation, was classified as “very good” for total chlorophyll (2.91) and chlorophyll b (2.67), and “weak” for chlorophyll a (1.79) and carotenoids (1.43). Therefore, models based on the ClorofiLOG® index are suitable for non-destructive estimation of total chlorophyll and chlorophyll b in M. laevigata, supporting its application as a practical tool for the physiological monitoring of this species. This approach may assist in the early detection of plant stress, guide nutrient management decisions, and contribute to optimizing cultivation strategies for this medicinal species under both experimental and production-scale conditions.

The success of conservation agriculture in tropical environments depends on crop rotations that integrate species diversity with the production of high-quality mulch, essential for effective soil cover. This study aimed to evaluate the biomass decomposition and nitrogen (N) release from summer cover crop species, by employing distinct indices to characterize their plant residues in terms of nitrogen accumulated release (NAR) and remaining dry matter (RDM). The experiment was conducted at the “Luiz de Queiroz” College of Agriculture, using a randomized block design with five treatments and four replicates. The treatments consisted of plant residues from: sunn hemp (Crotalaria juncea L.), jack bean (Canavalia ensiformis (L.) DC.), Congo grass (Urochloa ruziziensis L.), pearl millet (Pennisetum glaucum L.), and maize (Zea mays L.). Biomass decomposition and N release were assessed using nylon litter bags, with samplings at 15, 30, 60, and 90 days after crop termination. The leguminous species showed the highest N release rates, while among grasses, pearl millet exhibited the highest values for both NAR and RDM after 90 days. A significant correlation was observed between the plant residue quality index (PRQI) and the rates of biomass decomposition and N release. Simultaneously, the residual biomass quality index (RBQI) proved effective in distinguishing tropical forage species as more efficient in balancing NAR and RDM throughout the experimental period.

Salicylic acid is a phenolic hormone that influences the physiological and biochemical processes of plants, including resistance to biotic and abiotic stresses like salinity. The aim of this study was to evaluate the priming of pumpkin seeds with salicylic acid to mitigate salt stress during germination and early development. An entirely randomized design was used, in a 4 × 4 factorial scheme, using different doses of the phytohormone (100, 150, and 200 mg L−1 and distilled water) and salinity levels (0, 2, 4, and 6 dS m−1), with four replicates. Two genotypes, hybrid cv. Atlas and creole variety were used. The priming period of the seeds in salicylic acid was 8 hours. Then, the seeds were packed in germitest paper, soaked in saline solution, and placed in a germinating chamber. The initial germination count, germination percentage, and abnormal seedlings were evaluated. In a greenhouse, the emergence test was conducted with the seeds primed seeds. Saline solution was provided once a day. The percentage of emergence, emergence speed index, shoot and root length, and shoot and root dry mass were evaluated. The salt stress compromised seed germination and seedling development. The hybrid was sensitive to the salinity of 2 dS m−1, while the creole variety tolerated salinity up to 2 dS m−1. Priming of pumpkin seedlings with salicylic acid did not relieve salt stress during germination and early development.