Urbanization has provided greater demand for food, and the search for strategies capable of reducing waste is essential to ensure food security. Lettuce (Lactuca sativa L.) culture has a short life cycle and its harvest point is determined visually, causing waste and important losses. Using vegetation indices could be an important alternative to reduce errors during harvest definition. The objective of this study was to evaluate different vegetation indices to predict the growth rate and harvest point of lettuce. Twenty-five genotypes of biofortified green lettuce were evaluated. The Green Leaf Index (GLI), Normalized Green Red Difference Index (NGRDI), Spectral Slope Saturation Index (SI), and Overall Hue Index (HUE) were calculated from images captured at 1, 8, 18, 24, and 36 days after transplanting (vegetative state). The diameter and average leaf area of plants were measured using QGIS software. Green mass, number of leaves, and plant and stem diameter were measured in the field. The means were compared using the Scott–Knott test (p ≤ 0.05) and simple linear regression models were generated to monitor the growth rate, obtaining R² values ranging from 62% to 99%. Genetic dissimilarity was confirmed by the multivariate analysis presenting a cophenetic correlation coefficient of 88.49%. Furthermore, validation between data collected in the field versus data obtained by imaging was performed using Pearson’s correlations and showed moderate to high values. Overall, the vegetation indices SI, GLI, and NGRDI were efficient for monitoring the growth rate and determining the harvest point of different green lettuce genotypes, in attempts to reduce waste and losses. It is suggested that the definition of the harvest point based on vegetation indices are specific for each genotype.

The use of dwarf plants in tomato breeding has provided several advantages. However, there are no identified dwarf plants (dd) containing the self-pruning habit (spsp). The aim of this work was to obtain future generations, characterize the germplasm, and select potential dwarf plants with a determinate growth habit to obtain Salad-type lines. The work was started by carrying out hybridization, followed by the first, second, and third backcrosses. Once F₂BC₃ seeds became available, the introgression of the self-pruning gene (spsp) into dwarf plants (dd) began. Three strains of normal architecture and a determinate growth habit were hybridized with two strains of dwarf size and an indeterminate growth habit, thus yielding four hybrids. Additionally, donor genotype UFU MC TOM1, the commercial cultivar Santa Clara, and the wild accession Solanum pennellii were used in the experiment. Agronomic traits, fruit quality, metabolomics, and acylsugars content were evaluated, and dwarf plants with a determinate growth habit were selected. Hybrid 3 exhibited the highest yields. Visual differences between determinate and indeterminate dwarf plant seedlings were observed. It is suggested to carry out five self-pollinations of the best dwarf plant determined and subsequent hybridization with homozygous lines of normal plant architecture and determinate growth habit to obtain hybrids.

Tomato (Solanum lycopersicum L.), a globally significant species, faces substantial economic losses due to pest insects. However, exploiting dwarf germplasm for pest resistance, particularly the UFU MC TOM1 lineage, remains underexplored. The objectives of this study were to select backcross populations from dwarf tomato plants through direct and indirect selection and to elucidate whether there are consequences in resistance level as backcross generations progress aiming at a genetic background of interest. Backcross populations 1, 2, and 3 of dwarf tomato plants were obtained. In the conducted experiment, featuring 20 treatments and four repetitions in a randomized block design, we assessed foliar injuries and herbivory through image analysis. Additionally, we quantified the content of acylsugars, conducted chromatographic analysis, and analyzed the metabolomic profile in the leaflets. Promisingly, the UFU 13_1 dwarf plant population showed potential for enhancing genetic improvement programs targeting pest insect resistance. Moreover, the progression of backcross generations yielded varied resistance levels, likely influenced by inheritance patterns and acylsugar content. The UFU MC TOM1 line, distinguished by its high acylsugar content, exhibited robust resistance against both the tomato leafminer (Tuta absoluta Meyrick 1917) and the leafminer (Liriomyza huidobrensis Blanchard). Furthermore, our analysis revealed the expression of metabolites in the UFU MC TOM1 lineage, potentially linked to various biotic and abiotic stress responses. These findings offer promising prospects for leveraging the dwarf tomato variety, UFU MC TOM1, in genetic improvement programs aimed at combating pest insects in tomatoes.

Lettuce (Lactuca sativa) is the most consumed leafy vegetable in the world, with great economic and social importance in Brazil. In breeding programs, selecting genotypes with high agronomic potential is essential to meet market demands and cultivation conditions. In this context, plant phenotyping by means of multispectral imaging emerges as a modern, efficient and non-destructive tool, which enhances the analysis of phenotypic characteristics quickly and accurately. Therefore, the aim of the present study was to group different lettuce situations according to their group using image-based phenotyping, in addition to morphological descriptors and agronomic evaluations. The experiment was carried out in an experimental area of the Federal University of Uberlândia, Campus of Monte Carmelo, MG, Brazil, in randomized blocks with three replicates and 17 treatments (lettuce populations of the F₂ generation, resulting from the cross between different lettuce cultivars and/or lines). Morphological descriptors and agronomic characteristics were obtained in the field. The vegetation indices GLI, NDVI, GNDVI, NGRDI and NDRE were calculated from images acquired at 49 days after transplanting. Means were compared using the Scott–Knott test (p ≤ 0.05), and the results were presented in box plots. Genetic dissimilarity was confirmed by multivariate analysis, which resulted in a cophenetic correlation coefficient of 96.11%. In addition, validation between field-collected data and image-obtained data was performed using heat maps and Pearson’s correlation. Populations UFU 003, UFU 006, UFU 009, UFU 011, UFU 012, UFU 013, UFU 014, UFU 016 and UFU 017 stood out, with high agronomic potential. Image-based phenotyping was correlated with agronomic traits and, therefore, can be considered an alternative to grouping different lettuce populations.

Tomatoes have tremendous economic, social, and nutritional importance. Among the various types of tomatoes, the Saladette/Italian stands out as an important cultivar for both fresh consumption and industrial processing. The production of this vegetable requires investments exceeding USD 30,000.00. Strategies that increase productivity to offset these costs are fundamental. One proposal to increase yield potential in tomato is the production of new hybrids using dwarf male parents as donors through an organized backcross breeding scheme. The present study, therefore, evaluated possible improvements in the agronomic performance and fruit quality of Saladette hybrids obtained from crosses between normal and dwarf inbred lines. Seventeen tomato hybrids obtained from three backcrosses (BC₁, BC_2, and BC₃) and two commercial cultivars as a control (cv. Bento and Vivacy) were evaluated. The data were analyzed using the Scott–Knott test, and artificial neural networks were used to study the dissimilarities among the hybrids. The hybrids obtained from the dwarf male parent exhibited morphological changes in the plants, including a reduction in internodes, a greater number of bunches per linear meter of plant, and biofortification of the fruits. Notably, from the second backcross onwards, increases in fruit productivity and quality were observed when creating hybrid combinations from dwarf male parents.

The objective of this study was to verify the genetic dissimilarity and validate image phenotyping using RGB (red, green, and blue) sensors in tropical carrot germplasms. The experiment was conducted in the city of Carandaí-MG, Brazil, using 57 tropical carrot entries from Seminis and three commercial entries. The entries were evaluated agronomically and two flights with Remotely Piloted Aircraft (RPA) were conducted. Clustering was performed to validate the existence of genetic variability among the entries using an artificial neural network to produce a Kohonen’s self-organizing map. The genotype–ideotype distance index was used to verify the best entries. Genetic variability among the tropical carrot entries was evidenced by the formation of six groups. The Brightness Index (BI), Primary Colors Hue Index (HI), Overall Hue Index (HUE), Normalized Green Red Difference Index (NGRDI), Soil Color Index (SCI), and Visible Atmospherically Resistant Index (VARI), as well as the calculated areas of marketable, unmarketable, and total roots, were correlated with agronomic characters, including leaf blight severity and root yield. This indicates that tropical carrot materials can be indirectly evaluated via remote sensing. Ten entries were selected using the genotype–ideotype distance (2, 15, 16, 22, 34, 37, 39, 51, 52, and 53), confirming the superiority of the entries.