Although intensively studied, few works had looked into S. pennellii’s ability to cope with water-deficit conditions from a breeding point of view. In this study, we assessed potential traits of S. pennellii, that had previously been linked to high yields in other plant species, under long-term water-limited conditions and made a parallel with plant yield. For this purpose, the drought-resistant tomato genotypes IL 3–5 and IL 10–1, and the drought-sensitive IL 2–5 and IL 7–1 at seed level, together with both parents the S. pennellii accession LA 716 and the cultivar M82 were kept at 50 and 100% ASW throughout the growing season. Our findings confirm the superiority of LA 716 under water-limited conditions compared to the other S. lycopersicum genotypes in terms of plant water status maintenance. Percentual reduction on plant yield was higher in IL 3–5 and IL 10–1 than in M82 plants, indicating no correlation between drought resistance on germination and plant productive stages. A strong positive correlation was found between fruit yield and A, gs, and Ψleaf at 50% ASW, suggesting these traits as important selection criteria. LT and gmin, LA 716’s most promising traits, did not show a linear correlation with fruit yield under low water regimes. This study unravels traits behind tomato performance under water-limited conditions and should work as guidance for breeders aiming at developing drought-resistant tomato cultivars.

This work aimed to study the inheritance of resistance to Phytophthora infestans in tomato plants, using the maximum likelihood estimation function. The susceptible cultivar Santa Clara (Solanum lycopersicum) was used as the female genitor and the P. infestans resistant S. habrochaites f. glabratum accession (BgH 6902) as the male genitor. F 1 plants from the crossing were self-pollinated to produce F 2 progenies, and also backcrossed with P r and P S to produce BC 1:r and BC 1:S generations, respectively. The tomato plants were inoculated 50 days after transplanting. Disease severity was evaluated via a diagrammatic scale. Comparison of the genetic models created using the maximum likelihood function revealed that the inheritance of resistance to P. infestans in S. habrochaites is conferred by a major gene with additive and dominance effects, polygenes with additive effects, plus the environmental effect. Vertical resistance can be explored using genes with major effects. Programs of recurrent and makerassisted selection are considered efficient strategies with which to select genotypes that hold P. infestans resistance conferred by polygenes.

In the genetic breeding of tomatoes, not only productivity, but also factors related to fruit quality and pest and disease management are taken into account. In this context, diseases stand out, since they are the main bottlenecks for successful cultivation. Currently, the search for more sustainable crops has demanded from producers’ alternatives to disease control to reduce the use of pesticides. Among the diseases that most reduce tomato production in Brazil, whether for table or industry, we can mention late blight, black spot, fusarium wilt, viruses, bacterial and nematode diseases. Genetic resistance, obtained by genetic breeding programs, is one of the best tools to deal with diseases to depend less on pesticides. Thus, this review aims to provide an overview of tomato breeding programs in terms of resistance to the main diseases that affect this crop.

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The mineral fertilizing and the supply of water seem to influence the content of lycopene in the fruits of tomato, thus it is crucial to elucidate the ideal levels of fertilizers and the adequate management of irrigation for this crop. Hence, the study had an objective to evaluate the efficiency of different levels of mineral fertilizing and the effect of irrigation management on the productivity as well as on the lycopene content in the fruits of tomato. For this, two experiments in Winter/Spring and Summer/Autumn were carried out. The treatments consisted of the combination of different levels of mineral fertilizersing with nitrogen, phosphorous, and potassium along with two levels of irrigation. The productivity of fruits, the production of large fruits, the lycopene content, and the efficiency in the use of nutrients, were evaluated. With the application of 120% of the recommended dose of fertilizing, the productivity of large fruits was maximum. The efficiency in the use of nitrogen, phosphorous, and potassium was maximum with the application of 120, 121 and 50% of the recommended dose of fertilizing, respectively, and 100% of the irrigation depth. The maximum content of lycopene was obtained, by applying 200% of the fertilizing dose and 50% of the irrigation depth. The best combination for the production of large fruits, higher lycopene content, and higher efficiency in the use of nitrogen, phosphorous, and potassium, was the application of 120% of the dosage of fertilizing and 100% of the irrigation depth.

At initial breeding stages, using a replicated check design is a viable alternative to reduce experimental field area as well as financial and operational costs. In this situation, spatial modeling could act to increase prediction accuracy of plant genotypic values. The objectives of this study were to demonstrate how spatially adjusted models can be used to reduce experimental error and how to compare statistical models in order to identify the best model for accurate genotype selection. For this purpose, we assessed 200 F 3:4 tomato families for their resistance to Phytophthora infestans isolates. NC1CELBR, NC25P, and the cultivar Santa Clara were used as checks. Under field conditions, plants were inoculated with P. infestans isolates and scored according to their level of disease severity. Nine statistical models were adjusted to estimate family genotypic values. The selection of the fittest model was based on residual variance values, accuracy, Akaike and Bayesian information criteria, and the maximum likelihood ratio test. We observed spatial patterns within the experimental field area. Spatial modeling decreased error, which is indicated by the better experimental variation distribution. Residual variance decreased, while genotypic variance increased ∼10% when spatial analysis was used. Spatial analysis improved selection accuracy by 19% compared with the traditional analysis. Therefore, we recommend incorporating spatial modeling into data analysis in breeding trials for disease resistance because it can provide higher gains from selection compared with traditional modeling approaches, depending on the experimental condition.

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