The objecti ves of this research are to evaluate the best tomato genotypes, according to their vegetative cycle, yield, and fruit quality, and to determine the influence of photosynthesis, transpiration and efficient water use. This work started in October, 1993, and ended in 1994; it was carried out under greenhouse conditions, at the Universidad Autónoma Agraria "Antonio Narro", Saltillo, Coabuila, Mexico. Significant differences were found among samples between genotypes, time of day, and leaf position. Genotypic yield was influenced by temperature: there was flower drop. The Celebrity genotype of determinate growth habit showed the highest yield per plant (5.42 kg/pt), and was also the most efficient with respect to water use, needing only 22.5 liters to produce a kilogram of fruit. The most precocious hybrid was the determined growth habit Bingo.

Seven potato (Solanum tuberosum L.) genotypes were evaluated, Norteña, Gigant, Mondial, Snowden, Alpha, Atlantic and Russett Burbank, under growth analysis efficiency and productivity criteria (six samples, every 18 days) like crop growth rate (CGR), Relative Growth Rate (RGR), Relative Leaf Growth Rate (RLGR), Leaf Area Ratio (LAR), Leaf Area Index (LAI) and Net Assimilation Rate (NAR). Differences were found (p £ 0.01) for variables in study (except for NAR), for sample variation differences (six along the cycle) being higher CGR in forth sample with Norteña and Russett Burbank genotypes. Norteña, Russett Burbank and Alpha were higher on TCR, showing a considerable increment on fifth and sixth sample. The best genotype on LAR were Atlantic and Snowden, showing Russett Burbank a pronounce decrement on fifth and sixth sample, because of foliar senescence. Respect to LAI, the best genotypes were Norteña and Gigant, being higher on forth and sixth sample, without senescence until this sample. For NAR, no differences were found between genotypes, Norteña was a little bit higher, showing the other five genotypes a similar behavior.

The main objective of this work was to determine the adaptation potential of tomato genotypes for greenhouse. Genotypes evaluated were: hybrids: Contessa, Summer Flavor 5000, Summer Flavor 6000, Celebrity, Bonita, Shady Lady, Sunbolt, Sunny, Heat Wave and Olympic; and the variety Flora Dade, as a check. The variables evaluated were: yield, agroclimatic and physiological. agroclimatic and physiological variables were determine in three evaluations in the crop cycle, at three times/day and two leaf positions, in each evaluation. Significant correlations were found (p≤0.05) between yield in t/ha and mean yield by plant, fruits by plant at harvest, and yield by plant, and between photosynthesis and water use efficiency. Principal component analysis showed first five components have an Eigenvalue greater than one, explaining the first three with a 72% of total variance. The first component, with a 36% of total variance is due to “The yield characteristics” component two, with a 23% of total variance, is due to “internal temperature regulation characteristics” and component five, with a 7.4% of variation, to “photosyntates efficient production”. Multiple linear regression analysis difference was significant (p<0.01). Yield in t/ha was explained by the multiple linear equation (r2 =0.98) of four variables.

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With the objective to determine correlations between yield and principal components of variation of cantaloupe genotypes, in Ramos Arizpe, Coahuila, 12 genotypes were established, in a Complete Randomized Block design with four replications. An experimental plot of two rows five meters long sown at double hill. The genotypes studied were: hybrids: Primo, Pronto, Challenger, Cheyenne, Hi-Line, Cruiser, Durango, Apache, Laguna, Caravelle and Main Pack, and the variety Top Mark, as a control. The variables evaluated were: yield (11 variables: quantitative and qualitative); phenology (three variables); agroclimatic (five variables) and physiologicals (four variables); significant and negative correlations (p<0.05) were found between yield and earliness, mean fruit weight, number of fruits, and between fruit number and fruit lenght. The most correlated physiological variables were photosynthesis and water use efficiency. With the principal component analysis up to the component three 65 % of variance is explained. Component one showed a high value on yield, weight and size characteristics, and called as “Yield Quantitative Characteristics”. In component two, “Earliness Component” showed the higher variations. Component three to six, explain similar proportions the other variables, being the sixth where was found the highest Photosynthesis. Multiple linear regression was significant (p<0.057), due to field conditions, can be considered adequate. Yield in t/ha is explained by a multiple linear equation (r2=0.99) of 10 variables.