Heritability of resistance to gummy stem blight (Didymella bryoniae (Auersw.) Rehm.) was measured in two diverse cucumber (Cucumis sativus L.) populations [North Carolina elite slicer 1 (NCES1) and North Carolina wide base pickle (NCWBP)]. Heritability was estimated using parent-offspring regression and half-sib family analysis in North Carolina field tests during 1991 and 1992. NCES1 is a slicing cucumber population with a narrow genetic base, and NCWBP is a pickling cucumber population with a wide genetic base. Heritability estimates were low to moderate ranging from 0.12 to 0.49 for the gummy stem blight leaf rating and from -0.03 to 0.12 for stem rating. Estimates of gain from selection were at least two times larger for selection based on half-sib families than for mass selection for all traits in both populations. Approximately three to five cycles of selection would be required to improve the NCES1 population mean for gummy stem blight leaf resistance by one rating scale unit, and three to four cycles of selection would be required to improve the NCWBP population mean for gummy stem blight leaf resistance by one rating scale unit, based on half-sib family selection. One rating scale unit decrease is equivalent to an 11% reduction in susceptibility. Gain would be slower if selecting for stem, or leaf and stem resistance. A moderate amount of additive genetic variation exists in both populations for gummy stem blight leaf resistance, but estimates for additive genetic variation for stem resistance indicate little to no additive genetic variation. Development of populations specifically for greater initial resistance and greater additive variance than found in these populations should aid in selection for resistance.
Pigeonpea, a subtropical legume, was successfully grown in a high-latitude (≈45°N) environment. Four short-season pigeonpea accessions from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) were subjected to three cycles of pedigree selection. Performance trials (175,000 plants/ha) were conducted on loamy sand with dryland and irrigated sites in 1991 and 1992. Thirty-eight S3-derived lines from ICRISAT ICPL 83004 were used in both years and seven S3-derived lines from ICRISAT P 2125 and ICRISAT ICPL 85010 were added the second year. Differences (P ≤ 0.05) in seed yield (kg·ha–1) were observed among the S3 lines, with a maximum yield of 1468 kg·ha–1. The lines also differed (P ≤ 0.05) for harvest index (HI), calculated as the ratio of seed yield to shoot total dry matter (TDM) with a maximum of 0.48 (line MF-26). Dryland seed yield was strongly correlated with TDM (r 2 = 0.98), HI (r 2 = 0.92), and early bloom (r 2 = 0.76). In a time-of-planting comparison of seven lines in 1992, seed yield was highest (754 kg·ha–1) at the earliest (29 Apr.) planting date and declined progressively to 178 kg·ha–1 at the latest (2 June) planting date, while HI decreased from 0.42 to 0.12. Plants were shorter at maturity in the earliest planting date.
In many cases, measurement of cucumber fruit weight in small research plots involves more labor and resources than just counting the number of fruit per plot. Therefore, plant breeders are interested in an efficient method for estimating fruit weight per grade (early, marketable, and cull) based on fruit number and total fruit weight. We evaluated the cucumber germplasm collection of 810 plant introduction accessions (supplied by the U.S. Dept. of Agriculture, Regional Plant Introduction Station at Ames, Iowa) along with seven check cultivars for yield. Correlations were calculated for all pairs of fruit number and fruit weight combinations for each grade. In general, the lowest correlations were observed between the fruit weight of each grade (early, marketable, and cull) and total fruit weight or number per plot. High correlations were observed for fruit weight and fruit number within each grade (early, marketable, and cull). An efficient method for estimating fruit weight per hectare of early, marketable, and cull grades is to count total, early, and cull fruit, then measure total fruit weight. Our results showed that the fruit weight of each grade (early, marketable, and cull) was best estimated using the fruit number of that grade (early, marketable, and cull) along with the total fruit weight and total fruit number.