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Gabriele Gusmini and Todd C. Wehner

introduction and appreciation by consumers has increased the interest of watermelon breeders in developing cultivars with reduced fruit size. Fruit weight in watermelon production is an important descriptor of fruit type, although it can also be considered a

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Richard P. Marini, James R. Schupp, Tara Auxt Baugher, and Robert Crassweller

Early-season estimates of fruit size distributions would be beneficial for apple growers and packers to develop intelligent marketing plans for the upcoming harvest season. Although apple fruit weight data usually fit a normal distribution ( Clarke

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Richard P. Marini, James R. Schupp, Tara Auxt Baugher, and Robert Crassweller

diameter, there is a need for models to estimate fruit weight (FW) or box count from early-season FD measurements. In previous studies, initial FD measurements were recorded at 30 to 60 d after full bloom (DAFB). Cell division is nearly completed by 60 DAFB

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M. Yamada, H. Yamane, and Y. Ukai

The expected proportion of individuals in progeny having genotypic values for fruit weight over a given selection criterion to the total individuals derived from a cross was estimated by multiple-regression analysis in which inbreeding coefficient (F) and midparental (MP) value were independent variables and progeny mean was the dependent variable in Japanese persimmon (Diospyros kaki Thunb.). A total of 117 seedlings from 39 crosses was used. Genetic differences of progenies among crosses could be explained solely by F and MP, the effect of the former being greater than the latter. The expected proportion of progenies with large fruit decreased as MP decreased and severely decreased as F increased. Based on the parental mean of 35 fruit on a single tree for 3 years, the proportion of individuals in progeny with fruit weight >200 g was estimated as 34%, 21%, and 12% for 0, 0.125, and 0.25 F values, respectively, in individual from a cross with MP = 200 g.

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Ed Stover, Mike Fargione, Richard Risio, Xiaoe Yang, and Terence Robinson

at the Univ. of Florida, for assistance with statistical methods for assessing effects of treatments on fruit weight adjusted for cropload. The cost of publishing this paper was defrayed in part by the payment of page charges. Under postal regulations

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Richard P. Marini and Donald Sowers

Abbreviations: CD, crop density; FI, flowering index; FS, fruit set; FSD, flowering spur density; FW, fruit weight; PD, pygmy density; SLW, specific leaf weight; VSD, vegetative spur density; YE, yield efficiency. 1 Associate Professor. 2 Research

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Patricia I. Garriz, Hugo L. Alvarez, and Graciela M. Colavita

Nondestructive estimation of pear fruit weight is an important horticultural element for size prediction, particularly when repeated measurements of the same tree must be made without affecting growth. Our objective was to develop a method for determining pear fruit weight (W) using models correlating it with fruit maximum diameter (D), an easily measured dimension. A mature crop of Pyrus communis L. cv. Williams was studied at our Experimental Farm. Five trees were selected at random and fruits were sampled at weekly intervals, starting in September, 21 days after full bloom (DFB) and ending in January, 142 DFB, during three growing seasons (1991–92, 1992–93, and 1993–94). Regression equations were developed using SYSTAT procedure. Data for three years were amalgamated because analysis showed that their curves did not differ. W vs. D was best fitted to the model W = 0,8236 D2.778 R 2 = 0,98. Variability of W and D increased with fruit growth.

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Guang-Lian Liao, Xiao-Biao Xu, Qing Liu, Min Zhong, Chun-Hui Huang, Dong-Feng Jia, and Xue-Yan Qu

. Fruit weight and length were significantly increased ( P < 0.01) by, respectively, 20% and 7%. With this treatment, the yield increased by 15% compared with the control group. The fruit shape index did not change significantly ( Fig. 3 ). Fig. 2. ( A

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Nischit V. Shetty and Todd C. Wehner

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.

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Richard P. Marini

Average fruit weight from two apple-thinning experiments was estimated by sampling 20-fruit/tree or harvesting all fruit on three branches/tree. The estimated values were compared with the true average fruit weight calculated from the entire crop on a tree. The value of a fruit was calculated from packout data obtained from the two sampling methods and was compared to the true value obtained from the entire tree. Statistical techniques, typically used by biometritions in medical research, were used to assess the agreement between the values obtained with the estimation methods and the true values. Estimates of average fruit weight obtained from 20-fruit/tree may differ from the true value by about 13% and estimates obtained from weighing all fruit on three limbs/tree may be within about 11% to 19% of the true mean. Estimates of fruit value obtained from a 20-fruit sample may differ from the true value by about 4 cents per fruit and estimates from three limbs/tree may differ from the true mean by about 7 cents per fruit. Analysis of variance was performed on each data set and the resulting P values differed for the three methods of estimating fruit weight and fruit value. Thus, erroneous conclusions may result from experiments where fruit weight and fruit value is estimated from relatively small samples.