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  • Author or Editor: Lia Hemerik x
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Fruit set and yield patterns were studied in detail in six pepper cultivars. Fruit set differed largely between the cultivars: cultivars with small fruits (fruit fresh weight 20 to 40 g) showed higher fruit set (≈50%) than cultivars with large fruits (fruit fresh weight 120 to 200 g; 11% to 19%). The former showed continuous fruit set (four to five fruits/plant/week), whereas the latter showed fluctuations in fruit set. Fluctuations in weekly fruit set, expressed as the ratio between standard deviation of weekly fruit set and the mean of weekly fruit set (cv), were much lower for the cultivars with small fruits (0.44 to 0.49) than for the cultivars with large fruits (1.1 to 1.6). Fluctuations in weekly fruit yield varied between 0.51 and 0.77 for cultivars with small fruits and between 1.04 and 1.45 for cultivars with large fruits. Fluctuations in fruit yield were significantly positively correlated (Pearson R = 0.87) with fluctuations in fruit set. The correlation between fruit set and fruit yield patterns was highest with a lag time of 8 weeks for the cultivars with small fruits and 9 to 10 weeks for the cultivars with large fruits. This corresponds with the expected lag time based on the average fruit growth duration. The cultivars produced the same amount of biomass, implying that source strength was more or less similar. Hence, differences in fruit set and fruit yield patterns between the cultivars were not the result of differences in source strength and must therefore be related to differences in sink strength.

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Quantifying fruit growth can be desirable for several purposes (e.g., prediction of fruit yield and size, or for the use in crop simulation models). The goal of this article was to determine the best sigmoid function to describe fruit growth of pepper (Capsicum annuum) from nondestructive fruit growth measurements. The Richards, Gompertz, logistic, and beta growth functions were tested. Fruit growth of sweet pepper was measured nondestructively in an experiment with three different average daily temperatures (18, 21, and 24 °C) and in an experiment with six cultivars with different fruit sizes (20 to 205 g fresh weight). Measurements of fruit length and fruit diameter or circumference were performed twice per week. From these, fruit volume was estimated. A linear relationship related fruit fresh weight to estimated fruit volume, and a Ricker or polynomial function related fruit dry matter content to fruit age. These relations were used to convert estimated fruit volume into fruit fresh and dry weights. As dry weight increased until harvest, fitting the sigmoid function to the dry weight data was less suitable: it would create uncertainty in the estimated asymptote. Therefore, the sigmoid functions were fitted to fresh weight growth of the fruit. The Richards function was the best function in each data set, closely followed by the Gompertz function. The fruit dry weight growth is obtained by multiplication of the sigmoid function and the function relating fruit dry matter content to fruit age.

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