Characterization of canopy structure for high-yield performance of greenhouse-grown satsuma mandarins using direct measurements and indirect estimations
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- YANO Taku
- Oita Prefectural Agriculture, Forestry and Fisheries Research Center
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- YASUTAKE Daisuke
- Faculty of Agriculture, Kyushu University
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- KIYOSUE Yoshinobu
- Oita Prefectural Agriculture, Forestry and Fisheries Research Center
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説明
Under assuming that high-yield canopy structure would be simply explained by a given index, orchard productivity of greenhouse-grown early-flowering satsuma mandarins “Miyagawa wase” was assessed using conventional modified-open-center-training and trellis-training methods. This was done by using universal indices that assist with determining yield in relation to canopy structure. Leaf area index was the optimum index for determining fruit yield. Empirical extinction coefficients showed negative linear trends with yield. Either plant area index, estimated by using a plant canopy analyzer, and crown cover showed poor correlation with fruit yield. To effectively predict yield from leaf area index, a direct measurement is recommended rather than an indirect optical method. Trellis-trained trees were superior to modified-open-center-trained trees. This is because trellis-trained trees had higher fruit productivity up untill 10 yeas old, and because 15-year-olds had better canopy light distrubution patterns when compared with modified open-center-trained trees. Based on the costs associated with planting seedlings and the labor-efficiency due to width of free alley, trellis-training 2.2 m×1.0 m plots was optimum for planting. In this study, even when accounting for the measurement error of woody elements, empirical extinction coefficients was a good index to base yield productivity. This is because this index directly represents vertical canopy light distribution. Additionally, the clumping index, calculated by using direct measurement and indirect optical method, was suggested to relate to canopy light distribution, however, further study must be essential.
収録刊行物
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- 農業気象
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農業気象 78 (1), 19-30, 2022
日本農業気象学会
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詳細情報 詳細情報について
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- CRID
- 1390572244891046656
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- NII論文ID
- 130008140318
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- NII書誌ID
- AN00200732
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- ISSN
- 18810136
- 00218588
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- NDL書誌ID
- 031946377
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDLサーチ
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