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Drought Effects on Cotton Yield and Fiber Quality on Different Fruiting Branches
Author(s) -
Wang Rui,
Ji Shu,
Zhang Pan,
Meng Yali,
Wang Youhua,
Chen Binglin,
Zhou Zhiguo
Publication year - 2016
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2015.08.0477
Subject(s) - lint , irrigation , biology , agronomy , fiber , yield (engineering) , fiber crop , horticulture , drought tolerance , field experiment , gossypium , zoology , gossypium hirsutum , chemistry , organic chemistry , metallurgy , materials science
Whole‐plant‐based measurements do not always accurately reflect the effect of drought on cotton because of its indeterminate growth habits. We conducted pot experiments with cotton and imposed three soil water levels (75 ± 5, 60 ± 5, and 45 ± 5% of field capacity [FC]) during boll development to determine influences of drought on yield distribution and fiber quality on different fruiting branches (FB). Drought not only reduced lint yield (decreased by 31 to 35 and 57 to 60% under 60 ± 5% FC and 45 ± 5% FC, respectively) but also altered yield distribution on different FB. Drought plants produced fewer and smaller bolls on higher FB than did the well‐watered plants. Boll biomass distribution and seed number per boll on upper FB were also altered by drought. Fiber length and strength declined progressively with decreasing water availability, being more pronounced on higher FB. Micronaire value was greater on higher FB under the same water regime, while no consistent influences of drought on micronaire were obtained. Boll weight, seed index, and fiber length and strength declined linearly with decreasing mean midday leaf water potential (LWP) during fruit maturation period (FMP) in the range of about 0.7 g, 1.0 g, 2.4 mm, and 3.4 cN tex –1 per MPa, respectively. Our findings showed that the bolls at various FB differed in drought response. The LWP was a suitable index for fiber properties under production environment. These data will be valuable for designing better irrigation strategies and improving cotton simulation models.