Cotton crop maturity: A compendium of measures and predictors

Gwathmey, C. Owen; Bange, Michael; Brodrick, Rose

doi:10.1016/j.fcr.2016.01.002

Cited by 44 publications

(37 citation statements)

References 37 publications

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“…As reported in other studies (Gwathmey, Bangeb, & Brodrick, 2016;Mkhabela et al, 2016), prediction of phenology based on accumulated thermal time showed good agreement with the observed phenology in all crops, except in cotton (Gossypium L.) at Parbhani and pigeon pea [Cajanus cajan (L.) Millsp.] at Bangalore (Figure 3).…”

Section: Validation Of Predicted Phenologysupporting

confidence: 86%

Algorithms for weather‐based management decisions in major rainfed crops of India: Validation using data from multi‐location field experiments

et al. 2021

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Crop weather calendars (CWC) serve as tools for taking crop management decisions. However, CWCs are not dynamic, as they were prepared by assuming normal sowing dates and fixed occurrence as well as duration of phenological stages of rainfed crops. Sowing dates fluctuate due to variability in monsoon onset and phenology varies according to crop duration and stresses encountered. Realizing the disadvantages of CWC for issuing accurate agromet advisories, a protocol of dynamic crop weather calendar (DCWC) was developed by All India Coordinated Research Project on Agrometeorology (AICRPAM). The DCWC intends to automatize agromet advisories using prevailing and forecasted weather. Different modules of DCWC, namely, Sowing & irrigation schedules, crop contingency plans, phenophase-wise crop advisory, and advisory for harvest were prepared using long-term data of ten crops at nine centers of AICRPAM in eight states in India. Modules for predicting sowing dates and phenology were validated for principal crops and varieties at selected locations. The predicted sowing dates of 10 crops pooled over nine centers showed close relationships with observed values (r 2 of .93). Predicted phenology showed better agreement with observed in all crops except cotton (Gossypium L.; at Parbhani) and pigeon pea [Cajanus cajan (L.) Millsp.] (at Bangalore). Predicted crop phenology using forecasted and realized weather by DCWC are close to each other, but number of irrigations differed, and it failed for accurate prediction in groundnut at Anantapur in drought year (2014). The DCWCs require further validation for making it operational to issue agromet advisories in all 732 districts of India.

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Section: Validation Of Predicted Phenologysupporting

confidence: 86%

Algorithms for weather‐based management decisions in major rainfed crops of India: Validation using data from multi‐location field experiments

et al. 2021

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“…Although several methods have been described and applied, there is no standard method for earliness and maturity measurements, since the proposed indices are not applicable for all situations (Ray and Richmond, 1966;Gwathmey et al, 2016). Diagnostic indices of maturity may be obtained from evaluations performed during plant growth or at the end of cycle.…”

Section: Researchmentioning

confidence: 99%

“…Diagnostic indices of maturity may be obtained from evaluations performed during plant growth or at the end of cycle. End-of-season measurements may be temporal, which involve a timescale quantification, or using a relative rather than an absolute timescale (Gwathmey et al, 2016). Earliness has often been evaluated by measuring the proportion of weight harvested at the first picking in relation to…”

Section: Researchmentioning

confidence: 99%

Shading and Nitrogen Effects on Cotton Earliness Assessed by Boll Yield Distribution

2019

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Shading and N fertilization affect fruit distribution in cotton (Gossypium hirsutum L.), but there is no detailed information on earliness of crop maturity according to phenological development. The aim of this work was to evaluate the effect of shading at early flowering and N top‐dressing rates on relative cotton earliness using plant mapping. Field experiments were conducted in Itapeva (16 d of shading; and 0, 60, 120, and 180 kg N ha−1) and Chapadão do Sul (17 d of shading; 0, 80, and 160 kg N ha−1; and early‐ and full‐season cultivars), Brazil. Seed cotton yield was grouped by phenological position (PP) according to the standard phenological scale, for interpolation calculation at each 10% increment in accumulated harvestable yield (Ac), weighted average PP (PPwa) determination, and logistic‐regression analysis. Crop maturity earliness was predicted based on the reduction in PPwa and in PP. Shading increased PP up to 10 and 30% of Ac due to a decrease of 33 and 40% in the number of bolls on early fruiting sites in Itapeva and Chapadão do Sul, respectively, but did not affect PPwa. Increases in PP up to high Ac percentages and in PPwa values were observed at the two higher N rates in both experiments, mainly due to lower and higher boll number at earlier and later fruiting sites, respectively. Short‐term shading during early flowering of cotton changed yield distribution by decreasing boll number on early fruiting sites, but did not affect the earliness of crop maturity. Earliness was decreased by high N rates due to higher cumulative seed cotton yield at later fruiting sites.

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“…Cotton growth and maturity are highly dependent on the environmental condition and field management (Schaefer et al., 2017; Zhao & Oosterhuis, 2000). Late maturity was often observed during abnormal climate conditions which adversely affected cotton yield and sowing of subsequent crops (Du et al., 2013; Gwathmey & Bange et al., 2016). The benefits of earliness include a reduction in late‐season input costs and improvement of the efficacy of defoliants and harvest (Raper & Gwathmey, 2015).…”

Section: Introductionmentioning

confidence: 99%

Multiple applications of mepiquat chloride enhanced development of plant‐wide fruits from square initiation to boll opening in cotton

Liao

Ren

et al. 2021

Crop Science

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Mepiquat chloride (MC) has been widely used for the field management of cotton (Gossypium hirsutum L.) and could enhance yield and quality. However, it is not completely clear how MC influences cotton development. A field study was conducted during 2011∼2012 cotton growing seasons to determine the effects of multiple MC applications (from the late seedling stage to near cutout) on the development of each fruit by calendar days and thermal time. Two cotton cultivars (GX3 and XK4) were used for the study. The MC application significantly hastened the appearance of squares across fruiting positions by 0.4-2.9 d in 2011; and those on upper (from the 11th) fruiting branches and on inner (first two) fruiting nodes of middle (5th-10th) fruiting branches under MC treatment formed 1.8-3.8 d earlier in 2012 compared with control. Also, MC decreased the duration from squaring to flowering by 0.1-0.3 d, and that from bloom to boll opening by 0.9-2.1 d. The MC application reduced the growing degree days (GDD) of most fruiting positions from planting to squaring owing to the early onset of squares. However, it increased the GDD of cotton bolls on the upper fruiting branches during maturation period, presumably due to their early set which exposed them to the higher temperatures during development. These results have improved our understanding of MC-induced earliness in cotton and could help growers to optimize earliness management. INTRODUCTIONCotton (Gossypium hirsutum L.) is an inherently indeterminate crop; its vegetative and reproductive growth continues simultaneously over a lengthy period (Chen & Dong, 2016). Cotton growth and maturity are highly dependent on the environmental condition and field management (Schaefer et al., 2017;Zhao & Oosterhuis, 2000). Late maturity was often observed during abnormal climate conditions which adversely affected cotton yield and sowing of subsequent crops (Du Abbreviations: GDD, growing degree days; MC, mepiquat chloride.

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Cotton crop maturity: A compendium of measures and predictors

Cited by 44 publications

References 37 publications

Algorithms for weather‐based management decisions in major rainfed crops of India: Validation using data from multi‐location field experiments

Algorithms for weather‐based management decisions in major rainfed crops of India: Validation using data from multi‐location field experiments

Shading and Nitrogen Effects on Cotton Earliness Assessed by Boll Yield Distribution

Multiple applications of mepiquat chloride enhanced development of plant‐wide fruits from square initiation to boll opening in cotton

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