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Improving temperature‐based predictions of the timing of flowering in cotton

Bange, M., Nunn, C., Mahan, J., Payton, P., Milroy, S.ORCID: 0000-0002-3889-7058, Finger, N., Caton, J., Dodge, W. and Quinn, J. (2022) Improving temperature‐based predictions of the timing of flowering in cotton. Agronomy Journal . Early View.

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Key management recommendations for cotton (Gossypium hirsutum L.) management require estimates of the timing of crop phenology. Most commonly growing day degree (DD) (thermal time) approaches are used. Currently, across many cotton production regions, there is no consistent approach to predicting first square and flower timing. Day degree approaches vary considerably, with base thresholds different (12.0–15.6 °C) with no consistency using an optimum temperature threshold (i.e., temperature where development ceases to increase). As cotton is grown in variable and changing climates, and cultivars change, there is a need to ensure the accuracy of this approach for predicting timing of flowering for assisting cotton management. In this study new functions to predict first square and first flower were developed and validated using data collected in multiple seasons and regions (Australia and the United States). Earlier controlled environment studies that monitored crop development were used to assess in more detail how temperatures were affecting early cotton development. New DD functions developed predicted first square and first flower better than the existing Australian and U.S. approaches. The best performing functions had base temperatures like those of existing U.S. functions (15.6 °C) and an optimum threshold temperature of 32.0 °C. New universal DD targets for first square (343 DD [°C]) and first flower (584 DD) were developed. Controlled environment studies supported this base temperature outcome; however, it was less clear that 32.0 °C was the optimum threshold temperature from these data. Precise predictions of cotton development will facilitate accurate growth stage assessments and hence better cotton management decisions.

Item Type: Journal Article
Murdoch Affiliation(s): College of Science, Health, Engineering and Education
Publisher: American Society of Agronomy
Copyright: © 2022 The Authors.
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