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RESEARCH ARTICLE (Open Access)

Untangling the complex mix of agronomic and economic uncertainties inherent in decisions on rainfed cotton

Sosheel S. Godfrey https://orcid.org/0000-0001-5705-8201 A B * , Thomas L. Nordblom https://orcid.org/0000-0002-9892-5102 A B , Muhuddin Rajin Anwar https://orcid.org/0000-0003-4226-746X A C , Ryan H. L. Ip https://orcid.org/0000-0001-8636-1891 D , David J. Luckett https://orcid.org/0000-0002-1687-5413 A and Michael P. Bange https://orcid.org/0000-0001-7728-2219 E
+ Author Affiliations
- Author Affiliations

A Gulbali Institute (Agriculture, Water and Environment), Charles Sturt University, Locked Bag 588, Wagga Wagga, NSW 2678, Australia.

B School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University, Locked Bag 588, Wagga Wagga, NSW 2678, Australia.

C NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, PMB, Wagga Wagga, NSW 2650, Australia.

D School of Computing, Mathematics and Engineering, Charles Sturt University, Locked Bag 588, Wagga Wagga, NSW 2678, Australia.

E Cotton Seed Distributors, formerly CSIRO Agriculture and Food, Australian Cotton Research Institute, Narrabri, NSW 2390, Australia.

* Correspondence to: sgodfrey@csu.edu.au

Handling Editor: Zed Rengel

Crop & Pasture Science 74(12) 1223-1237 https://doi.org/10.1071/CP22145
Submitted: 26 April 2022  Accepted: 18 April 2023  Published: 9 May 2023

© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Context

Production of rainfed (dryland) cotton (Gossypium hirsutum L.) occurs in many places globally, and is always burdened with greater uncertainties in outcomes than irrigated cotton. Assessing farm financial viability helps farmers to make clearer and more informed decisions with a fuller awareness of the potential risks to their business.

Aim

We aimed to highlight key points of uncertainty common in rainfed cotton production and quantify these variable conditions to facilitate clearer decision-making on sowing dates and row configurations.

Methods

The consequences of these decisions at six locations across two states in Australia, given estimates of plant-available water at sowing, are expressed in terms of comparable probability distributions of cotton lint yield (derived from crop modelling using historical weather data) and gross margin per hectare (derived from historical prices for inputs and cotton lint yield), using the copula approach. Examples of contrasting conditions and likely outcomes are summarised.

Key results

Sowing at the end of October with solid row configuration tended to provide the highest yield; however, single- and double-skip row configurations generally resulted in higher gross margins. Places associated with higher summer-dominant rainfall had greater chance of positive gross margins.

Conclusion

In order to maximise the probability of growing a profitable crop, farmers need to consider the variabilities and dependencies within and across price and yield before selecting the most appropriate agronomic decisions.

Implications

Given appropriate data on growing conditions and responses, our methodology can be applied in other locations around the world, and to other crops.

Keywords: dryland cotton, Gossypium hirsutum L, gross margin, management strategies, OZCOT for cotton, probabilistic model, risk.

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