Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance

Ritchie, J. T.; Abawi, GY; Dutta, Sunil; Harris, Trevor; Bange, Michael

doi:10.1111/j.1467-8489.2004.t01-1-00230.x

Cited by 25 publications

(15 citation statements)

References 27 publications

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“…This does not impair yields or the quality of the fiber. Tennakoon & Milroy (2003) and Ritchie et al (2004) obtained an increase in water use efficiency by studying some irrigation strategies, aiming at higher water saving.…”

Section: Introductionmentioning

confidence: 99%

Productive characteristics and water use efficiency in cotton plants under different irrigation strategies

Silva

Andrade²,

Fernandes³

et al. 2010

Rev. bras. eng. agríc. ambient.

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Studies have been carried out on efficient water use in irrigation. The present study evaluates the yield of cotton plants (Gossypium hirsutum L. r. latifolium Hutch), and the use of water for different irrigation strategies. The experiment was conducted under greenhouse conditions, and the cultivar used was CNPA-7H Precocious grown in plastic pots; each pot contained 20 kg of dry soil. The irrigation strategies were selected by taking into account the available water in the soil, the irrigation frequency and the irrigation suppression during flowering and boll development. Water consumption, boll weight, yield, harvest index and water use efficiency were evaluated and the results showed that water consumption resulting from the irrigation strategies used brought expressive variations in the studied parameters. In all strategies, irrigation suppression was the decisive factor in evaluating the water use efficiency. Key words: Gossypium hirsutum, phenology, water availability, water savingCaracterísticas produtivas e eficiência do uso de água do algodoeiro sob diferentes estratégias de irrigação RESUMO Estudos vêm sendo realizados com o objetivo de se estabelecer maior economia de água no manejo da irrigação sem, no entanto, prejudicar o rendimento das culturas, o que serviu de base para a realização do presente trabalho, visandose avaliar o rendimento do algodoeiro (Gossypium hirsutum L. r. latifolium Hutch) e a eficiência no uso da água pela cultura, sob diferentes estratégias de irrigação. O experimento foi conduzido em casa de vegetação, utilizando-se da cultivar CNPA-7H Precoce, cultivada em vaso plástico, contendo 20 kg de solo seco ao ar. As estratégias de irrigação foram estabelecidas levando-se em consideração a água disponível no solo, a frequência de irrigação e a supressão da irrigação na floração e no desenvolvimento das maçãs. Avaliaram-se: consumo de água, peso de capulho, rendimento, índice de colheita e eficiência no uso da água e, segundo os resultados obtidos, o consumo hídrico, influenciado pelas estratégias de irrigação, proporcionou variações expressivas em todos os parâmetros estudados, sendo a época da supressão da irrigação o fator determinante sobre a eficiência de uso da água. Palavras-chave:Gossypium hirsutum, fenologia, disponibilidade de água, economia de água 1 Part of the Master's Dissertation of the first author, presented at the PPGA of the CCA-UFPB 2 DSER/CCA/UFPB,

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Section: Introductionmentioning

confidence: 99%

Productive characteristics and water use efficiency in cotton plants under different irrigation strategies

Silva

Andrade²,

Fernandes³

et al. 2010

Rev. bras. eng. agríc. ambient.

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“…In other words, SDRF establishes necessary and sufficient conditions for the cumulative distribution function of F (y) to be preferred to the cumulative distribution function of G (y) by all individuals whose absolute risk aversion functions lie between lower r 1 (y) and upper bounds r 2 (y) (Harris and Mapp, 1986). Stochastic dominance with respect to a function has been implemented by many empirical studies (Barham et al, 2011;Cochran et al, 1985;Greene et al, 1985;Harris and Mapp, 1986;King and Robison, 1981;de la Llata et al, 1999;Musser et al, 1981;Parcell and Langemeier, 1997;Ritchie et al, 2004;Zacharias and Grube, 1984). It is a practical tool to help farmers better understand their risk preferences and choices under price, yield, or weather uncertainty (King and Robison, 1981).…”

Section: Stochastic Dominancementioning

confidence: 99%

Risk Management Strategies using Precision Agriculture Technology to Manage Potato Late Blight

et al. 2017

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Precision agriculture has emerged as a revolutionary technology, which transforms farming related data into useful information for agricultural decision-making. Th is paper compares precision farming technology with calendar-based approach in scheduling fungicide applications to manage potato (Solanum tuberosum L.) late blight disease. Th ree fungicide scheduling strategies were evaluated: calendar-based strategy, BlightPro decision support system based strategy (DSS-based strategy), and unsprayed control. Using results from 14 yr of computer simulation experiments for 59 locations in the United States, we constructed distributions of net return to all costs excluding fungicide cost and application cost per 0.41 ha (net return per 0.41 ha) for the calendar-based and DSS-based strategies at each location. Th ese distributions were then compared using three risk management methods: stochastic dominance, stochastic dominance with respect to a function, and stochastic effi ciency with respect to a function. Th e DSS-based strategy was identifi ed as the most eff ective approach to manage late blight in terms of disease suppression, net return per 0.41 ha, and risk-adjusted net return. Results indicate that the DSS-based strategy is the preferred method to schedule fungicide applications. Under high disease pressure circumstances, the economic benefi ts to potato growers of adopting the precision agriculture technology ranged from US$30 to $573 per 0.41 ha. For risk neutral individuals, who are concerned about the diff erence between average net return per 0.41 ha, the benefi ts ranged from $30 to $305 per 0.41 ha. Except for growers raising the moderately resistant potato cultivars, more risk averse individuals tended to benefi t more from adopting the precision agriculture technology, with benefi ts ranging from $38 to $573 per 0.41 ha. Abbreviations: AUDPC, area under disease progress curve; CE, certainty equivalent; DSS, decision support system; FSD, fi rst-degree stochastic dominance; RP, risk premium; net return per 0.41 ha, net return to all costs excluding fungicide cost and application cost per 0.41 ha; SERF, stochastic effi ciency with respect to a function; SSD, second-degree stochastic dominance; SDRF, stochastic dominance with respect to a function. Core ideas• Th e benefi ts of adopting precision farming technology was investivated in scheduling fungicide applications to manage potato late blight.• Th e precision farming technology is the preferred method to schedule fungicide applications in terms of disease suppression, net return per 0.41 ha, and risk-adjusted net return.• Th e increased adoption of the precision farming technology would help manage late blight, limit potential crop losses, and improve net returns.

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“…This was achieved by coupling the ENSO/streamflow relationship with water allocation models used by water resource managers. Ritchie et al (2004) have combined economic, agronomic, hydrological and climatological modelling to assist with plant -area decisions for irrigated cotton farmers in the northern Murray-Darling Basin. Ritchie et al (2004) found that significant gains in gross margin returns can be obtained if farmers manage planting area based on seasonal climate forecasts.…”

Section: Introductionmentioning

confidence: 99%

“…Ritchie et al (2004) have combined economic, agronomic, hydrological and climatological modelling to assist with plant -area decisions for irrigated cotton farmers in the northern Murray-Darling Basin. Ritchie et al (2004) found that significant gains in gross margin returns can be obtained if farmers manage planting area based on seasonal climate forecasts. However, Ritchie et al (2004) also note that a farmer's response to seasonal climate forecasting is strongly influenced by attitude to risk.…”

Section: Introductionmentioning

confidence: 99%

“…Ritchie et al (2004) found that significant gains in gross margin returns can be obtained if farmers manage planting area based on seasonal climate forecasts. However, Ritchie et al (2004) also note that a farmer's response to seasonal climate forecasting is strongly influenced by attitude to risk. Pagano & Garen (2005) review the evolution of the integration of climate information and forecasts into the western United States water supply.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Forecasting water allocations for Bundaberg sugarcane farmers

Everingham¹,

Baillie²,

Inman-Bamber³

et al. 2008

Clim. Res.

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Limited water availability in dry cane growing regions poses a challenge to sugarcane farmers. Water allocations tend to be lower at the beginning of the water season, and are increased during the season when inflows are captured. Probabilistic information reflecting the likelihood of specified increases in water allocation is not available to sugarcane farmers. The present paper describes how seasonal climate forecasts were used to provide this information for the 2001/2002 season as part of a case study involving sugarcane farmers in Bundaberg, Australia. Water allocation forecasts were then supplied to an irrigation simulation scheduling system to provide guidance about when and how much water could be applied. This research was underpinned by a cross-institutional collaboration that engaged industry, extension officers, engineers from the water authority and scientists from agriculture and climatology. The key findings from this investigation were 2-fold: the participatory approach (1) contributed to the development of information needed by industry, and (2) demonstrated the potential usefulness of climate forecasting models, hydrological models and cropping system simulators to contribute to enhancing knowledge about water availability and application. Additional investigations are required before this technology can be operationalised.

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Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance

Cited by 25 publications

References 27 publications

Productive characteristics and water use efficiency in cotton plants under different irrigation strategies

Productive characteristics and water use efficiency in cotton plants under different irrigation strategies

Risk Management Strategies using Precision Agriculture Technology to Manage Potato Late Blight

Forecasting water allocations for Bundaberg sugarcane farmers

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