Effects of Deficit Drip Irrigation Ratios on Cotton (<i>Gossypium hirsutum</i> L.) Yield and Fibre Quality

Başal, Hüseyin; Dağdelen, Necdet; Ünay, Aydın; Yılmaz, Ersel

doi:10.1111/j.1439-037x.2008.00340.x

Cited by 115 publications

(130 citation statements)

References 36 publications

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“…Cotton responses to deficit irrigation have been reported in some earlier works (Wanjura et al, 2002;Howell et al, 2004;Pettigrew, 2004;Dagdelen et al, 2006;DeTar, 2008;Basal et al, 2009). When adopting deficit irrigation, it is difficult to predict the yield re-Simulating cotton response to deficit irrigation with AquaCrop minimum and maximum temperature, dew point, wind velocity at 2 m, solar radiation, and rainfall.…”

Section: Introductionmentioning

confidence: 99%

Simulating cotton yield response to deficit irrigation with the FAO AquaCrop model

Hussein

Janat

Yakoub

1970

Span. j. agric. res.

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The Food and Agriculture Organization has reflected the importance of predicting yield response to water by developing the AquaCrop model. During three growing seasons (2007)(2008)(2009)), a field experiment was conducted in the South-East of Damascus (Syria) to assess the response of drip irrigated cotton grown under full (FI) and deficit irrigation (80, 65, 50% of FI). Input data and comparisons between simulated and observed canopy cover (CC), biomass production at harvesting, final seed cotton yield, and soil water content using data sets of the 2007 season, were used for model calibration. The calibrated model was validated using data sets of the 2008 and 2009 seasons, getting accurate simulation results for CC [root mean square error (RMSE) = 6.5%] and actual evapotranspirationETa (RMSE = 25 mm, index of agreement = 0.99). The predicted seed cotton yields were within 6% of measurements. The model predictions of soil water content in the 0.60 m profile were close in the general trend to the measurements. In spite of the good prediction of ETa and seed cotton yield for each treatment, there is an apparent tendency for AquaCrop to over-estimate water use efficiency (WUE) under water-deficit conditions. Therefore, in cases of limited input data, the AquaCrop could be a promising model for estimating crop productivity under deficit irrigation conditions. Additional key words: canopy cover; crop yield modeling; water productivity; water stress. ResumenSimulación de la respuesta del rendimiento del algodón al riego deficitario con el modelo AquaCrop de la FAO Por lo importante que es predecir la respuesta del rendimiento al riego, la FAO ha desarrollado el modelo AquaCrop. Se llevó a cabo durante tres temporadas (2007-2009) un experimento de campo en el sureste de Damasco (Siria) para evaluar la respuesta del algodón cultivado con riego por goteo, bajo riego total (FI) y deficitario (80, 65, 50% del FI). Para la calibración del modelo se utilizaron los datos input y las comparaciones entre los valores simulados y observados de cobertura del dosel (CC), producción de biomasa en la cosecha, rendimiento final de semilla de algodón, y contenido de agua en el suelo, utilizando conjuntos de datos de la temporada 2007. Se validó el modelo calibrado utilizando conjuntos de datos de las temporadas 2008 y 2009, obteniéndose resultados precisos de simulación para CC [error cuadrático medio (RMSE) = 6,5%] y la evapotranspiración real ETa (RMSE =25 mm; índice de concordancia = 0,99). Los rendimientos de semilla previstos estuvieron dentro del 6% de las mediciones. Las predicciones del modelo para el contenido de agua en el perfil de 0,60 m se acercaron a la tendencia general de las mediciones. A pesar de la buena predicción de la ETa y del rendimiento de las semillas para cada tratamiento, hay una clara tendencia de AquaCrop a sobreestimar el uso eficiente del agua (WUE) en condiciones de déficit hídrico. Por lo tanto, en los casos de datos input limitados, el AquaCrop podría ser un modelo prometedor para estimar la p...

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Section: Introductionmentioning

confidence: 99%

Simulating cotton yield response to deficit irrigation with the FAO AquaCrop model

Hussein

Janat

Yakoub

1970

Span. j. agric. res.

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“…High fiber quality is essential for textile industry because it affects the quality of final products and the processing performance, with impact on processing cost and branding/marketing of the products (Basal et al, 2009a). ISSN 2166-0379 2017 In cotton, the effect of GxE varies among fiber traits, which means that certain fiber traits are more sensitive to environmental changes than others.…”

Section: Discussionmentioning

confidence: 99%

“…Fiber quality is a complex of various traits, such as fiber length, strength, uniformity etc. (Poehlman and Sleper, 1995) and thus it depends on both genetic and environmental factors that influence the plant's development (Bradow and Davidonis, 2000;Campbell and Jones, 2005;Basal et al, 2009a;Kothari et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Genotype by Environment Interactions on Cotton Fiber Traits and Their Implications on Variety Recommendation

Greveniotis

Sioki²

2017

JAS

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The objective of this study was to evaluate cotton fiber quality traits across diverse environments. This could lead to the selection of the best environment for cotton cultivations and the best adapted commercial cultivars. For this reason four main cotton regions were chosen as different environments: Thessaly, Thrace, Macedonia and Sterea Ellas. Five of the most commercial upland cotton cultivars (DP332, DP377, ST402, CELIA and ELSA) were used for evaluation of their fiber quality traits. Each cultivar was sown in 10 different fields (in order to exploit and evaluate different soil types) in each of the above mentioned regions and (in total) 200 fields were used in total. Four samples from each field were collected in order to analyze fiber quality traits: micronaire, maturity index (%), fiber length as the upper half mean length (mm), fiber strength (gram/tex), uniformity index (%), fiber elongation, Cultivation regions must also be selected in a way that they could promote fiber traits, in order to ensure the highest fiber quality. Cotton fiber quality traits were affected differently from environmental fluctuations, showing that the ranking of cultivars according to environmental fluctuations is important, if proper breeding methods should be applied. Each trait is affected differently by environmental fluctuations and requires precise knowledge of the degree of inheritance i.e., as to how much qualitative or quantitative is the trait, in order to choose and apply the proper breeding method.

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“…They observed that irrigation improved ginning percentage and increased yield, and the fiber quality parameters such as the length, micronaire, and uniformity were affected by the irrigation regimes. In a research by Basal Dagdelen, Unay, and Yilmaz (2009), it was showed that deficit irrigation of cotton with drip irrigation at 75% level did not decrease seed cotton yield and there was no significant differences in fiber length, fineness, uniformity, and elongation between the 100% and 75% irrigation levels. Whitaker, Ritchie, Bednarz, and Mills (2008) reported that non-irrigated cotton matured earlier than the irrigated.…”

Section: Introductionmentioning

confidence: 97%

Effect of Supplemental Irrigation and Graded Levels of Nitrogen on Cotton Yield and Quality

Sui¹,

Byler²,

Fisher³

et al. 2014

JAS

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Effects of supplemental irrigation and graded levels of nitrogen (N) on cotton yield and fiber quality were investigated in the Mississippi Delta in 2011 and 2012. Cotton was planted in 48 experimental plots with irrigation as main treatment unit and N application rate (0, 39, 67, 101, 135, and 168 kg ha -1 ) as subunit. Supplemental irrigation was conducted based on soil-water sensor measurements. Cotton yield was determined using a boll buggy equipped with load cells. Cotton samples were collected and ginned, and the fiber quality was evaluated. Statistical analyses on the effects of irrigation and leaf N on the yield and fiber quality indicated that compared with non-irrigated cotton, the irrigated cotton increased seed cotton yield by 14%. Leaf N content varied in a range of 3.27% to 5.86% with an average of 4.34%. Leaf N of irrigated plants was 9.0% and 3.6% higher than that of the non-irrigated plants in 2011 and 2012, respectively. Soil water stress had a negative effect on N uptake of cotton plants. Yield showed a positive linear correlation with leaf N content in both irrigated and non-irrigated plots. Irrigation improved fiber quality, including all fiber length parameters. Upper half mean length (UHML) of cotton fiber in irrigated treatment was 2.7% and 1.8% greater than that in the non-irrigated treatment in 2011 and 2012, respectively. Micronaire decreased, and neps and yellowness increased with the increase of leaf N under irrigated and non-irrigated conditions. Excessive application of N would not be beneficial to fiber quality and could possibly create negative impact on some properties of cotton fibers.

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Effects of Deficit Drip Irrigation Ratios on Cotton (Gossypium hirsutum L.) Yield and Fibre Quality

Cited by 115 publications

References 36 publications

Simulating cotton yield response to deficit irrigation with the FAO AquaCrop model

Simulating cotton yield response to deficit irrigation with the FAO AquaCrop model

Genotype by Environment Interactions on Cotton Fiber Traits and Their Implications on Variety Recommendation

Effect of Supplemental Irrigation and Graded Levels of Nitrogen on Cotton Yield and Quality

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