Effect of rainfall on productivity of cotton
DOI:
https://doi.org/10.31783/elsr.2020.615663Keywords:
rainfall variability, cotton productivity, standard meteorological correlation, regressionAbstract
Study of rainfall and its effect on crop yield is very useful for crop planning for rainfed cash crop like cotton for farmers and policy makers in rainfed agriculture. A study was conducted to evaluate rainfall variability and its effect on Cotton yield for Junagadh district of Gujarat for seasonal, monthly, fortnightly and weekly rainfall by correlation & regression analysis. Arithmetic mean, standard deviation and coefficient of variation for seasonal rainfall was found as 982 mm, 349 mm and 36 % respectively. July month contributes about 40% of the total seasonal rainfall. Correlation coefficient between seasonal rainfall and yield was 0.66, while it was highest as 0.46 for September and lowest as 0.15 for August. For fortnightly rainfall, the highest correlation coefficient was founded as 0.64 for Fifth Fortnight (5F) and negative -0.27 for 1F. 31st Standard Meteorological Week (SMW) recorded highest correlation 0.65. The regression analysis revealed that predictability for seasonal, monthly and fortnightly rainfall was 43%, 55% and 84 % respectively, while it was 96% for weekly rainfall. 5 FN and 31st SMW were found most substantial in all above parameters.
References
[1]. F. Ndamani and W. Tsunemi (2015). Influences of rainfall on crop production and suggestions for adaptation. Int. J. of Agric. Sci., 5: 367-374.
[2]. P. K. Singh, L. S. Rathore, K. K. Singh, A. K. Baxla and B. Athiyaman (2008). Incomplete gamma distribution of rainfall for sustainable crop production strategies at Palampur, Himachal Pradesh. Mausam, 60: 73-80.
[3]. I. R. Ajayi, M. O. Afolabi, E. F. Ogunbodede and G. Sunday (2010). Modeling rainfall as a constraining factor for cocoa yield in ondo state. Am. J. Sci. Ind. Res., 1: 127-134.
[4]. J. H. Hammond (2006). Cotton is king, speech by Senate of South Carolina before United States senate, Teaching American History, pp311-322.
[5]. B. Sultan, M. B.-Medjo, A. Berg, P. Quirion and S. Janicot (2010). Multi-scales and multi-sites analyses of the role of rainfall in cotton yields in West Africa. Int. J. Climatol., 30: 58-71.
[6]. P. Gwimbi and T. Mundoga (2010). Impact of climate change on cotton production under rainfed conditions: case of Gokwe. J. Sustain. Dev. Afr., 12: 59-69.
[7]. Z. M. Adare, A. Srinivas, P. V. Rao, T. R. Prakash and T. R. Thatikunta (2016). Association of weather variables with yield and yield components of cotton (Gossypium hirsutun L.) at reproductive phenophase. Afr. J. Agric. Res., 11: 2555-2561.
[8]. V. Prasanna (2014). Impact of monsoon rainfall on the total foodgrain yield over India. J. of Earth Sys. Sci., 123:1129-1145
[9]. K. J. Duffy and T. P. Masere (2015). Effect of within-season daily rainfall distribution on maize crop yields. Outlook on Agric., 44: 1-5.
[10]. A. Shikha, P. Maharana, K. K. Singh and A. P. Dimri (2018). Cotton crop in changing climate. Current Sci., 115: 948-954.
[11]. D. W. Parvin, S. W. Martin, F. Cooke and B. B. Freeland (2005). Effect of harvest season rainfall on cotton yield. The J. Cotton Sci., 9: 115-120.
[12]. P. K. Singh, L. S. Rathore, K. K. Singh, A. K. Baxla and B. Athiyaman (2008). Incomplete gamma distribution of rainfall for sustainable crop production strategies at Palampur, Himachal Pradesh. Mausam, 60: 73-80.
[13]. N. J. Rankja, S. M. Upadhyay, H. R. Pandya and B. A. Parmar (2010). Estimation of cotton yield based on weather parameters of Banaskantha district in Gujarat state. J. of Agrometeorol., 12: 47-52.
[14]. D. A. Loka and D. M. Oosterhuis (2012). Water stress and reproductive development in cotton. Department of Crop, Soil, and Environmental Sciences University of Arkansas, Fayetteville, AR 72704 (2012).
[15]. D. Abdoulaye, B. Bruno, Z. Beteo and Y. Hamma (2017). Impact of climate change on cotton production in Burkina Faso. Afr. J. Agr. Res., 12: 494-501.
[16]. P. S. Adhikari, J. P. Ale, K. R. Brodsky, N. R.Thorp, N. R. Modala and E. M. Barnes (2016). Simulating future climate change impacts on seed cotton yield in the Texas High Plains using the CSM‐CROPGRO‐Cotton model. Agr. Water Manage., 164: 317-330.
[17]. H. S. Thakare, P. K. Shrivastava and B. Kirti (2014). Impact of weather parameters on cotton productivity at Surat (Gujarat), India. J. of Appl.and Natural Sci., 6: 599-604.
[18]. R. Singh, D. Ganga, D. J. Parmar and S. Mishra (2017). Impact of rainfall and temperature on the yield of major crops in Gujarat state of India: a panel data analysis (1980-2011). Current J. Appl. Sci. Tech., 24: 1-9.
[19]. M. Ratnam, S. Rajamani and E. Narayana (2014). Seasonal weather behavior on cotton in the Guntur district of Andhra Pradesh. Int. J. Pure App. Biosci., 2: 275-275.
[20]. N. J. Rankja, S. M. Upadhyay and S. L. Varmora (2009). Forecasting model for cotton yield based on generated weather variables of Ahmedabad district in Gujarat state. J. Agrometeorol, 11: 183-188.
[21]. R. S. Parmar (2013). Influence of rainfall distribution on the productivity of groundnut in Bhavnagar district of Gujarat state. Int. J. of Agric. Sci. and Vet Med., 1: 2320-3730.
[22]. P. A. Pandya, H. H. Mashru, R. J. Patel and H. D. Rank (2019). Rainfall variations and its correlation with groundnut productivity. Int. J. Multi. Res. Dev., 6: 87-90.
Downloads
Published
Issue
Section
License
Copyright (c) 2020 Author (s)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright © The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author(s) and source are properly credited, and the work is not modified or adapted.
