Amin Asad, Nasim Wajid, Mubeen Muhammad, Nadeem Muhammad, Ali Liaqat, Hammad Hafiz Mohkum, Sultana Syeda Refat, Jabran Khawar, Rehman M Habib Ur, Ahmad Shakeel, Awais Muhammad, Rasool Atta, Fahad Shah, Saud Shah, Shah Adnan Noor, Ihsan Zahid, Ali Shahzad, Bajwa Ali Ahsan, Hakeem Khalid Rehman, Ameen Asif, Rehman Hafeez Ur, Alghabar Fahad, Jatoi Ghulam Hussain, Akram Muhammad, Khan Aziz, Islam Faisal, Ata-Ul-Karim Syed Tahir, Rehmani Muhammad Ishaq Asif, Hussain Sajid, Razaq Muhammad, Fathi Amin
Department of Environmental Sciences, COMSATS Institute of Information Technology (CIIT), Vehari, Pakistan.
CIHEAM-Institut Agronomique Méditerranéen de Montpellier (IAMM), 3191 route de Mende, Montpellier, France.
Environ Sci Pollut Res Int. 2017 Feb;24(6):5811-5823. doi: 10.1007/s11356-016-8311-8. Epub 2017 Jan 4.
Crop nutrient management is an essential component of any cropping system. With increasing concerns over environmental protection, improvement in fertilizer use efficiencies has become a prime goal in global agriculture system. Phosphorus (P) is one of the most important nutrients, and strategies are required to optimize its use in important arable crops like cotton (Gossypium hirsutum L.) that has great significance. Sustainable P use in crop production could significantly avoid environmental hazards resulting from over-P fertilization. Crop growth modeling has emerged as an effective tool to assess and predict the optimal nutrient requirements for different crops. In present study, Decision Support System for Agro-technology Transfer (DSSAT) sub-model CSM-CROPGRO-Cotton-P was evaluated to estimate the observed and simulated P use in two cotton cultivars grown at three P application rates under the semi-arid climate of southern Punjab, Pakistan. The results revealed that both the cultivars performed best at medium rate of P application (57 kg ha) in terms of days to anthesis, days to maturity, seed cotton yield, total dry matter production, and harvest index during 2013 and 2014. Cultivar FH-142 performed better than MNH-886 in terms of different yield components. There was a good agreement between observed and simulated days to anthesis (0 to 1 day), days to maturity (0 to 2 days), seed cotton yield, total dry matter, and harvest index with an error of -4.4 to 15%, 12-7.5%, and 13-9.5% in MNH-886 and for FH-142, 4-16%, 19-11%, and 16-8.3% for growing years 2013 and 2014, respectively. CROPGRO-Cotton-P would be a useful tool to forecast cotton yield under different levels of P in cotton production system of the semi-arid climate of Southern Punjab.
作物养分管理是任何种植系统的重要组成部分。随着对环境保护的日益关注，提高肥料使用效率已成为全球农业系统的首要目标。磷（P）是最重要的养分之一，需要采取策略来优化其在重要的可耕地作物（如棉花（陆地棉））中的使用，这具有重要意义。作物生产中可持续的磷使用可以显著避免因过度施磷造成的环境危害。作物生长模型已成为评估和预测不同作物最佳养分需求的有效工具。在本研究中，对农业技术转移决策支持系统（DSSAT）子模型CSM-CROPGRO-Cotton-P进行了评估，以估算在巴基斯坦旁遮普省南部半干旱气候条件下，三个施磷水平下种植的两个棉花品种的磷使用情况及模拟值。结果表明，在2013年和2014年，就开花天数、成熟天数、籽棉产量、总干物质产量和收获指数而言，两个品种在中等施磷量（57千克/公顷）时表现最佳。在不同产量构成因素方面，品种FH-142比MNH-886表现更好。在2013年和2014年生长季，MNH-886的开花天数（误差为-4.4%至15%）、成熟天数（误差为12%至7.5%）、籽棉产量、总干物质和收获指数的观测值与模拟值之间具有良好的一致性，FH-142的相应误差分别为4%至16%、19%至11%和16%至8.3%。CROPGRO-Cotton-P将是预测旁遮普省南部半干旱气候棉花生产系统中不同磷水平下棉花产量的有用工具。
