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Optimizing irrigation and nitrogen requirements for maize through empirical modeling in semi-arid environment.
- Source :
- Environmental Science & Pollution Research; Jan2019, Vol. 26 Issue 2, p1227-1237, 11p
- Publication Year :
- 2019
-
Abstract
- Uncertainty in future availability of irrigation water and regulation of nutrient amount, management strategies for irrigation and nitrogen (N) are essential to maximize the crop productivity. To study the response of irrigation and N on water productivity and economic return of maize (Zea mays L.) grain yield, an experiment was conducted at Water Management Research Center, University of Agriculture Faisalabad, Pakistan in 2015 and 2016. Treatments included of full and three reduced levels of irrigation, with four rates of N fertilization. An empirical model was developed using observed grain yield for irrigation and N levels. Results from model and economic analysis showed that the N rates of 235, 229, 233, and 210 kg ha<superscript>−1</superscript> were the most economical optimum N rates to achieve the economic yield of 9321, 8937, 5748, and 3493 kg ha<superscript>−1</superscript> at 100%, 80%, 60%, and 40% irrigation levels, respectively. Economic optimum N rates were further explored to find out the optimum level of irrigation as a function of the total water applied using a quadratic equation. The results showed that 520 mm is the optimum level of irrigation for the entire growing season in 2015 and 2016. Results also revealed that yield is not significantly affected by reducing the irrigation from full irrigation to 80% of full irrigation. It is concluded from the study that the relationship between irrigation and N can be used for efficient management of irrigation and N and to reduce the losses of N to avoid the economic loss and environmental hazards. The empirical equation can help farmers to optimize irrigation and N to obtain maximum economic return in semi-arid regions with sandy loam soils. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09441344
- Volume :
- 26
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Environmental Science & Pollution Research
- Publication Type :
- Academic Journal
- Accession number :
- 134137618
- Full Text :
- https://doi.org/10.1007/s11356-018-2772-x