Large scale assessment of the production process and rice yield gap analysis by comparative performance analysis and boundary-line analysis methods

Gorjizad, A.; Dastan, S.; Soltani, A.; Ajam Norouzi, H.

Italian Journal of Agronomy 14(2): 123-131


ISSN/ISBN: 1125-4718
DOI: 10.4081/ija.2019.1174
Accession: 068492230

Download citation:  

Article/Abstract emailed within 0-6 h
Payments are secure & encrypted
Powered by Stripe
Powered by PayPal

To reduce the yield gap, specifying yield constraints in a particular area is necessary. A complete yield gap assessment method must provide information regarding potential yield, actual yield, and causes of the gap and their importance. Therefore, documenting the production process to explain crop management factors in each area is very important. The objective of the study was to perform a rice yield gap analysis by using comparative performance analysis (CPA) and boundary-line analysis (BLA). Data were gathered from about 100 paddy fields in Neka, eastern Mazandaran province, one of the major rice producing regions in Iran, in 2015 and 2016. All agricultural practices from nursery preparation to harvest have been recorded for improved rice cultivars. Cpa focuses on the ability to estimate potential yield and the reason for a yield gap. Boundary lines were fitted to the edge of the data cloud of crop yield versus management variables in data from paddy fields monitoring. The documenting analysis shows that the range of paddy yield in 100 fields varied from 6100 to 8200 kg haâ€"1. Potential yields were 9241 kg haâ€"1 for Cpa method, and 7999 kg haâ€"1 for Bla method. Furthermore, yield gap predicted 2047 kg haâ€"1 for Cpa method and 874 kg haâ€"1 for Bla method. In BLA, the average relative yield and relative yield gap of the 13 investigated variables were 89.75% and 10.25% respectively. These results show the importance of each management factor in yield gap. It was concluded that Cpa and Bla as applied in the study is a cheap and simple method that, without the need for expensive experimentation, is able to detect yield gap and its causes in a district. From these results, it can be said that the calculated yield gap is close to the definition given for the utilised yield gap and shows the difference between the actual yield and attainable yield in relation to the environmental conditions of the region.