Evaluation of forage maize yield gap using an integrated crop simulation model-satellite imagery method (Case study: four watershed basins in Golestan Province). Issue 2 (28th January 2019)

• Record Type: Journal Article
• Authors: Pourhadian, Hossein; Kamkar, Behnam; Soltani, Afshin; Mokhtarpour, Hassan
• Is Part Of: Archives of agronomy and soil science. Volume 65:Issue 2(2019)
• Page Start: 253
• Page End: 268
• Publication Date: 2019-01-28
• Subjects: GIS -- maize -- NDVI -- solar radiation -- yield gap; Horticulture -- Periodicals; Soils -- Periodicals; 630.5
• DOI: 10.1080/03650340.2018.1493579
• Languages: English
• ISSNs: 0365-0340

Abstract

ABSTRACT: The yield gap provides a guide for prioritization of crop management options (such as optimized sowing date, seeding rate, irrigation schedule, soil fertility, fertilizer application, weed and pest control) in a studied area. This study aimed to determine the maize yield gap in four major watersheds in Golestan Province, Iran, using an integrated crop simulation model-satellite imagery method. The actual yield estimated by the NDVI (as the selected index) was between 8.89 and 20.40 t ha −1, while the potential yield is between 19.03 and 22.35 t ha −1 . About 91.76% of the studied area had a yield less than 85% of the potential yield. The lowest actual yield was in the south, southeast, and north of the study area. The yield gap was estimated between 0 to 11.76 t ha −1 and 66.66% of maize farms yield gap was between 3.5 to 5.5 t ha −1 . The yield gap fraction changed between 0 and 0.57. The results showed that soil-dependent variables, slope, and fluctuation in farm management factors (plant density, planting, irrigation, and various methods of weed control) caused the yield gap. High yield gap indicates that there is an opportunity to increase production through managerial optimization or excluding maize from cropping patterns.