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Production efficiency and effect of water management on rice yield in Japan: two-stage DEA model on 110 paddy fields of a large-scale farm

Production efficiency and effect of water management on rice yield in Japan: two-stage DEA model... Keywords Koshihikari · Slack analysis · Technical efficiency · Tobit regression · Water depth · Water temperature Japan, Koshihikari accounts for approximately 36% of the Introduction total domestic planting area (Komenet 2016). Prior studies on the determinants of rice yield using In Japan, the production of rice (Oryza sativa L.) needs overseas field-level on-farm data include Abdullah and Ali to improve the efficiency and competitiveness, confront- (2014), Barrett et al. (2010) and Kozak et al. (2007). Studies ing the decreases in gross production and high costs of using the experimental data sampled in Japan include Hirai the inputs, and challenges in the TPP era (Nanseki et al. et al. (2012). In our prior study, we analyzed the determi- 2016). In 2014, the production of sorted brown rice was nants of Koshihikari, using the data from a large-scale farm 8.43 × 10   t, 40% lower than the 1985 production of in the Kanto Region of Japan (Li et al. 2016). However, 11.83 × 10  t (MAFF 2016a). In 2013, the average pro- we have not found similar studies, sampling field-level on- duction cost of sorted rice in Japan was 258 Japanese Yen farm data in Japan. In this study, we continue our previous (JPY) per kg (MAFF 2016b). The http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Paddy and Water Environment Springer Journals

Production efficiency and effect of water management on rice yield in Japan: two-stage DEA model on 110 paddy fields of a large-scale farm

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References (19)

Publisher
Springer Journals
Copyright
Copyright © 2018 by The International Society of Paddy and Water Environment Engineering and Springer Japan KK, part of Springer Nature
Subject
Life Sciences; Agriculture; Hydrology/Water Resources; Hydrogeology; Geoecology/Natural Processes; Ecotoxicology; Soil Science & Conservation
ISSN
1611-2490
eISSN
1611-2504
DOI
10.1007/s10333-018-0652-0
Publisher site
See Article on Publisher Site

Abstract

Keywords Koshihikari · Slack analysis · Technical efficiency · Tobit regression · Water depth · Water temperature Japan, Koshihikari accounts for approximately 36% of the Introduction total domestic planting area (Komenet 2016). Prior studies on the determinants of rice yield using In Japan, the production of rice (Oryza sativa L.) needs overseas field-level on-farm data include Abdullah and Ali to improve the efficiency and competitiveness, confront- (2014), Barrett et al. (2010) and Kozak et al. (2007). Studies ing the decreases in gross production and high costs of using the experimental data sampled in Japan include Hirai the inputs, and challenges in the TPP era (Nanseki et al. et al. (2012). In our prior study, we analyzed the determi- 2016). In 2014, the production of sorted brown rice was nants of Koshihikari, using the data from a large-scale farm 8.43 × 10   t, 40% lower than the 1985 production of in the Kanto Region of Japan (Li et al. 2016). However, 11.83 × 10  t (MAFF 2016a). In 2013, the average pro- we have not found similar studies, sampling field-level on- duction cost of sorted rice in Japan was 258 Japanese Yen farm data in Japan. In this study, we continue our previous (JPY) per kg (MAFF 2016b). The

Journal

Paddy and Water Environment – Springer Journals

Published: Sep 6, 2018

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