‍An empirical analysis of main factors affecting the rice harvest loss based on the ordered multinomial logistic model

WU Linhai1,2 HU Qipeng1 ZHU Dian3 WANG Jianhua2

(1.Research Base for Food Security of Jiangsu Province, Jiangnan University)
(2.Collaborative Innovation Center for Food Security and Nutrition)
(3.Dongwu Business School, Suzhou University)

【Abstract】In this study, the meaning of the rice harvest loss was defined based on previous research on definition of postharvest grain losses and the realities in China. The current rice harvest loss in different areas in China was analyzed based on sampling survey data from 957 farmers in 10 provinces in China. On this basis, the main factors affecting the rice harvest loss and their marginal effects were investigated by using the ordered multinomial logistic model. The survey found that 56.13% of subjects believed that the rice harvest loss was 4% or below in China though there were differences among the provinces. Results revealed that proportion of family business income, the size of production area, level of mechanization, timely harvest, and attitude toward harvest had a negative effect on the rice harvest loss. On the other hand, that whether farmers having experience as migrant workers or not had a positive effect on the rice harvest loss. Moreover, bad weather and being short of hands during harvest significantly increased rice postharvest losses.

【Keywords】 rice; harvest loss; ordered multinomial logistic model; marginal effect;


【Funds】 2015 Special Food Programme for Public Benefits (201513004-6) Fund for Outstanding Innovation Team on Humanities and Social Sciences of Colleges and Universities in Jiangsu Province (2013-011)

Download this article


    [1]. ①The postharvest food loss rate is the ratio of postharvest food loss to total food output. [^Back]

    [2]. ②Source: website of the State Statistics Bureau (http://www.stats.gov.cn). [^Back]

    [3]. ①Because there is no standard definition of food loss and food waste in the academia, and food loss and food waste have not been strictly distinguished due to practical limitations, in order to make the data from China relating to food loss during harvest comparable to overseas data, food loss discussed in this article includes food waste. [^Back]

    [4]. ②If a transverse crack appears on a rice grain, namely, it is cracked. Cracked grains not only show reduced quality, but also will increase broken rice ratio during post production processing. [^Back]

    [5]. ①Harvest methods mainly include combined harvest and multi-stage harvest. Wherein, multi-stage harvest includes reaping, bundling, stacking, collecting, threshing, cleaning, sorting and selecting. [^Back]

    [6]. ②The calculation is conducted using the data from China Statistical Yearbook 2014 (edited by State Statistics Bureau, China Statistics Press, 2014). [^Back]

    [7]. ③It is usually divided into six main rice producing regions in China, i.e. southern China, central China, northern China, south-western China, north-eastern China where rice is produced in one season, and the dry north-western region. [^Back]

    [8]. ①According to literature from China and other countries, a consistent conclusion relating to rice postharvest loss is that rice postharvest loss rates usually are between 3% and 7%. [^Back]

    [9]. ②Rice postharvest loss rate = rice harvest loss per mu / rice output per mu. [^Back]


    [1] Chen, W., Zhou, Q. & Huang, J. Chinese Journal of Rice Science (中国水稻科学), (4) (2006).

    [2] Fei, Y., Chen, L., Peng, G. et al. Jiangsu Agricultural Sciences (江苏农业科学), (5) (2013).

    [3] Feng, G. & Sun, C. Rural Science & Technology (农村科技), (4) (2014).

    [4] Guo, Y., Chen, R. & Guo, J. Agricultural Economy (农业经济), (1) (2014).

    [5] Huang, Y. & Zhang, H. Issues in Agricultural Economy (农业经济问题), (5) (2011).

    [6] Huang, Z., Wang, J. & Chen, Z. Chinese Rural Economy (中国农村经济), (11) (2014).

    [7] Li, G. Chinese Rural Economy (中国农村经济), (5) (2014).

    [8] Li, W. Journal of Hunan Agricultural University (Social Sciences) (湖南农业大学学报(社会科学版)), (5) (2010).

    [9] Li, Z., Xia, P., Wang, Z. et al. Journal of Zhejiang Agricultural University (浙江农业大学学报), (4) (1991).

    [10] Liu, H., Chen, W., Zou, S. et al. Modern Agricultural Equipment (现代农业装备), (1) (2014).

    [11] Song, H., Zhang, H., Li, J. et al., Journal of Huazhong Agricultural University (Social Sciences) (华中农业大学学报(社会科学版)), (4) (2015).

    [12] Zhang, H., Liu, Y. & Chen, X. Farmer’s Guide to Wealth (农民致富之友), (6) (2013).

    [13] Zhang, J., Fu, Z. & Li, D. China Agricultural University Journal of Social Sciences Edition (中国农业大学学报(社会科学版)), (12) (1998).

    [14] Zhang, Y., Chu, Q. & Wang, H. Research of Agricultural Modernization (农业现代化研究), (3) (2009).

    [15]Abass, A. B.; Ndunguru, G.; Mamiro, P.; Alenkhe, B.; Mlingi, N. and Bekunda, M.: Post-harvest Food Losses in a Maize-based Farming System of Semi-arid Savannah Area of Tanzania, Journal of Stored Products Research, 57(4): 49-57, 2014.

    [16]Akar, T.; Avci, M. and Dusunceli, F.: Berley:Post-harvest Operations, Food and Agriculture Organization of the United Nations, Turkey, 2004.

    [17]Appiah, F.; Guisse, R. and Dartey, P. K.: Post-harvest Losses of Rice from Harvesting to Milling in Ghana, Journal of Stored Products and Postharvest Research, 2(4): 64-71, 2011.

    [18]Aulakh, J. and Regmi, A.: Post-harvest Food Losses Estimation-Development of Consistent Methodology, paper submitted to Agricultural & Applied Economics Association’s 2013AAEA & CAES Joint Annual Meeting, Washington DC, 2013.

    [19]Basavaraja, H.; Mahajanashetti, S. B. and Udagatti, N. C.: Economic Analysis of Post-harvest Losses in Food Grains in India: A Case Study of Karnataka, Agricultural Economics Research Review, 20(1): 117-126, 2007.

    [20]Bokusheva, R.; Finger, R.; Fischler, M.; Berlin, R.; Marín, Y.and Pérez, F.: Factors Determining the Adoption and Impact of a Postharvest Storage Technology, IAAE, Brazil, 2012.

    [21]Buchner, B.; Fischler, C.; Gustafson, E.; Reilly, J.; Riccardi, G.; Ricordi, C.and Veronesi, U.: Food Waste: Causes, Impacts and Proposals, Barilla Center for Food & Nutrition, 2012.

    [22]Greene, W. H.: Econometric Analysis, Prentice Hall, New Jersey, 2003.

    [23]Grethe, H.; Dembele, A. and Duman, N.: How to Feed the World's Growing Billions: Understanding FAO World Food Projections and Their Implications, Study for WWF Deutschland and the Heinrich-Böll-Stiftung, Berlin, 2011.

    [24]Gustavsson, J.; Cederberg, C.; Sonesson, U.; Otterdijk, R. V. and Meybeck, A.: Global Food Losses and Food Waste: Extent, Causes and Prevention, Food and Agriculture Organization of the United Nations, Rome, 2011.

    [25]Halloran, A.; Clement, J.; Kornum, N.; Bucatariu, C. and Magid, J.: Addressing Food Waste Reduction in Denmark, Food Policy, 49(1): 294-301, 2014.

    [26]Hodges, R. J.; Buzby, J. C. and Bennett, B.: Postharvest Losses and Waste in Developed and Less Developed Countries: Opportunities to Improve Resource Use, The Journal of Agricultural Science, 149(S1): 37-45, 2011.

    [27]Hodges, R. J. and Maritime, C.: Post-harvest Weight Losses of Cereal Grains in Sub-Saharan Africa, Natural Resources Institute, University of Greenwich, 2012.

    [28]Lantin, R.: Rice: Post-harvest Operations, International Rice Research Institute, Philippines, 1999.

    [29]Liu, G.: Food Losses and Food Waste in China: A First Estimate, OECD Food, Agriculture and Fisheries Papers, 66(1): 3-29, 2014.

    [30]Liu, J.; Folberth, C.; Yang, H.; Röckström, J.; Abbaspour, K. and Alexander, J. B.: A Global and Spatially Explicit Assessment of Climate Change Impacts on Crop Production and Consumptive Water Use. Plus One, 8(2): 1-13, 2013.

    [31]Newell, R. G. and Anderson, S.: Simplified Marginal Effects in Discrete Choice Models, Economics Letters, 81(3): 321-326, 2003.

    [32]Parfitt, J.; Barthel, M. and Macnaughton, S.: Food Waste within Food Supply Chains: Quantification and Potential for Change to 2050, Philosophical Transactions, 365(9): 3065-3081, 2010.

    [33]Priefer, C.; Jörissen, J. and Bräutigam, K. R.: Technology Options for Feeding 10 Billion People. Options for Cutting Food Waste, Institute for Technology Assessment and Systems Analysis, 2013.

    [34]Teshome, A.; Kenneth, T.J.; Bernard, B.; Lenore, F. and Lambert, D. H.: Traditional Farmers’ Knowledge of Sorghum Landrace Storability in Ethiopia, Economic Botany, 53(1): 69-78, 1999.

    [35]World Bank; FAO and NRI: Missing Food: The Case of Post-harvest Grain Losses in Sub-Saharan Africa, World Bank, Washington DC, 2011.

    [36]WRAP: New Estimates for Household Food and Drink Waste in the UK, Waste and Resources Action Program, Bradbury, UK, 2011.

    [37]Zhejiang Academy of Agricultural Sciences: Grain Post-production System Analysis in China: Terminal Report, Zhejiang Academy of Agricultural Sciences, Postharvest Development Research Center, Hangzhou, China, 1991.

This Article


CN: 11-3586/F

Vol , No. 06, Pages 22-33+95

November 2015


Article Outline


  • 1 Introduction
  • 2 Literature review and definitions
  • 3 Survey designs and the sample analysis
  • 4 Theoretical model and variable setting
  • 5 Estimation results from the model and discussions
  • 6 Conclusion
  • Footnote