Abstract
Reducing food loss and waste has recently become an important aspect of ensuring China’s national food security. Because of the importance of household grain storage, the government of China implemented the Scientific Grain Storage Project (SGSP) to encourage farmers to adopt advanced storage facilities (mainly metal silos for rice storage). Based on survey data of 1159 households in 21 provinces, we first analysed the factors that affect farmers’ adoption of metal silos and then used Propensity Score Matching method to assess the impact of metal silos on household rice storage and storage losses. The number of years of schooling, religious beliefs of household decision makers, family size, annual net income, Cooperative membership, planting area, and awareness of grain saving practices were significantly correlated with household decisions on the adoption of metal silos. Metal silos significantly extended the duration of rice storage by households by 18 days, reduced rice storage losses by 43% from 1.6% to 0.7% of output, and protected rice from rodent damage during storage. Promoting the adoption of metal silos by farmers is important for ensuring China’s food security. The adoption of metal silos can increase the supply of rice by 626,800 t per year; save 86,600 ha of land, 29,400 t of fertilizer, and 0.82 billion m3 of water; reduce carbon emissions by 232,200 t, and meet the food consumption needs of 1.39 million people per year. The government should continue the SGSP scheme and encourage farmers to adopt advanced storage facilities.

Similar content being viewed by others

Notes
National Food and Strategic Reserves Administration. 2009. “Guidance on the implementation of reduce post-harvest loss project” (in Chinese), http://www.lswz.gov.cn/html/ywpd/hykj/2018-06/11/content_210676.shtml.
Metal silos are only one major type of facility promoted by the Scientific Grain Storage Project. Other facilities include steel framework warehouses and metal mesh warehouses. However, compared to metal silos, the other facilities are used less frequently. In the Scientific Grain Storage Project, more than 90% of farmers adopt metal silos. These facilities are often airtight and hermetic.
National Food and Strategic Reserves Administration. 2009. “Measures for the on farm scientific grain storage” (in Chinese), http://www.gov.cn/gzdt/2009-06/24/content_1348773.htm.
Nearest neighbour matching matches a subject from the control group to a subject in the treatment group based on the closest propensity score. In kernel matching, each subject in the treatment group is matched to weighted averages of individuals with similar propensity scores, and greater weight is given to people with closer scores. Radius matching uses a tolerance level of the maximum propensity score distance between a subject in the treatment group and all individuals in the control group who are within that distance (Caliendo & Kopeinig, 2008).
This survey covered wheat, rice, maize, soybean, rapeseed, groundnut, potato and sweet potato. We selected all rice samples.
Data source: National Bureau of Statistics (CN), http://data.stats.gov.cn/.
Data from China’s main rice-producing areas (four provinces and eight counties) show that the rice loss rate at storage stage were 1.21% (Lu et al., 2019).
Our survey results show that the farmers believed that rodent damage is the major cause of storage loss. On average, each farmer lost 17.02 kg of rice during storage; the loss of 10.40 kg was due to rodent damage, the loss of 3.63 kg was due to insects or pests, and the loss of 3.00 kg was caused by mildew. Hence, in this study, we particularly focused on the impact of metal silos on rodent damage.
References
African Postharvest Losses Information System. (2018). The African Postharvest Losses Information System. www.aphlis.net.
Becker, S. O., & Ichino, A. (2002). Estimation of average treatment effects based on propensity scores. Stata Journal, 2(4), 358–377.
Bellemare, M. F., Çakir, M., & Peterson, H. H. (2017). On the measurement of food waste. American Journal of Agricultural Economics, 99(5), 1148–1158.
Beretta, C., Stoessel, F., & Baier, U. (2013). Quantifying food losses and the potential for reduction in Switzerland. Waste Management, 33(3), 764–773.
Cai, J. P., Bai, X. G., & Huang, S. X. (2001). Technology of reducing households' grain storage loss. Grain Storage, 5, 32–36 (In Chinese).
Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31–72.
Cao, F. F., Zhu, J. F., Guo, Y., Liu, J. L., & Wu, L. P. (2018). Wheat harvest loss in China: Based on experiments and surveys in 5 cities of 4 provinces. Journal of Arid Land Resources and Environment, 32(07), 7–14 (In Chinese).
Chegere, M. J. (2018). Post-harvest losses reduction by small-scale maize farmers: The role of handling practices. Food Policy, 77, 103–115.
Chegere, M. J., Lokina, R., & Mwakaje, A. G. (2020). The impact of hermetic storage bag supply and training on food security in Tanzania. Food Security, 12(6), 1299–1316.
Chen, X. J., Wu, L. H., Shan, L. J., & Zang, Q. X. (2018). Main factors affecting post-harvest grain loss during the sales process: A survey in nine provinces of China. Sustainability, 10(3), 661.
Chen, X. W. (2009). Review of China's agricultural and rural development: Policy changes and current issues. China Agricultural Economic Review, 1(2), 121–135.
Cheng, J., Yang, G., & Xiang, J. (2017). The impact of the universal two-child policy on China's medium and long term food security. Issues in Agricultural Economy, 38(12), 8-16+110. (In Chinese).
Cheng, K., Yan, M., Nayak, D., Pan, G. X., Smith, P., Zheng, J. F., & Zheng, J. W. (2015). Carbon footprint of crop production in China: An analysis of national statistics data. Journal of Agricultural Science, 153(03), 422–431.
Christiansen, F. (2009). Food security, urbanization and social stability in China. Journal of Agrarian Change, 9(4), 548–575.
Diprete, T. A., & Gangl, M. (2004). Assessing bias in the estimation of causal effects: Rosenblum bounds on matching estimators and instrumental variables estimation with imperfect instruments. Sociological Methodology, 34(1), 271–310.
FAO. (2011). Global food losses and food waste-extent, causes and prevention. FAO.
Fukase, E., & Martin, W. (2016). Who will feed China in the 21st century? Income growth and food demand and supply in China. Journal of Agricultural Economics, 67(1), 3–23.
Gao, L. W., Xu, S. W., Li, Z. M., Chen, S. K., Yu, W., Zhang, Y., Li, D., Wang, Y., & Wu, C. (2016). Main grain crop postharvest losses and its reducing potential in China. Transactions of the Chinese Society of Agricultural Engineering, 32(23), 1–11 (In Chinese).
Ghose, B. (2014). Food security and food self-sufficiency in China: From past to 2050. Food and Energy Security, 3(2), 85–96.
Gitonga, Z. M., De Groote, H., & Kassie, M. (2013). Impact of metal silos on households’ maize storage, storage losses and food security: An application of a propensity score matching. Food Policy, 43, 44–55.
Guo, Y. W., & Wang, D. (2015). Survey on grain storage losses caused by rodents in rural China. China Plant Protection, 35(3), 32–35 (In Chinese).
Heckman, J. J., Ichimura, H., & Todd, P. E. (1997). Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme. The Review of Economic Studies, 64(4), 605–654.
Huang, J. K., & Yang, G. L. (2017). Understanding recent challenges and new food policy in China. Global Food Security-Agriculture Policy Economics and Environment, 12, 119–126.
Huang, J. K., Wei, W., Cui, Q., & Xie, W. (2017). The prospects for China's food security and imports: Will China starve the world via imports. Journal of Integrative Agriculture, 16(12), 2933–2944.
Kadjo, D., Ricker-Gilbert, J., Abdoulaye, T., Shively, G., & Baco, M. N. (2018). Storage losses, liquidity constraints, and maize storage decisions in Benin. Agricultural Economics, 49(4), 435–454.
Kaminski, J., & Christiaensen, L. (2014). Post-harvest loss in sub-Saharan Africa—What do farmers say? Global Food Security, 3, 149–158.
Kanashiro, P., & Rivera, J. (2019). Do chief sustainability officers make companies greener? The moderating role of regulatory pressures. Journal of Business Ethics, 155(3), 687–701.
Kassie, M., Shiferaw, B., & Muricho, G. (2011). Agricultural technology, crop income, and poverty alleviation in Uganda. World Development, 39(10), 1784–1795.
Kumar, D., & Kalita, P. (2017). Reducing postharvest losses during storage of grain crops to strengthen food security in developing countries. Foods, 6(1), 8.
Lee, W. S. (2013). Propensity score matching and variations on the balancing test. Empirical Economics, 44(1), 47–80.
Li, Y. S. (2013). Self-selection, migration, and children educational performance-evidence from an underdeveloped province in rural China. China Economic Quarterly, 12(3), 1027–1050 (In Chinese).
Liu, J. G. (2013). Food losses and waste in China and their implication for water and land. Environmental Science & Technology, 47(18), 10137–10144.
Lu, S. J., Liu, X. J., Xu, L., Tang, Z. C., Liu, G., & Chen, G. Y. (2019). Addressing the losses and waste of Chinese rice supply chain: Sources, drivers and mitigation strategies. Scientia Agricultura Sinica, 52(18), 3134–3144 (In Chinese).
Majumder, S., Bala, B. K., Arshad, F. M., Haque, M. A., & Hossain, M. A. (2016). Food security through increasing technical efficiency and reducing postharvest losses of rice production systems in Bangladesh. Food Security, 8(2), 361–374.
Ministry of Agriculture and Rural Affairs of the People’s Republic of China. (2008). The NationalAgricultural Production Plan of Area (2008~2015). http://www.moa.gov.cn/nybgb/2008/djiuq/201806/t20180611_6151652.htm. (In Chinese).
Minten, B., Beyene, S. T., & Reardon, T. (2020). Post-harvest losses in rural-urban value chains: Evidence from Ethiopia. Food Policy, 98, 101860. https://doi.org/10.1016/j.foodpol.2020.101860.
Mori-Clement, Y. (2019). Impacts of CDM projects on sustainable development: Improving living standards across Brazilian municipalities? World Development, 113, 222–236.
National Development and Reform Commission. (2018). Cost-benefit data of agricultural products (2017). China Statistics Press (In Chinese).
National Food and Strategic Reserves Administration. (2009a). Guidance on the implementation of reduce post-harvest loss project. http://www.lswz.gov.cn/html/ywpd/hykj/2018-06/11/content_210676.shtml. (In Chinese).
National Food and Strategic Reserves Administration. (2009b). Measures for the on farm scientific grain storage. http://www.gov.cn/gzdt/2009-06/24/content_1348773.htm. (In Chinese).
Ndegwa, M. K., De Groote, H., Gitonga, Z. M., & Bruce, A. Y. (2016). Effectiveness and economics of hermetic bags for maize storage: Results of a randomized controlled trial in Kenya. Crop Protection, 90, 17–26.
Ognakossan, K. E., Affognon, H. D., Mutungi, C. M., Sila, D. N., Midingoyi, S. K. G., & Owino, W. O. (2016). On-farm maize storage systems and rodent postharvest losses in six maize growing agro-ecological zones of Kenya. Food Security, 8(6), 1169–1189.
Parfitt, J., Barthel, M., & Macnaughton, S. (2010). Food waste within food supply chains: Quantification and potential for change to 2050. Philosophical Transactions of the Royal Society of London, 365(1554), 3065–3081.
Park, A. (2006). Risk and household grain management in developing countries. Economic Journal, 116(514), 1088–1115.
Ricker-Gilbert, J., & Jones, M. (2015). Does storage technology affect adoption of improved varieties in Africa? Insights from Malawi’s input subsidy program. Food Policy, 50, 92–105.
Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. American Statistician, 39(1), 33–38.
Sheahan, M., & Barrett, C. B. (2017). Review: Food loss and waste in sub-Saharan Africa. Food Policy, 70, 1–12.
Sun, S. K., Wang, Y. B., Liu, J., & Wu, P. T. (2016). Quantification and evaluation of water footprint of major grain crops in China. Journal of Hydraulic Engineering, 47(09), 1115–1124 (In Chinese).
Tesfaye, W., & Tirivayi, N. (2018). The effect of improved storage innovations on food security and welfare in Ethiopia. Food Policy, 75, 52–67.
Wang, H., Chen, Z. P., & Wu, X. Y. (2019). Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? -empirical analysis based on the PSM-DID method. Energy Policy, 129, 930–938.
Zhu, L. (2011). Food security and agricultural changes in the course of China's urbanization. China & World Economy, 19(2), 40–59.
Acknowledgements
We acknowledge the financial support from the special project on non-profit grain industry research, “Research on Investigation and Assessment Techniques for Post-Harvest Grain Loss and Waste” programme, supported by the National Food and Strategic Reserves Administration and National Natural Science Foundation of China. We thank the district authorities in the study area and all those who were involved in the data collection, analysis and report compilation.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflicts of interest.
Rights and permissions
About this article
Cite this article
Luo, Y., Huang, D., Wu, L. et al. The impact of metal silos on rice storage and storage losses in China. Food Sec. 14, 81–92 (2022). https://doi.org/10.1007/s12571-021-01194-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12571-021-01194-4