Agronomic assessment of the yield variability and yield gap of maize in Bhutan

Passang Wangmo , Kinzang Thinley , Taiken Nakashima , Yoichiro Kato

Crop and Environment ›› 2024, Vol. 3 ›› Issue (1) : 25 -32.

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Crop and Environment ›› 2024, Vol. 3 ›› Issue (1) :25 -32. DOI: 10.1016/j.crope.2023.11.003
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Agronomic assessment of the yield variability and yield gap of maize in Bhutan
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Abstract

Maize is the staple food crop in Bhutan, which has not achieved national food self-sufficiency. On-farm assessment of yield variability would provide insights into the priorities for Bhutan's maize development program. Here, we conducted three studies in Bhutan: a household survey, on-station experiment, and on-farm monitoring. First, we interviewed 100 households and collected information on maize crop management options and farming characteristics. Second, we evaluated maize growth at two research stations in different elevation zones (640 and 1,700 m a.s.l.). Third, we harvested maize from 25 farm fields at low and high elevations. The gaps between potential yield (with the best management practices at the research stations) and average farm yield and between the best and average farm yields were 53% and 23%, respectively, at the low elevation, and 23% and 20%, respectively, at the high elevation. The classification and regression tree (CART) model showed that field location (distance from the farmer's home), seed source (certified vs. self-produced), and the number of household members involved in farming were the key farming characteristics that affected yield variability, and the manure application regime, urea application, sowing method, and weeding frequency were key management practices. Our results suggest that future research should clarify the most suitable sowing methods and nutrient and weed management regimes, and identify optimal cultivars for each elevation zone, with the goal of developing crop management guidelines for smallholder farmers in Bhutan.

Keywords

Bhutan / Classification and regression tree model / Maize / Management practice / Yield gap / Yield variability

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Passang Wangmo, Kinzang Thinley, Taiken Nakashima, Yoichiro Kato. Agronomic assessment of the yield variability and yield gap of maize in Bhutan. Crop and Environment, 2024, 3(1): 25-32 DOI:10.1016/j.crope.2023.11.003

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Abbreviations

Not applicable.

Availability of data and materials

Data will be shared upon request by the readers.

Authors' contributions

W.P.: investigation, formal analysis, and writing original draft; K.T.: writing, review, and editing; T.N.: writing, review, and editing; and Y.K.: conceptualization, supervision, funding acquisition, writing, review, and editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Yoichiro Kato (Editorial Board member) was not involved in the journal's review nor decisions related to this manuscript.

Acknowledgements

We are grateful for support from the Agriculture Research and Development Centre of Bhutan in carrying out this study. We thank Ms. Kinley Wangmo, Tashi Dema, and Tshering Choden for their technical assistance. This study was financially supported in part by the Project for Human Resource Development Scholarship by Japanese Grant Aid (JDS, to P.W.) and the Japan Society for the Promotion of Science (JSPS, no. 18KK0169, to Y.K.).

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.crope.2023.11.003.

References

[1]

Asiedu, E.A., Asante, R., Sallah, P.Y., Baduon, A., Avah, E., 2007. Effects of farmers' seed source on maize seed quality and crop productivity. Ghana J. Agric. Sci. 40, 105-111.

[2]

Assefa, B.T., Chamberlin, J., Reidsma, P., Silva, J.V., van Ittersum, M.K., 2020. Unravelling the variability and causes of smallholder maize yield gaps in Ethiopia. Food Secur. 12, 83-103.

[3]

Bakht, J., Shafi, M., Rehman, H., Uddin, R., Anwar, S., 2011. Effect of planting methods on growth, phenology and yield of maize varieties. Pak. J. Bot. 43, 1629-1633.

[4]

Banerjee, H., Goswami, R., Chakraborty, S., Dutta, S., Majumdar, K., Satyanarayana, T., Jat, M.L., Zingore, S., 2014. Understanding biophysical and socio-economic determinants of maize (Zea mays L.) yield variability in eastern India. NJAS - Wagen. J. Life Sci. 70-71, 79-93.

[5]

Bautista, E.G., Gagelonia, E.C., Abon, J.E., Corales, A.M., Bueno, C.S., Banayo, N.P.M.C., Lugto, R.V., Suralta, R.R., Kato, Y., 2019. Development of hand tractor-mounted seed drill for rice-based cropping systems in the Philippines. Plant Prod. Sci. 22, 54-57.

[6]

Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J., 1984. Classification and Regression Trees. Chapman and Hall (Wadsworth, Inc.), New York, USA.

[7]

Bucagu, C., Ndoli, A., Cyamweshi, A.R., Nabahungu, L.N., Mukuralinda, A., Smethurst, P., 2020. Determining and managing maize yield gaps in Rwanda. Food Secur. 12, 1269-1282.

[8]

Devkota, K.P., McDonald, A.J., Khadka, A., Khadka, L., Paudel, G.P., Devkota, M., 2015. Decomposing maize yield gaps differentiates entry points for intensification in the rainfed mid-hills of Nepal. Field Crops Res. 179, 81-94.

[9]

Dutta, S., Chakraborty, S., Goswami, R., Banerjee, H., Majumdar, K., Li, B., Jat, M.L., 2020. Maize yield in smallholder agriculture system—An approach integrating socioeconomic and crop management factors. PLoS One 15, e0229100.

[10]

Eash, L., Fonte, S.J., Sonder, K., Honsdorf, N., Schmidt, A., Govaerts, B., Verhulst, N., 2019. Factors contributing to maize and bean yield gaps in Central America vary with site and agroecological conditions. J. Agric. Sci. 157, 300-317.

[11]

FAOSTAT, 2021. Production qualities by country. https://www.fao.org/faostat/en. (Accessed 15 February 2021).

[12]

Ferraro, D.O., Rivero, D.E., Ghersa, C.M., 2009. An analysis of the factors that influence sugarcane yield in Northern Argentina using classification and regression trees. Field Crops Res. 112, 149-157.

[13]

Gantoli, G., Ayala, V.R., Gerhards, R., 2013. Determination of the critical period for weed control in corn. Weed Technol. 27, 63-71.

[14]

Ghimire, S., Sherchan, D., Andersen, P., Pokhrel, C., Ghimire, S., Khanal, D., 2016. Effect of variety and practice of cultivation on yield of spring maize in terai of Nepal. Agrotechnology 5, 1-6.

[15]

Guilpart, N., Grassini, P., Sadras, V.O., Timsina, J., Cassman, K.G., 2017. Estimating yield gaps at the cropping system level. Field Crops Res. 206, 21-32.

[16]

GYGA, 2018. Global Yield Gap Atlas. https://www.yieldgap.org/web/guest/coverage-and-data-download. (Accessed 20 November 2021).

[17]

Katwal, T.B., Wangchuk, D., Dorji, L., Wangdi, N., Choney, R., 2013. Evaluation of gray leaf spot tolerant genotypes from CIMMYT in the highland maize production ecosystems of Bhutan. J. Life Sci. 7, 443-452.

[18]

Katwal, T.B., Wangchuk, D., Wangdi, N., Choney, R., Dorji, L., 2015. Community based seed production—A sustainable seed production model for subsistence of Bhutanese maize farmers. J. Food Sci. Eng. 5, 76-84.

[19]

Kihara, J., Tamene, L.D., Massawe, P., Bekunda, M., 2015. Agronomic survey to assess crop yield, controlling factors and management implications: a case-study of Babati in northern Tanzania. Nutr. Cycl. Agroecosyst. 102, 5-16.

[20]

Lemon, S.C., Roy, J., Clark, M.A., Friedmann, P.D., Rakowski, W., 2003. Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression. Ann. Behav. Med. 26, 172-181.

[21]

Leonardo, W.J., van de Ven, G.W., Udo, H., Kanellopoulos, A., Sitoe, A., Giller, K.E., 2015. Labour not land constrains agricultural production and food self-sufficiency in maizebased smallholder farming systems in Mozambique. Food Secur. 7, 857-874.

[22]

Lobell, D.B., Cassman, K.G., Field, C.B., 2009. Crop yield gaps: their importance, magnitudes, and causes. Annu. Rev. Environ. Resour. 34, 179-204.

[23]

Memon, S.Q., Baig, M.B., Mari, G.R., 2007. Tillage practices and effect of sowing methods on growth and yield of maize crop. Agric. Trop. Subtrop. 40, 89-100.

[24]

Mian, M.A.K., Kakon, S.S., Zannat, S.T., Begum, A.A., 2021. Plant population is the function of grain yield of maize. Open J. Plant Sci. 6, 103-107.

[25]

Munialo, S., Dahlin, A.S., Onyango, M.C., Oluoch-Kosura, W., Marstorp, H., Öborn, I., 2020. Soil and management-related factors contributing to maize yield gaps in western Kenya. Food Energy Secur. 9, e189.

[26]

Niang, A., Becker, M., Ewert, F., Dieng, I., Gaiser, T., Tanaka, A., Senthilkumar, K., Rodenburg, J., Johnson, J.M., Akakpo, C., Segda, Z., Gbakatchetche, H., Jaiteh, F., Bam, R.K., Dogbe, W., Keita, S., Kamissoko, N., Mossi, I.M., Bakare, O.S., Cissé, M., Baggie, I., Ablede, K.A., Saito, K., 2017. Variability and determinants of yields in rice production systems of West Africa. Field Crops Res. 207, 1-12.

[27]

Omovbude, S., Udensi, E.U., 2012. Profitability of selected weed control methods in maize (Zea mays L.) in Nigeria. J. Anim. Plant Sci. 15, 2109-2117.

[28]

Pasuquin, J.M., Pampolino, M.F., Witt, C., Dobermann, A., Oberthür, T., Fisher, M.J., Inubushi, K., 2014. Closing yield gaps in maize production in Southeast Asia through site-specific nutrient management. Field Crops Res. 156, 219-230.

[29]

Peramaiyan, P., McDonald, A.J., Kumar, V., Craufurd, P., Wasim, I., Parida, N., Sanghamitra, P., Singh, B., Yadav, A., Ajay, A., Singh, S., Malik, R.K., 2022. Narrowing maize yield gaps in the rainfed plateau region of Odisha. Exp. Agric. 58, 1-16.

[30]

Ragasa, C., Dankyi, A., Acheampong, P., Wiredu, A.N., Chapoto, A., Asamoah, M., Tripp, R., 2013. Patterns of adoption of improved rice technologies in Ghana. Ghana Strategy Support Program (GSSP) Working Paper 35. International Food Policy Research Institute (IFPRI), Washington, DC, USA, pp. 1-36.

[31]

Sadras, V.O., Cassman, K.G., Grassini, P., Hall, A.J., Bastiaanssen, W.G.M., Laborte, A.G., Milne, A.E., Sileshi, G., Steduto, P., 2015. Yield gap analysis of field crops: Methods and case studies. Food and Agriculture Organization (FAO) Water Report 41. FAO, Rome, Italy, pp. 1-83.

[32]

Speybroeck, N., 2012. Classification and regression trees. Int. J. Public Health 57, 243-246.

[33]

Tamene, L., Mponela, P., Ndengu, G., Kihara, J., 2016. Assessment of maize yield gap and major determinant factors between smallholder farmers in the Dedza district of Malawi. Nutr. Cycl. Agroecosyst. 105, 291-308.

[34]

Tittonell, P., Shepherd, K.D., Vanlauwe, B., Giller, K.E., 2008a. Unravelling the effects of soil and crop management on maize productivity in smallholder agricultural systems of western Kenya—An application of classification and regression tree analysis. Agric. Ecosyst. Environ. 123, 137-150.

[35]

Tittonell, P., Vanlauwe, B., Corbeels, M., Giller, K.E., 2008b. Yield gaps, nutrient use efficiencies and response to fertilisers by maize across heterogeneous smallholder farms of western Kenya. Plant Soil 313, 19-37.

[36]

van Ittersum, M.K., Cassman, K.G., Grassini, P., Wolf, J., Tittonell, P., Hochman, Z., 2013. Yield gap analysis with local to global relevance: A review. Field Crops Res. 143, 4-17.

[37]

Wopereis, M.C.S., Tamélokpo, A., Ezui, K., Gnakpénou, D., Fofana, B., Breman, H., 2006. Mineral fertilizer management of maize on farmer fields differing in organic inputs in the West African savanna. Field Crops Res. 96, 355-362.

[38]

Zheng, H., Chen, L., Han, X., Zhao, X., Ma, Y., 2009. Classification and regression tree (CART) for analysis of soybean yield variability among fields in Northeast China: The importance of phosphorus application rates under drought conditions. Agric. Ecosyst. Environ. 132, 98-105.

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