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Identifying drivers for variability in maize (Zea mays L.) yield in Ghana: A meta-regression approach

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  • Kouame, Anselme K.K.
  • Bindraban, Prem S.
  • Kissiedu, Isaac N.
  • Atakora, Williams K.
  • El Mejahed, Khalil

Abstract

Maize is the main cereal crop in Ghana, but its production is adversely affected by various biotic and abiotic factors.

Suggested Citation

  • Kouame, Anselme K.K. & Bindraban, Prem S. & Kissiedu, Isaac N. & Atakora, Williams K. & El Mejahed, Khalil, 2023. "Identifying drivers for variability in maize (Zea mays L.) yield in Ghana: A meta-regression approach," Agricultural Systems, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:agisys:v:209:y:2023:i:c:s0308521x23000720
    DOI: 10.1016/j.agsy.2023.103667
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    1. Espoir Mukengere Bagula & Jackson-Gilbert Mwanjalolo Majaliwa & Twaha Ali Basamba & Jean-Gomez Mubalama Mondo & Bernard Vanlauwe & Geofrey Gabiri & John-Baptist Tumuhairwe & Gustave Nachigera Mushagal, 2022. "Water Use Efficiency of Maize ( Zea mays L.) Crop under Selected Soil and Water Conservation Practices along the Slope Gradient in Ruzizi Watershed, Eastern D.R. Congo," Land, MDPI, vol. 11(10), pages 1-20, October.
    2. Paudel, Dilli & Boogaard, Hendrik & de Wit, Allard & Janssen, Sander & Osinga, Sjoukje & Pylianidis, Christos & Athanasiadis, Ioannis N., 2021. "Machine learning for large-scale crop yield forecasting," Agricultural Systems, Elsevier, vol. 187(C).
    3. Wright, Marvin N. & Ziegler, Andreas, 2017. "ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i01).
    4. Diao, Xinshen & Hazell, Peter B.R. & Kolavalli, Shashidhara & Resnick, Danielle, 2019. "Ghana's economic and agricultural transformation: Past performance and future prospects: Synopsis," IFPRI synopses 9780896296862, International Food Policy Research Institute (IFPRI).
    5. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    6. Jig Han Jeong & Jonathan P Resop & Nathaniel D Mueller & David H Fleisher & Kyungdahm Yun & Ethan E Butler & Dennis J Timlin & Kyo-Moon Shim & James S Gerber & Vangimalla R Reddy & Soo-Hyung Kim, 2016. "Random Forests for Global and Regional Crop Yield Predictions," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-15, June.
    7. Tomislav Hengl & Gerard B M Heuvelink & Bas Kempen & Johan G B Leenaars & Markus G Walsh & Keith D Shepherd & Andrew Sila & Robert A MacMillan & Jorge Mendes de Jesus & Lulseged Tamene & Jérôme E Tond, 2015. "Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-26, June.
    8. Timsina, Jagadish & Dutta, Sudarshan & Devkota, Krishna Prasad & Chakraborty, Somsubhra & Neupane, Ram Krishna & Bishta, Sudarshan & Amgain, Lal Prasad & Singh, Vinod K. & Islam, Saiful & Majumdar, Ka, 2021. "Improved nutrient management in cereals using Nutrient Expert and machine learning tools: Productivity, profitability and nutrient use efficiency," Agricultural Systems, Elsevier, vol. 192(C).
    9. Nathaniel D. Mueller & James S. Gerber & Matt Johnston & Deepak K. Ray & Navin Ramankutty & Jonathan A. Foley, 2012. "Closing yield gaps through nutrient and water management," Nature, Nature, vol. 490(7419), pages 254-257, October.
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    Cited by:

    1. Adzawla, William & Setsoafia, Edinam D. & Setsoafia, Eugene D. & Amoabeng-Nimako, Solomon & Atakora, Williams K. & Bindraban, Prem D., 2024. "Accuracy of agricultural data and implications for policy: Evidence from maize farmer recall surveys and crop cuts in the Guinea Savannah zone of Ghana," Agricultural Systems, Elsevier, vol. 214(C).

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