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Interpretable machine learning methods to explain on-farm yield variability of high productivity wheat in Northwest India


Type:
Article
Title:
Interpretable machine learning methods to explain on-farm yield variability of high productivity wheat in Northwest India
Creator:
Hari S. Nayak;
Hari S. Nayak
ORCID iD iconhttps://orcid.org/0000-0003-2585-1576
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Silva, J.V.;
ORCID iD icon
Silva, J.V.
ORCID iD iconhttps://orcid.org/0000-0002-3019-5895
ScopusScopus ID
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Parihar, C.M.;
Parihar, C.M.
ORCID iD iconhttps://orcid.org/0000-0003-3855-2655
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Krupnik, T.J.;
ORCID iD icon
Krupnik, T.J.
ORCID iD iconhttps://orcid.org/0000-0001-6973-0106
ScopusScopus ID
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Sena, D.R.;
Kakraliya Suresh Kumar;
Jat, H.S.;
Sidhu, H.S.;
Sharma, P.C.;
Sharma, P.C.
ORCID iD iconhttps://orcid.org/0000-0002-5783-7480
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Jat, M.L.;
ORCID iD icon
Jat, M.L.
ORCID iD iconhttps://orcid.org/0000-0003-0582-1126
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Sapkota, T.B.
ORCID iD icon
Sapkota, T.B.
ORCID iD iconhttps://orcid.org/0000-0001-5311-0586
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Year:
2022
Copyright:
CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Journal:
Field Crops Research
Journal volume:
287
Article number:
108640
DOI:
10.1016/j.fcr.2022.108640
Place of Publication:
Amsterdam (Netherlands)
Publisher:
Elsevier
Citation:
Interpretable machine learning methods to explain on-farm yield variability of high productivity wheat in Northwest India. 2022. 287 DOI: 10.1016/j.fcr.2022.108640 Elsevier.

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Genetic ResourcesInstitutionalMaizeSocioeconomicsSustainable Agrifood SystemsSustainable IntensificationWheat

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