000 03297nab|a22005177a|4500
001 69629
003 MX-TxCIM
005 20251128150338.0
008 2511272025|||||ne ||p|op||||00||0|eng|dd
022 _a0167-8809
022 _a1873-2305 (Online)
024 8 _ahttps://doi.org/10.1016/j.agee.2025.109918
040 _aMX-TxCIM
041 _aeng
100 1 _aAgbohessou, Y.
_932777
245 1 0 _aProxydetection of the impact distance of trees on crops :
_bAn indicator of the Land Equivalent Ratio
260 _aAmsterdam (Netherlands) :
_bElsevier B.V.,
_c2025.
500 _aPeer review
500 _aOpen Access
520 _aFaidherbia albida is known to affect the yield of various crops, typically in a pattern where the impact decreases with increasing distance from the tree. While several studies have investigated the spatial extent of this effect, limited research has explored how this distance varies across different crops or its relationship with crop yield and the Land Equivalent Ratio. In this study, we used a geostatistical approach combined with multispectral UAV (Unmanned Aerial Vehicle) imagery to address these gaps in understanding. The results showed that, in contrast to its tripling effect on millet yield, F. albida does not have a significant impact on groundnut pod yield, it only improves its haulm yield under its crown by about 50 %. The geostatistical analysis showed that F. albida affects the groundnut crop up to 9.8-m, compared to 18-m for millet. Yield upscaling from subplots to the whole plot was achieved with an error of 8 % for groundnut pod yield and 13 % for haulm yield. Groundnut’s partial Land Equivalent Ratio (LERcp) was 1.02 for pod yield and 1.05 for haulm yield, which was lower than the LERcp for millet. We concluded that the distance at which agroforestry trees influence crops is a reliable predictor of their effect on yield and Land Equivalent Ratio. This approach offers a promising tool for future agroforestry studies, potentially guiding crop management strategies in agroforestry systems.
546 _aText in English
597 _dEuropean Union (EU)
_dRAMSES II
_dEC2CO – ENCAS Projects
_dLaboratoire des Moyens Analytiques (LAMA)
650 7 _aFaidherbia albida
_2AGROVOC
_97674
650 7 _aCrops
_2AGROVOC
_91069
650 7 _aLand equivalent ratio
_2AGROVOC
_910878
650 7 _aGeostatistics
_2AGROVOC
_99905
700 1 _aAudebert, A.
_940733
700 1 _8001713635
_aNdour, A.
_gSustainable Agrifood Systems
_929881
700 1 _aLeroux, L.
_917288
700 1 _aJourdan, C.
_932780
700 1 _aClermont-Dauphin, C.
_932773
700 1 _aSow, S.
_932768
700 1 _aPierre, C.
_940734
700 1 _aTaugourdeau, S.
_92606
700 0 _aMame Sokhna Sarr
_940735
700 0 _aSekouna Diatta
_940736
700 1 _aDiaite, D.S.
_932781
700 1 _aSeghieri, J.
_932778
700 1 _aLe Maire, G.
_914024
700 1 _aVezy, R.
_932771
700 1 _aFoncéka, D.
_926805
700 1 _aRoupsard, O.
_92603
773 0 _tAgriculture, Ecosystems and Environment
_dAmsterdam (Netherlands) : Elsevier B.V., 2025.
_gv. 394, art. 109918
_x0167-8809
_wG444470
856 4 _yOpen Access through DSpace
_uhttps://hdl.handle.net/10883/36240
942 _cJA
_n0
_2ddc
999 _c69629
_d69621