 Your new post is loading...
 Your new post is loading...
Rockström, J., Kassam, A., Friedrich, T., Reicosky, D., Dumansky, J., Goddard, T. & Peiretti, R.A. 2026. Global Sustainability. 9. Article e11, pages 1-27. https://doi.org/10.1017/sus.2025.10045
Schiavo, J.A., Lopes, V.R., Araújo, A.R., Macedo, M.C.M.,Oliveira, N. de S., Coêlho, R. da S., Souza, C.B. da Silva, Farias, P.G. da Silva, Panachuki, E., Couto, A.M. & Oelbermann, M. 2025. Applied and Environmental Soil Science. 2025 (1). Article 8491885. https://doi.org/10.1155/aess/8491885
Yuan, C., Ma, Z., Liu, S., Nie, H., Feng, G., Wang, S. & Luo, S. 2025. Frontiers in Microbiology. 16. Article 173092. https://doi.org/10.3389/fmicb.2025.1730920
Nthebere, K., Prakash, T.R., Bhimireddy, P., Chandran, L.P., Gudapati, J., Admala, M. & Prasad, K. 2025 Heliyon. 11 (1) Article e41196. https://doi.org/10.1016/j.heliyon.2024.e41196
Attia, A., Woli, P., Long, C.R., Rouquette, F.M., Smith, G.R., Datta, A., Felke, T. & Rajan, N. 2025. Journal of Environmental Management. 391. Article 126352. https://doi.org/10.1016/j.jenvman.2025.126352
Fagodiya, R.K., Verma, K., Sharma, G., Rai, A.K., Prajapat, K., Singh, R., Sheoran, P., Basak, N., Chandra, P., Sharma, D.P., Yadav, R.K. & Biswas, A.K. 2025. Soil and Tillage Research. 254. Article 106697. https://doi.org/10.1016/j.still.2025.106697
Madzivanzira, T., Mvumi, B.M., Nazare, R.M., Nyakudya, E., Mtambanengwe, F. & Mapfumo, P. 2025.Advances in Agriculture. 1. Article 4837619. https://doi.org/10.1155/aia/4837619
Zhou, Y., Ferdinand, M.S., van Wesemael, J., Dvorakova, K., Baret, P.V., Van Oost, K. & van Wesemael, B. 2025. Remote Sensing of Environment. 328. Article 114858. https://doi.org/10.1016/j.rse.2025.114858
Kim, D.H., Wade, T., Brym, Z., Ogisma, L., Bhattarai, R., Bai, X., Bhadha, J. & Her, Y. 2025. Journal of Environmental Management. 387. Article 125833. https://doi.org/10.1016/j.jenvman.2025.125833
|
Hasanain, Md., Singh, V.K., Rathore, S.S., Meena, V.S., Singh, R.K., et al., (9 more). Biomass and Bioenergy. 208. Article 108864. https://doi.org/10.1016/j.biombioe.2025.108864
Jia, Y., Sun, Y., Zhang, D., Yang, W., Pang, J., Siddique, K.H.. & Qu, Z. 2025. Agronomy-Basel. 15 (5) Article 1007. https://doi.org/10.3390/agronomy15051007
Khosa, M.K., Barik, K., Aksakal, E., Jahangir, Md MR., Didenko, N.O. & Islam, K.R. 2025. Plos One. 20 (5) Article e0322891. https://doi.org/10.1371/journal.pone.0322891
|
This analysis applied machine-learning techniques to a wealth of published data to create a predictive model of the agronomic outcome of CA relative to conventional practice (CP) based on 21 variables. Results showed that over-yielding of CA relative to CP was driven by a complex of climate, soil, geographic and management variables, and cannot be predicted accurately from precipitation amount or aridity index alone. Success of CA greatly increases with mean air temperature from 20°C and with duration of CA for up to 13years. They suggest that predictive models can be used as an important tool by policy-makers and funding organizations to target financial resources to those regions where CA adoption will have the greatest impact on productivity.