This study was performed to examine the separate and simultaneous influence of predictive models'choice alongside sample ratios selection in soil organic matter(SOM).The research was carried out in northern Morocco,characterized by relatively cold weather and diverse geological conditions.The dataset herein used accounted for 1591 soil samples,which were randomly split into the following ra-tios:10％(～150 sample ratio),20％(～250 sample ratio),35％(～450 sample ratio),50％(～600 sample ratio)and 95％(～1200 sample ratio).Models herein involved were ordinary kriging(OK),regression kriging(RK),multiple linear regression(MLR),random forest(RF),quantile regression forest(QRF),Gaussian process regression(GPR)and an ensemble model.The findings in the study showed that the accuracy of SOM prediction is sensitive to both predictive models and sample ratios.OK combined with 95％sample ratio performed equally to RF in conjunction with all the sample ratios,as the latter did not show much sensitivity to sample ratios.ANOVA results revealed that RF with a-10％sample ratio could also be optimum for predicting SOM in the study area.In conclusion,the findings herein reported could be instrumental for producing cost-effective detailed and accurate spatial estimation of SOM in other sites.Furthermore,they could serve as a baseline study for future research in the region or elsewhere.Therefore,we recommend conducting series of simulation of all possible combinations between various predictive models and sample ratios as a preliminary step in soil organic matter prediction.

Kingsley John;Yassine Bouslihim;Kokei Ikpi Ofem;Lahcen Hssaini;Rachid Razouk;Paul Bassey Okon;Isong Abraham Isong;Prince Chapman Agyeman;Ndiye Michael Kebonye;Chengzhi Qin

Department of Soil Science and Soil Protection,Faculty of Agrobiology,Food,and Natural Resources,Czech University of Life Sciences,Kamycká 129,16500,Prague,Czech Republic;National Institute of Agricultural Research,Morocco;Department of Soil Science,Faculty of Agriculture,Forestry and Wildlife Resources Management,University of Calabar,PMB 1115,540004,Etta Agbo Road,Calabar,Nigeria;State Key Laboratory of Resources and Environmental Information System,Institute of Geographical Sciences and Natural Resources Research,CAS,Beijing,100101,China

国际水土保持研究（英文）

[1]Kingsley John;Yassine Bouslihim;Kokei Ikpi Ofem;Lahcen Hssaini;Rachid Razouk;Paul Bassey Okon;Isong Abraham Isong;Prince Chapman Agyeman;Ndiye Michael Kebonye;Chengzhi Qin-.Do model choice and sample ratios separately or simultaneously influence soil organic matter prediction?)[J].国际水土保持研究（英文）,2022(03):470-486

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