{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T07:34:37Z","timestamp":1768548877492,"version":"3.49.0"},"reference-count":55,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,25]],"date-time":"2021-08-25T00:00:00Z","timestamp":1629849600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of Guangxi","award":["2019GXNSFBA245036"],"award-info":[{"award-number":["2019GXNSFBA245036"]}]},{"name":"National Natural Science Foundation of China","award":["32060369"],"award-info":[{"award-number":["32060369"]}]},{"name":"Basic Scientific Research Fund of Guangxi Academy of Science","award":["2019YJJ1009"],"award-info":[{"award-number":["2019YJJ1009"]}]},{"name":"Basic Ability Improvement Scientific Research Fund of Young and Middle-aged Teachers in Guangxi Universities","award":["2020KY58008"],"award-info":[{"award-number":["2020KY58008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The ratio between nitrogen and phosphorus (N\/P) in plant leaves has been widely used to assess the availability of nutrients. However, it is challenging to rapidly and accurately estimate the leaf N\/P ratio, especially for mixed forest. In this study, we collected 301 samples from nine typical karst areas in Guangxi Province during the growing season of 2018 to 2020. We then utilized five models (partial least squares regression (PLSR), backpropagation neural network (BPNN), general regression neural network (GRNN), PLSR+BPNN, and PLSR+GRNN) to estimate the leaf N\/P ratio of plants based on these samples. We also applied the fractional differentiation to extract additional information from the original spectra of each sample. The results showed that the average leaf N\/P ratio of plants was 17.97. Plant growth was primarily limited by phosphorus in these karst areas. The sensitive spectra to estimate leaf N\/P ratio had wavelengths ranging from 400\u2013730 nm. The prediction capabilities of these five models can be ranked in descending order as PLSR+GRNN, PLSR+BPNN, PLSR, GRNN, and BPNN when considering both accuracy and robustness. The PLSR+GRNN model yielded high R2 and performance to deviation (RPD), and low root mean squared error (RMSE) with values of 0.91, 3.15, and 1.98, respectively, for the training test and 0.81, 2.25, and 2.46, respectively, for validation test. Compared with the PLSR model, both PLSR+BPNN and PLSR+GRNN models had higher accuracy and were more stable. Moreover, both PLSR+BPNN and PLSR+GRNN models overcame the issue of overfitting, which occurs when a single model is used to predict leaf N\/P ratio. Therefore, both PLSR+BPNN and PLSR+GRNN models can be used to predict the leaf N\/P ratio of plants in karst areas. Fractional differentiation is a promising spectral preprocessing technique that can improve the accuracy of models. We conclude that the leaf N\/P ratio of mixed forest can be effectively estimated using combined models based on field spectroradiometer data in karst areas.<\/jats:p>","DOI":"10.3390\/rs13173368","type":"journal-article","created":{"date-parts":[[2021,8,25]],"date-time":"2021-08-25T23:25:50Z","timestamp":1629933950000},"page":"3368","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Using Field Spectroradiometer to Estimate the Leaf N\/P Ratio of Mixed Forest in a Karst Area of Southern China: A Combined Model to Overcome Overfitting"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1269-878X","authenticated-orcid":false,"given":"Wen","family":"He","sequence":"first","affiliation":[{"name":"College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541006, China"},{"name":"Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain, Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guilin 541006, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3362-7366","authenticated-orcid":false,"given":"Yanqiong","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China"}]},{"given":"Jinye","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541006, China"}]},{"given":"Yuefeng","family":"Yao","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain, Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guilin 541006, China"}]},{"given":"Ling","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Southwest University, Chongqing 400715, China"}]},{"given":"Daxing","family":"Gu","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain, Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guilin 541006, China"}]},{"given":"Longkang","family":"Ni","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain, Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guilin 541006, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1217","DOI":"10.1890\/02-0249","article-title":"Fundamental connections among organism C: N: P stoichiometry, macromolecular composition, and growth","volume":"85","author":"Vrede","year":"2004","journal-title":"Ecology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1111\/j.1461-0248.2000.00185.x","article-title":"Biological stoichiometry from genes to ecosystems","volume":"3","author":"Elser","year":"2000","journal-title":"Ecol. 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