{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T17:45:39Z","timestamp":1770140739797,"version":"3.49.0"},"reference-count":52,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T00:00:00Z","timestamp":1629331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32071903"],"award-info":[{"award-number":["32071903"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Jiangsu Agricultural Science and Technology Innovation","award":["CX (20) 3072"],"award-info":[{"award-number":["CX (20) 3072"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFE0202900"],"award-info":[{"award-number":["2020YFE0202900"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The accurate estimation and timely diagnosis of crop nitrogen (N) status can facilitate in-season fertilizer management. In order to evaluate the performance of three leaf and canopy optical sensors in non-destructively diagnosing winter wheat N status, three experiments using seven wheat cultivars and multi-N-treatments (0\u2013360 kg N ha\u22121) were conducted in the Jiangsu province of China from 2015 to 2018. Two leaf sensors (SPAD 502, Dualex 4 Scientific+) and one canopy sensor (RapidSCAN CS-45) were used to obtain leaf and canopy spectral data, respectively, during the main growth period. Five N indicators (leaf N concentration (LNC), leaf N accumulation (LNA), plant N concentration (PNC), plant N accumulation (PNA), and N nutrition index (NNI)) were measured synchronously. The relationships between the six sensor-based indices (leaf level: SPAD, Chl, Flav, NBI, canopy level: NDRE, NDVI) and five N parameters were established at each growth stages. The results showed that the Dualex-based NBI performed relatively well among four leaf-sensor indices, while NDRE of RS sensor achieved a best performance due to larger sampling area of canopy sensor for five N indicators estimation across different growth stages. The areal agreement of the NNI diagnosis models ranged from 0.54 to 0.71 for SPAD, 0.66 to 0.84 for NBI, and 0.72 to 0.86 for NDRE, and the kappa coefficient ranged from 0.30 to 0.52 for SPAD, 0.42 to 0.72 for NBI, and 0.53 to 0.75 for NDRE across all growth stages. Overall, these results reveal the potential of sensor-based diagnosis models for the rapid and non-destructive diagnosis of N status.<\/jats:p>","DOI":"10.3390\/s21165579","type":"journal-article","created":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T09:58:06Z","timestamp":1629367086000},"page":"5579","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Evaluation of Three Portable Optical Sensors for Non-Destructive Diagnosis of Nitrogen Status in Winter Wheat"],"prefix":"10.3390","volume":"21","author":[{"given":"Jie","family":"Jiang","sequence":"first","affiliation":[{"name":"National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"MOE Engineering Research Center of Smart Agricultural, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"MARA Key Laboratory for Crop System Analysis and Decision Making, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cuicun","family":"Wang","sequence":"additional","affiliation":[{"name":"National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"MOE Engineering Research Center of Smart Agricultural, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"MARA Key Laboratory for Crop System Analysis and Decision Making, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"Jiangsu Collaborative Innovation Center for Modern Crop 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A review","volume":"31","author":"Miao","year":"2011","journal-title":"Agron. Sustain. Devlop."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.2136\/sssaj2005.0396","article-title":"Potential impact of precision nitrogen management on corn yield, protein content, and test weight","volume":"71","author":"Miao","year":"2007","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.biosystemseng.2012.08.009","article-title":"Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps","volume":"114","author":"Mulla","year":"2013","journal-title":"Biosyst. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Dong, R., Miao, Y., Wang, X., Chen, Z., Yuan, F., Zhang, W., and Li, H. (2020). Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages. Remote Sens., 12.","DOI":"10.3390\/rs12071139"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1006\/anbo.1994.1133","article-title":"Determination of a critical nitrogen dilution curve for winter wheat crops","volume":"74","author":"Justes","year":"1994","journal-title":"Ann. Bot."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/j.eja.2008.01.005","article-title":"Diagnosis tool for plant and crop N status in vegetative stage: Theory and practices for crop N management","volume":"28","author":"Lemaire","year":"2008","journal-title":"Eur. J. Agron."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Xia, T., Miao, Y., Wu, D., Shao, H., Khosla, R., and Mi, G. (2016). Active Optical Sensing of Spring Maize for In-Season Diagnosis of Nitrogen Status Based on Nitrogen Nutrition Index. Remote. Sens., 8.","DOI":"10.3390\/rs8070605"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1051\/agro:2007032","article-title":"Replacing the nitrogen nutrition index by the chlorophyll meter to assess wheat N status","volume":"27","author":"Prost","year":"2007","journal-title":"Agron. Sustain. Dev."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Souza, R., Pea-Fleitas, M.T., Thompson, R.B., Gallardo, M., and Padilla, F.M. (2020). Assessing Performance of Vegetation Indices to Estimate Nitrogen Nutrition Index in Pepper. Remote Sens., 12.","DOI":"10.3390\/rs12050763"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2007","DOI":"10.1081\/CSS-120000265","article-title":"Comparison of Dumas and Kjeldahl methods with automatic analyzers on agricultural samples under routine rapid analysis conditions","volume":"32","author":"Watson","year":"2001","journal-title":"Commun. Soil Sci. Plant Anal."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1002\/jpln.200620627","article-title":"Determination of a critical dilution curve for nitrogen concentration in cotton","volume":"170","author":"Xue","year":"2007","journal-title":"J. Plant Nutr. Soil Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"10823","DOI":"10.3390\/s130810823","article-title":"A Review of Methods for Sensing the Nitrogen Status in Plants: Advantages, Disadvantages and Recent Advances","volume":"13","year":"2013","journal-title":"Sensors"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s42106-019-00068-2","article-title":"Evaluation of Both SPAD Reading and SPAD Index on Estimating the Plant Nitrogen Status of Winter Wheat","volume":"14","author":"Yue","year":"2020","journal-title":"Int. J. Plant Prod."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.fcr.2017.08.023","article-title":"Use of a chlorophyll meter to assess nitrogen nutrition index during the growth cycle in winter wheat","volume":"214","author":"Ravier","year":"2017","journal-title":"Field Crop. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1111\/j.1399-3054.2012.01639.x","article-title":"A new optical leaf-clip meter for simultaneous non-destructive assessment of leaf chlorophyll and epidermal flavonoids","volume":"146","author":"Cerovic","year":"2012","journal-title":"Physiol. Plant."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhang, K., Liu, X., Ma, Y., Zhang, R., Cao, Q., Zhu, Y., Cao, W., and Tian, Y. (2020). A Comparative Assessment of Measures of Leaf Nitrogen in Rice Using Two Leaf-Clip Meters. Sensors, 20.","DOI":"10.3390\/s20010175"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Dong, T., Shang, J., Chen, J.M., Liu, J., Qian, B., Ma, B., Morrison, M.J., Zhang, C., Liu, Y., and Shi, Y. (2019). Assessment of Portable Chlorophyll Meters for Measuring Crop Leaf Chlorophyll Concentration. Remote Sens., 11.","DOI":"10.3390\/rs11222706"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1080\/01904160701555689","article-title":"Evaluation of the Dualex for the assessment of corn nitrogen status","volume":"30","author":"Tremblay","year":"2007","journal-title":"J. Plant Nutr."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"121","DOI":"10.17660\/ActaHortic.2009.824.13","article-title":"The Dualex\u2014A New Tool to Determine Nitrogen Sufficiency in Broccoli","volume":"824","author":"Tremblay","year":"2009","journal-title":"Acta Hortic."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1080\/01904160903391081","article-title":"Performance of Dualex in spring wheat for crop nitrogen status assessment, Yield predication and estimation of soil nitrate content","volume":"33","author":"Tremblay","year":"2010","journal-title":"J. Plant Nutr."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Gabriel, J.L., Quemada, M., Alonso-Ayuso, M., Lizaso, J.I., and Mart\u00edn-Lammerding, D. (2019). Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing. Sensors, 19.","DOI":"10.3390\/s19183881"},{"key":"ref_23","unstructured":"Lejealle, S., Evain, S., and Cerovic, Z.G. (2010, January 18\u201321). Multiplex: A new diagnostic tool for management of nitrogen fertilization of turfgrass. Proceedings of the 10th International Conference on Precision Agriculture, Denver, CO, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1987","DOI":"10.1016\/j.rse.2010.04.006","article-title":"New spectral indicator assessing the efficiency of crop nitrogen treatment in corn and wheat","volume":"114","author":"Chen","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.eja.2007.11.005","article-title":"Monitoring leaf nitrogen status with hyperspectral reflectance in wheat","volume":"28","author":"Feng","year":"2008","journal-title":"Eur. J. Agron."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.fcr.2004.04.004","article-title":"Prediction of grain protein content in winter wheat (Triticum aestivum L.) using plant pigment ratio (PPR)","volume":"90","author":"Wang","year":"2004","journal-title":"Field Crop. Res."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Jiang, J., Wang, C., Wang, Y., Cao, Q., Tian, Y., Zhu, Y., Cao, W., and Liu, X. (2020). Using an Active Sensor to Develop New Critical Nitrogen Dilution Curve for Winter Wheat. Sensors, 20.","DOI":"10.3390\/s20061577"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1007\/s10705-017-9865-7","article-title":"Topdressing nitrogen recommendation in wheat after applying organic manures: The use of field diagnostic tools","volume":"110","author":"Aranguren","year":"2018","journal-title":"Nutr. Cycl. Agroecosyst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.fcr.2017.11.006","article-title":"Characterizing soybean vigor and productivity using multiple crop canopy sensor readings","volume":"216","author":"Miller","year":"2018","journal-title":"Field Crop. Res."},{"key":"ref_30","unstructured":"Barnes, E.M., Clarke, T.R., Richards, S.E., Colaizzi, P.D., and Thompson, T. (2000, January 16\u201319). Coincident detection of crop water stress, nitrogen status, and canopy density using ground based multispectral data. Proceedings of the Fifth International Conference on Precision Agriculture, Bloomington, MN, USA."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combination for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhang, J., Liu, X., Liang, Y., Cao, Q., Tian, Y., Zhu, Y., Cao, W., and Liu, X. (2019). Using a Portable Active Sensor to Monitor Growth Parameters and Predict Grain Yield of Winter Wheat. Sensors, 19.","DOI":"10.3390\/s19051108"},{"key":"ref_33","unstructured":"Page, A.L., Miller, R.H., and Keeney, D.R. (1982). Nitrogen -total. In Methods of Soil Analysis. Chemical and Microbial Properties, American Society of Agronomy, and Soil Science Society."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Cao, Q., Miao, Y., Shen, J., Yuan, F., Cheng, S., and Cui, Z. (2018). Evaluating Two Crop Circle Active Canopy Sensors for In-Season Diagnosis of Winter Wheat Nitrogen Status. Agronomy, 8.","DOI":"10.3390\/agronomy8100201"},{"key":"ref_35","unstructured":"Lillesand, T., Kiefer, R., and Chipman, J. (2015). Remote Sensing and Image Interpretation, Wiley. [7th ed.]."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2307\/2529310","article-title":"The measurement of observer agreement for categorical data","volume":"33","author":"Landis","year":"1977","journal-title":"Biometrics"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Padilla, F.M., Gallardo, M., Teresa Pe\u00f1a-Fleitas, M., de Souza, R., and Thompson, R.B. (2018). Proximal Optical Sensors for Nitrogen Management of Vegetable Crops: A Review. Sensors, 18.","DOI":"10.3390\/s18072083"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.fcr.2004.05.002","article-title":"Optically assessed contents of leaf polyphenolics and chlorophyll as indicators of nitrogen deficiency in wheat (Triticum aestivum L.)","volume":"91","author":"Cartelat","year":"2005","journal-title":"Field Crop. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.eja.2014.04.006","article-title":"Evaluation of optical sensor measurements of canopy reflectance and of leaf flavonols and chlorophyll contents to assess crop nitrogen status of muskmelon","volume":"58","author":"Padilla","year":"2014","journal-title":"Eur. J. Agron."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s11119-014-9363-8","article-title":"Using active canopy sensors and chlorophyll meters to estimate grapevine nitrogen status and productivity","volume":"16","author":"Taskos","year":"2015","journal-title":"Precis. Agric."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Aula, L., Omara, P., Nambi, E., Oyebiyi, F.B., and Raun, W.R. (2020). Review of Active Optical Sensors for Improving Winter Wheat Nitrogen Use Efficiency. Agronomy, 10.","DOI":"10.3390\/agronomy10081157"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Wang, Y., Zhang, K., Tang, C., Cao, Q., Tian, Y., Zhu, Y., Cao, W., and Liu, X. (2019). Estimation of Rice Growth Parameters Based on Linear Mixed-Effect Model Using Multispectral Images from Fixed-Wing Unmanned Aerial Vehicles. Remote Sens., 11.","DOI":"10.3390\/rs11111371"},{"key":"ref_43","first-page":"1829","article-title":"Non-destructive Assessment of Plant Nitrogen Parameters Using Leaf Chlorophyll Measurements in Rice","volume":"7","author":"Cao","year":"2016","journal-title":"Front. Plant Sci."},{"key":"ref_44","first-page":"160","article-title":"Spectral indices of wheat cultivars at different growth stages under Punjab conditions","volume":"19","author":"Kaur","year":"2018","journal-title":"J. Agrometeorol."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Huang, S., Miao, Y., Yuan, F., Cao, Q., Ye, H., Lenz-Wiedemann, V.I.S., and Bareth, G. (2019). In-Season Diagnosis of Rice Nitrogen Status Using Proximal Fluorescence Canopy Sensor at Different Growth Stages. Remote Sens., 11.","DOI":"10.3390\/rs11161847"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"14073","DOI":"10.1038\/s41598-017-14597-1","article-title":"Evaluating different approaches to non-destructive nitrogen status diagnosis of rice using portable RapidSCAN active canopy sensor","volume":"7","author":"Lu","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.fcr.2016.10.009","article-title":"Estimation of nitrogen fertilizer requirement for rice crop using critical nitrogen dilution curve","volume":"201","author":"Liu","year":"2017","journal-title":"Field Crop. Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1002\/agj2.20036","article-title":"Chlorophyll meter-based nitrogen fertilizer optimization algorithm and nitrogen nutrition index for in-season fertilization of paddy rice","volume":"112","author":"Zhang","year":"2020","journal-title":"Agron. J."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2552","DOI":"10.2134\/agronj2018.03.0217","article-title":"Active-Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt","volume":"110","author":"Bean","year":"2018","journal-title":"Agron. J."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.fcr.2007.11.002","article-title":"Spectral measurements of the total aerial N and biomass dry weight in maize using a quadrilateral-view optic","volume":"106","author":"Mistele","year":"2008","journal-title":"Field Crop. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1007\/s11119-020-09733-3","article-title":"Site-specific nitrogen management in winter wheat supported by low-altitude remote sensing and soil data","volume":"22","author":"Argento","year":"2021","journal-title":"Precis. Agric."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"936","DOI":"10.3389\/fpls.2018.00936","article-title":"Combining Unmanned Aerial Vehicle (UAV)-Based Multispectral Imagery and Ground-Based Hyperspectral Data for Plant Nitrogen Concentration Estimation in Rice","volume":"9","author":"Zheng","year":"2018","journal-title":"Front. Plant Sci."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/16\/5579\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:47:10Z","timestamp":1760165230000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/16\/5579"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,19]]},"references-count":52,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["s21165579"],"URL":"https:\/\/doi.org\/10.3390\/s21165579","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,19]]}}}