Статті в журналах з теми "Chlorophyll Content Prediction"
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Lv, Jie, Feng Li Deng, and Zhen Guo Yan. "Using PROSEPCT and SVM for the Estimation of Chlorophyll Concentration." Advanced Materials Research 989-994 (July 2014): 2184–87. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2184.
Повний текст джерелаLiu, Yang, Jinfei Zhao, Yurong Tang, Xin Jiang, and Jiean Liao. "Construction of a Chlorophyll Content Prediction Model for Predicting Chlorophyll Content in the Pericarp of Korla Fragrant Pears during the Storage Period." Agriculture 12, no. 9 (August 31, 2022): 1348. http://dx.doi.org/10.3390/agriculture12091348.
Повний текст джерелаXu, Yanan, Keling Tu, Ying Cheng, Haonan Hou, Hailu Cao, Xuehui Dong, and Qun Sun. "Application of Digital Image Analysis to the Prediction of Chlorophyll Content in Astragalus Seeds." Applied Sciences 11, no. 18 (September 19, 2021): 8744. http://dx.doi.org/10.3390/app11188744.
Повний текст джерелаZhao, Long, Zhao Mei Qiu, Peng Jun Mao, and Gui Yang Deng. "Research on Biological Materials for the Preferred of the Chlorophyll Content Gray GM (1,1) Prediction Models Based on the Different Light." Advanced Materials Research 910 (March 2014): 65–69. http://dx.doi.org/10.4028/www.scientific.net/amr.910.65.
Повний текст джерелаJin, Xiu Liang, Chang Wei Tan, Jun Chan Wang, Lu Tong, Fen Tuan Yang, Xin Kai Zhu, and Wen Shan Guo. "Estimation of Wheat Chlorophyll Content Based on HJ Satellite CCD." Advanced Materials Research 468-471 (February 2012): 1599–604. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.1599.
Повний текст джерелаAli, Abebe Mohammed, Roshanak Darvishzadeh, Andrew Skidmore, Marco Heurich, Marc Paganini, Uta Heiden, and Sander Mücher. "Evaluating Prediction Models for Mapping Canopy Chlorophyll Content Across Biomes." Remote Sensing 12, no. 11 (June 1, 2020): 1788. http://dx.doi.org/10.3390/rs12111788.
Повний текст джерелаP. SHANMUGAPRIYA, K. R. LATHA, S. PAZHANIVELAN, R. KUMARAPERUMAL, G. KARTHIKEYAN, and N. S. SUDARMANIAN. "Cotton yield prediction using drone derived LAI and chlorophyll content." Journal of Agrometeorology 24, no. 4 (December 2, 2022): 348–52. http://dx.doi.org/10.54386/jam.v24i4.1770.
Повний текст джерелаShafiq Amirul Sabri, Mohd, R. Endut, C. B. M. Rashidi, A. R. Laili, S. A. Aljunid, and N. Ali. "Analysis of Near-infrared (NIR) spectroscopy for chlorophyll prediction in oil palm leaves." Bulletin of Electrical Engineering and Informatics 8, no. 2 (June 1, 2019): 506–13. http://dx.doi.org/10.11591/eei.v8i2.1412.
Повний текст джерелаLarson, James E., Penelope Perkins-Veazie, and Thomas M. Kon. "Apple Fruitlet Abscission Prediction. II. Characteristics of Fruitlets Predicted to Persist or Abscise by Reflectance Spectroscopy Models." HortScience 58, no. 9 (September 2023): 1095–103. http://dx.doi.org/10.21273/hortsci17245-23.
Повний текст джерелаDamayanti, R., D. F. A. Riza, A. W. Putranto, and R. J. Nainggolan. "Vernonia Amygdalina Chlorophyll Content Prediction by Feature Texture Analysis of Leaf Color." IOP Conference Series: Earth and Environmental Science 757, no. 1 (May 1, 2021): 012026. http://dx.doi.org/10.1088/1755-1315/757/1/012026.
Повний текст джерелаKrishnapriya, Vengavasi, R. Arunkumar, R. Gomathi, and S. Vasantha. "PREDICTION MODELS FOR NON-DESTRUCTIVE ESTIMATION OF TOTAL CHLOROPHYLL CONTENT IN SUGARCANE." Journal of Sugarcane Research 9, no. 2 (December 31, 2019): 150. http://dx.doi.org/10.37580/jsr.2019.2.9.150-163.
Повний текст джерелаMa, Ling, Yao Zhang, Yiyang Zhang, Jing Wang, Jianshe Li, Yanming Gao, Xiaomin Wang, and Longguo Wu. "Rapid Nondestructive Detection of Chlorophyll Content in Muskmelon Leaves under Different Light Quality Treatments." Agronomy 12, no. 12 (December 19, 2022): 3223. http://dx.doi.org/10.3390/agronomy12123223.
Повний текст джерелаLin, Wenpeng, Xumiao Yu, Di Xu, Tengteng Sun, and Yue Sun. "Effect of Dust Deposition on Chlorophyll Concentration Estimation in Urban Plants from Reflectance and Vegetation Indexes." Remote Sensing 13, no. 18 (September 8, 2021): 3570. http://dx.doi.org/10.3390/rs13183570.
Повний текст джерелаSong, Yufei, Shiwu Li, Zhiguo Liu, Yuekui Zhang, and Nan Shen. "Analysis on Chlorophyll Diagnosis of Wheat Leaves Based on Digital Image Processing and Feature Selection." Traitement du Signal 39, no. 1 (February 28, 2022): 381–87. http://dx.doi.org/10.18280/ts.390140.
Повний текст джерелаShi, Hongzhao, Jinjin Guo, Jiaqi An, Zijun Tang, Xin Wang, Wangyang Li, Xiao Zhao, et al. "Estimation of Chlorophyll Content in Soybean Crop at Different Growth Stages Based on Optimal Spectral Index." Agronomy 13, no. 3 (February 24, 2023): 663. http://dx.doi.org/10.3390/agronomy13030663.
Повний текст джерелаAn, Gangqiang, Minfeng Xing, Binbin He, Chunhua Liao, Xiaodong Huang, Jiali Shang, and Haiqi Kang. "Using Machine Learning for Estimating Rice Chlorophyll Content from In Situ Hyperspectral Data." Remote Sensing 12, no. 18 (September 22, 2020): 3104. http://dx.doi.org/10.3390/rs12183104.
Повний текст джерелаLv, Gang, and Hai Qing Yang. "Nondestructive Measurement of Grape Leaf Chlorophyll Content Using Multi-Spectral Imaging Technology and Calibration Models." Advanced Engineering Forum 1 (September 2011): 365–69. http://dx.doi.org/10.4028/www.scientific.net/aef.1.365.
Повний текст джерелаEswari, Jujjavarapu Satya, Manwendra Kumar Tripathi, Swasti Dhagat, and Santosh Kr Karn. "Five Objective Optimization Using Naïve & Sorting Genetic Algorithm (NSGA) for Green Microalgae Culture Conditions for Biodiesel Production." Recent Innovations in Chemical Engineering (Formerly Recent Patents on Chemical Engineering) 12, no. 2 (September 26, 2019): 110–21. http://dx.doi.org/10.2174/2405520412666190124163629.
Повний текст джерелаLin, W. C., J. W. Hall, and A. Klieber. "Video Imaging for Quantifying Cucumber Fruit Color." HortTechnology 3, no. 4 (October 1993): 436–39. http://dx.doi.org/10.21273/horttech.3.4.436.
Повний текст джерелаFlorence, Anna, Andrew Revill, Stephen Hoad, Robert Rees, and Mathew Williams. "The Effect of Antecedence on Empirical Model Forecasts of Crop Yield from Observations of Canopy Properties." Agriculture 11, no. 3 (March 18, 2021): 258. http://dx.doi.org/10.3390/agriculture11030258.
Повний текст джерелаKang, Yeseong, Jinwoo Nam, Younggwang Kim, Seongtae Lee, Deokgyeong Seong, Sihyeong Jang, and Chanseok Ryu. "Assessment of Regression Models for Predicting Rice Yield and Protein Content Using Unmanned Aerial Vehicle-Based Multispectral Imagery." Remote Sensing 13, no. 8 (April 14, 2021): 1508. http://dx.doi.org/10.3390/rs13081508.
Повний текст джерелаJi, Jiangtao, Nana Li, Hongwei Cui, Yuchao Li, Xinbo Zhao, Haolei Zhang, and Hao Ma. "Study on Monitoring SPAD Values for Multispatial Spatial Vertical Scales of Summer Maize Based on UAV Multispectral Remote Sensing." Agriculture 13, no. 5 (May 2, 2023): 1004. http://dx.doi.org/10.3390/agriculture13051004.
Повний текст джерелаKamenova, Ilina, Petar Dimitrov, and Rusina Yordanova. "Evaluation of RapidEye vegetation indices for prediction of biophysical/biochemical variables of winter wheat." Aerospace Research in Bulgaria 30 (2018): 63–74. http://dx.doi.org/10.3897/arb.v30.e06.
Повний текст джерелаTa, Na, Qingrui Chang, and Youming Zhang. "Estimation of Apple Tree Leaf Chlorophyll Content Based on Machine Learning Methods." Remote Sensing 13, no. 19 (September 29, 2021): 3902. http://dx.doi.org/10.3390/rs13193902.
Повний текст джерелаZhang, Ying, Xiao Hu Zhao, and Cai Juan Li. "Soft Sensing for Algae Blooms Based on Physical-Chemical Factors of Marine Environment." Applied Mechanics and Materials 58-60 (June 2011): 630–35. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.630.
Повний текст джерелаZillmann, E., M. Schönert, H. Lilienthal, B. Siegmann, T. Jarmer, P. Rosso, and T. Weichelt. "Crop Ground Cover Fraction and Canopy Chlorophyll Content Mapping using RapidEye imagery." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 28, 2015): 149–55. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-149-2015.
Повний текст джерелаAbdel-Sattar, Mahmoud, Adel Al-Saif, Abdulwahed Aboukarima, Dalia Eshra, and Lidia Sas-Paszt. "Quality Attributes Prediction of Flame Seedless Grape Clusters Based on Nutritional Status Employing Multiple Linear Regression Technique." Agriculture 12, no. 9 (August 25, 2022): 1303. http://dx.doi.org/10.3390/agriculture12091303.
Повний текст джерелаYu, Siyao, Haoran Bu, Xue Hu, Wancheng Dong, and Lixin Zhang. "Establishment and Accuracy Evaluation of Cotton Leaf Chlorophyll Content Prediction Model Combined with Hyperspectral Image and Feature Variable Selection." Agronomy 13, no. 8 (August 13, 2023): 2120. http://dx.doi.org/10.3390/agronomy13082120.
Повний текст джерелаQian, Ji, Juan Zhou, and Yang Liu. "Labview-based Study on the Modeling Method of Chlorophyll Content Prediction in Tomato Leaves." Advances in Modelling and Analysis B 60, no. 2 (June 30, 2017): 416–28. http://dx.doi.org/10.18280/ama_b.600211.
Повний текст джерелаPaul, Subir, Vinayaraj Poliyapram, Nevrez Imamoglu, Kuniaki Uto, Ryosuke Nakamura, and D. Nagesh Kumar. "Canopy Averaged Chlorophyll Content Prediction of Pear Trees Using Convolutional Autoencoder on Hyperspectral Data." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13 (2020): 1426–37. http://dx.doi.org/10.1109/jstars.2020.2983000.
Повний текст джерелаYuan, Jianqing, Zhongbin Su, Qingming Kong, Li Kang, Qi Zhang, and Yu Zhang. "Hyperspectral Response of Rice Canopy and Prediction of Its Chlorophyll Content in Cold Regions." International Journal of u- and e-Service, Science and Technology 8, no. 10 (October 31, 2015): 75–82. http://dx.doi.org/10.14257/ijunesst.2015.8.10.08.
Повний текст джерелаHoel, Bernt Olav. "Chlorophyll Meter Readings in Winter Wheat: Cultivar Differences and Prediction of Grain Protein Content." Acta Agriculturae Scandinavica, Section B — Soil & Plant Science 52, no. 4 (January 2002): 147–57. http://dx.doi.org/10.1080/090647103100004843.
Повний текст джерелаShanmugapriya, P., K. R. Latha, S. Pazhanivelan, R. Kumaraperumal, G. Karthikeyan, and N. S. Sudarmanian. "Spatial prediction of leaf chlorophyll content in cotton crop using drone-derived spectral indices." Current Science 123, no. 12 (December 25, 2022): 1473. http://dx.doi.org/10.18520/cs/v123/i12/1473-1480.
Повний текст джерелаWang, Jinghua, Xiang Li, Wancheng Wang, Fan Wang, Quancheng Liu, and Lei Yan. "Research on Rapid and Low-Cost Spectral Device for the Estimation of the Quality Attributes of Tea Tree Leaves." Sensors 23, no. 2 (January 4, 2023): 571. http://dx.doi.org/10.3390/s23020571.
Повний текст джерелаEze, Elias, Sam Kirby, John Attridge, and Tahmina Ajmal. "Time Series Chlorophyll-A Concentration Data Analysis: A Novel Forecasting Model for Aquaculture Industry." Engineering Proceedings 5, no. 1 (June 29, 2021): 27. http://dx.doi.org/10.3390/engproc2021005027.
Повний текст джерелаLiu, Chuang, Yi Liu, Yanhong Lu, Yulin Liao, Jun Nie, Xiaoliang Yuan, and Fang Chen. "Use of a leaf chlorophyll content index to improve the prediction of above-ground biomass and productivity." PeerJ 6 (January 11, 2019): e6240. http://dx.doi.org/10.7717/peerj.6240.
Повний текст джерелаQiao, Lang, Dehua Gao, Junyi Zhang, Minzan Li, Hong Sun, and Junyong Ma. "Dynamic Influence Elimination and Chlorophyll Content Diagnosis of Maize Using UAV Spectral Imagery." Remote Sensing 12, no. 16 (August 17, 2020): 2650. http://dx.doi.org/10.3390/rs12162650.
Повний текст джерелаGeorgiopoulou, Ioulia, Soultana Tzima, Georgia D. Pappa, Vasiliki Louli, Epaminondas Voutsas, and Kostis Magoulas. "Experimental Design and Optimization of Recovering Bioactive Compounds from Chlorella vulgaris through Conventional Extraction." Molecules 27, no. 1 (December 22, 2021): 29. http://dx.doi.org/10.3390/molecules27010029.
Повний текст джерелаNemeskéri, Eszter, and Lajos Helyes. "Physiological Responses of Selected Vegetable Crop Species to Water Stress." Agronomy 9, no. 8 (August 13, 2019): 447. http://dx.doi.org/10.3390/agronomy9080447.
Повний текст джерелаZhu, Jiyou, Weijun He, Jiangming Yao, Qiang Yu, Chengyang Xu, Huaguo Huang, and Catherine Mhae B. Jandug. "Spectral Reflectance Characteristics and Chlorophyll Content Estimation Model of Quercus aquifolioides Leaves at Different Altitudes in Sejila Mountain." Applied Sciences 10, no. 10 (May 24, 2020): 3636. http://dx.doi.org/10.3390/app10103636.
Повний текст джерелаKumar, Chandan, Partson Mubvumba, Yanbo Huang, Jagman Dhillon, and Krishna Reddy. "Multi-Stage Corn Yield Prediction Using High-Resolution UAV Multispectral Data and Machine Learning Models." Agronomy 13, no. 5 (April 28, 2023): 1277. http://dx.doi.org/10.3390/agronomy13051277.
Повний текст джерелаEvans, Marlene S., Richard D. Robarts, and Michael T. Arts. "Predicted versus actual determinations of algal production, algal biomass, and zooplankton biomass in a hypereutrophic, hyposaline prairie lake." Canadian Journal of Fisheries and Aquatic Sciences 52, no. 5 (May 1, 1995): 1037–49. http://dx.doi.org/10.1139/f95-102.
Повний текст джерела王, 博. "Prediction of Chlorophyll Content in Rice under Arsenic Stress Based on Dynamic Fuzzy Neural Network Model." Advances in Environmental Protection 07, no. 05 (2017): 404–13. http://dx.doi.org/10.12677/aep.2017.75054.
Повний текст джерелаMatsunaka, Teruo, Yuji Watanabe, Tadashi Miyawaki, and Nobuo Ichikawa. "Prediction of grain protein content in winter wheat through leaf color measurements using a chlorophyll meter." Soil Science and Plant Nutrition 43, no. 1 (March 1997): 127–34. http://dx.doi.org/10.1080/00380768.1997.10414721.
Повний текст джерелаHaboudane, Driss, John R. Miller, Nicolas Tremblay, Pablo J. Zarco-Tejada, and Louise Dextraze. "Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture." Remote Sensing of Environment 81, no. 2-3 (August 2002): 416–26. http://dx.doi.org/10.1016/s0034-4257(02)00018-4.
Повний текст джерелаCroft, H., J. M. Chen, Y. Zhang, A. Simic, T. L. Noland, N. Nesbitt, and J. Arabian. "Evaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework." ISPRS Journal of Photogrammetry and Remote Sensing 102 (April 2015): 85–95. http://dx.doi.org/10.1016/j.isprsjprs.2015.01.008.
Повний текст джерелаWibowo, Fachrina. "Prediction of gene action content of Na, K, and Chlorophyll for Soybean Crop Adaptation to Salinity." JERAMI Indonesian Journal of Crop Science 2, no. 1 (September 1, 2019): 21–28. http://dx.doi.org/10.25077/jijcs.2.1.21-28.2019.
Повний текст джерелаPutra, Kielvien Lourensius Eka Setia, Fabian Surya Pramudya, Alexander Agung Santoso Gunawan, and Prasetyo Mimboro. "Predicting Nitrogen Content in Oil Palms through Machine Learning and RGB Aerial Imagery." International Journal of Emerging Technology and Advanced Engineering 13, no. 6 (June 25, 2023): 19–27. http://dx.doi.org/10.46338/ijetae0623_03.
Повний текст джерелаZeng, Linglin, Guozhang Peng, Ran Meng, Jianguo Man, Weibo Li, Binyuan Xu, Zhengang Lv, and Rui Sun. "Wheat Yield Prediction Based on Unmanned Aerial Vehicles-Collected Red–Green–Blue Imagery." Remote Sensing 13, no. 15 (July 26, 2021): 2937. http://dx.doi.org/10.3390/rs13152937.
Повний текст джерелаMineeva, N. M. "Evaluation of Nutrient-Chlorophyll Relationships in the Rybinsk Reservoir." Water Science and Technology 28, no. 6 (September 1, 1993): 25–28. http://dx.doi.org/10.2166/wst.1993.0125.
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