المؤلفون: Tongrui Zhang, Qinhao Jian, Xinzhuan Yao, Li Guan, Linlin Li, Fei Liu, Can Zhang, Dan Li, Hu Tang, Litang Lu

المصدر: Heliyon, Vol 10, Iss 10, Pp e31553- (2024)

مصطلحات موضوعية: Plant growth-promoting, PGPR biological agents, Camellia sinensis, Nicotiana tabacum, Capsicum annuum, Tea yield, Science (General), Q1-390, Social sciences (General), H1-99

وصف الملف: electronic resource

العلاقة: http://www.sciencedirect.com/science/article/pii/S2405844024075844Test; https://doaj.org/toc/2405-8440Test

الوصول الحر: https://doaj.org/article/c3391cdfeafd440aa499b7c8965d4285Test

المؤلفون: Zeeshan Ramzan, H. M. Shahzad Asif, Irfan Yousuf, Muhammad Shahbaz

المصدر: IEEE Access, Vol 11, Pp 42578-42594 (2023)

مصطلحات موضوعية: Multimodal, data fusion, deep neural networks, crop yield forecasting tea yield, Pakistan, satellite imagery, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

العلاقة: https://ieeexplore.ieee.org/document/10110955Test/; https://doaj.org/toc/2169-3536Test

الوصول الحر: https://doaj.org/article/0766b021dcc048bd8f6af45fe8f7c697Test

المؤلفون: Lili Sun, Zhaoliang Zhang, Yeyun Li, Jianyun Ruan, Tanmoy Karak, Tianyuan Yang

المصدر: Frontiers in Plant Science, Vol 14 (2023)

مصطلحات موضوعية: Camellia sinensis (L.) O. Ktze, mineral nutrients, tea yield and quality formation, fertilizer, efficient use of nutrients, Plant culture, SB1-1110

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/articles/10.3389/fpls.2023.1192432/fullTest; https://doaj.org/toc/1664-462XTest

الوصول الحر: https://doaj.org/article/88effda23f8648b5b2cd4ca935fca12fTest

المؤلفون: Caitlin Clarke, Brantlee Spakes Richter, Bala Rathinasabapathi

المصدر: Frontiers in Plant Science, Vol 14 (2023)

مصطلحات موضوعية: InDel markers, Nei’s genetic distance, Camellia sinensis, tea yield, biohistory, Plant culture, SB1-1110

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/articles/10.3389/fpls.2023.1149682/fullTest; https://doaj.org/toc/1664-462XTest

الوصول الحر: https://doaj.org/article/0428ce8f74224e56b6e912b91cdb667aTest

المؤلفون: Kourosh Majd Salimi, Reza Azadi Gonbad, Shahrzad Shaigan

المصدر: محیط زیست و مهندسی آب, Vol 8, Iss 1, Pp 63-78 (2022)

مصطلحات موضوعية: drip irrigation, drought, soil moisture, tea quality, tea yield, Environmental sciences, GE1-350, Water supply for domestic and industrial purposes, TD201-500

وصف الملف: electronic resource

العلاقة: http://www.jewe.ir/article_133607_ebaf2c6ce0c2627cea2f0ae4ee70bb42.pdfTest; https://doaj.org/toc/2476-3683Test

الوصول الحر: https://doaj.org/article/257291c92a314c2299703e1305fe12a6Test

المؤلفون: Chaudhuri, Priyasankar¹, Jamatia, Singh Kwrak Santua

المصدر: AGRICULTURAL SCIENCE DIGEST - A RESEARCH JOURNAL 41(2):274-281. 2021

المؤلفون: Jianghua Ye, Yuhua Wang, Jiaqian Kang, Yiling Chen, Lei Hong, Mingzhe Li, Yun Jia, Yuchao Wang, Xiaoli Jia, Zeyan Wu, Haibin Wang

المصدر: Plants, Vol 12, Iss 1, p 122 (2022)

مصطلحات موضوعية: tea tree (Camellia sinensis), soil acidification, sheep manure, nitrogen transformation, tea yield and quality, Botany, QK1-989

وصف الملف: electronic resource

العلاقة: https://www.mdpi.com/2223-7747/12/1/122Test; https://doaj.org/toc/2223-7747Test

الوصول الحر: https://doaj.org/article/bc92980e5ccc4fee850b020804cdcf19Test

المؤلفون: Jui, S. Janifer Jabin, Ahmed, A. A. Masrur, Bose, Aditi, Raj, Nawin, Sharma, Ekta, Soar, Jeffrey, Chowdhury, Md Wasique Islam

مصطلحات موضوعية: Bangladesh, Hybrid model, Machine learning, Meteorological variables, Satellite information, Tea yield

وصف الملف: application/pdf

العلاقة: https://research.usq.edu.au/download/befcb21a62c110e0269afe39f73d270c35cd29e71a0bef90eec581b6b935a892/29812586/remotesensingTest-tea%20562392.pdf; https://doi.org/10.3390/rs14030805Test; Jui, S. Janifer Jabin, Ahmed, A. A. Masrur, Bose, Aditi, Raj, Nawin, Sharma, Ekta, Soar, Jeffrey and Chowdhury, Md Wasique Islam. 2022. "Spatiotemporal Hybrid Random Forest Model for Tea Yield Prediction Using Satellite-Derived Variables." Remote Sensing. 14 (3), pp. 1-18. https://doi.org/10.3390/rs14030805Test

الإتاحة: https://doi.org/10.3390/rs14030805Test
https://research.usq.edu.au/item/q7166/spatiotemporal-hybrid-random-forest-model-forTest-tea-yield-prediction-using-satellite-derived-variables
https://research.usq.edu.au/download/befcb21a62c110e0269afe39f73d270c35cd29e71a0bef90eec581b6b935a892/29812586/remotesensingTest-tea%20562392.pdf

المؤلفون: Batool, Dania, Shahbaz, Muhammad, Shahzad Asif, Hafiz, Shaukat, Kamran, Alam, Talha Mahboob, Hameed, Ibrahim A., Ramzan, Zeeshan, Waheed, Abdul, Aljuaid, Hanan, Luo, Suhuai

المساهمون: The University of Newcastle. College of Engineering, Science & Environment, School of Information and Physical Sciences

مصطلحات موضوعية: crop simulation models, machine learning, AquaCrop, tea yield, crop yield prediction

العلاقة: Plants Vol. 11, Issue 15, no. 1925; http://hdl.handle.net/1959.13/1457136Test; uon:45299

الإتاحة: http://hdl.handle.net/1959.13/1457136Test

المؤلفون: Dania Batool, Muhammad Shahbaz, Hafiz Shahzad Asif, Kamran Shaukat, Talha Mahboob Alam, Ibrahim A. Hameed, Zeeshan Ramzan, Abdul Waheed, Hanan Aljuaid, Suhuai Luo

المصدر: Plants; Volume 11; Issue 15; Pages: 1925

مصطلحات موضوعية: crop simulation models, machine learning, AquaCrop, tea yield, crop yield prediction

جغرافية الموضوع: agris

وصف الملف: application/pdf

العلاقة: Plant Modeling; https://dx.doi.org/10.3390/plants11151925Test

الإتاحة: https://doi.org/10.3390/plants11151925Test