Yield Prediction and Growth Mode Characterization of Greenhouse Tomatoes with Neural Networks and Fuzzy Logic-Reference-Cited by-同舟云学术

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Yield Prediction and Growth Mode Characterization of Greenhouse Tomatoes with Neural Networks and Fuzzy Logic

Published:2009 Issue:6 Volume:52 Page:2115-2128
ISSN:2151-0040
Container-title:Transactions of the ASABE
language:en
Short-container-title:

Author:

E. Fitz-Rodríguez ,G. A. Giacomelli

Publisher

American Society of Agricultural and Biological Engineers (ASABE)

Subject

Soil Science,Agronomy and Crop Science,Biomedical Engineering,Food Science,Forestry

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Estimating hydroponic lettuce phenotypic parameters for efficient resource allocation;Computers and Electronics in Agriculture;2024-03

2. Prediction Model of Greenhouse Tomato Yield Using Data Based on Different Soil Fertility Conditions;Agronomy;2023-07-17

3. Comprehensive review of yield prediction models of greenhouse tomato;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20

4. Monitoring and control of environmental parameters to predict growth in citrus crops using Machine Learning;2022 7th International Conference on Machine Learning Technologies (ICMLT);2022-03-11

5. Artificial intelligence approaches to predict growth, harvest day, and quality of lettuce (Lactuca sativa L.) in a IoT-enabled greenhouse system;Biosystems Engineering;2021-12

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