Transpiration Prediction of Sweet Peppers Hydroponically-grown in Soilless Culture via Artificial Neural Network Using Environmental Factors in Greenhouse-Reference-Cited by-同舟云学术

Transpiration Prediction of Sweet Peppers Hydroponically-grown in Soilless Culture via Artificial Neural Network Using Environmental Factors in Greenhouse

Published:2017-10-01 Issue:4 Volume:26 Page:411-417
ISSN:2288-0992
Container-title:Protected horticulture and Plant Factory
language:en
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Author:

Nam Du Sung¹,Lee Joon Woo¹,Moon Tae Won¹,Son Jung Eek¹

Affiliation:

1. Department of Plant Science and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea

Funder

Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries

Publisher

The Korean Society for Bio-Environment Control

Subject

General Medicine

Link

https://www.ksbec.org/articles/pdf/doi/10.12791/KSBEC.2017.26.4.411.pdf

Reference22 articles.

1. Impact of drip and surface irrigation on growth, yield and WUE of capsicum (Capsicum annum L.)

2. Stomatal regulation in greenhouse crops: analysis and simulation

3. ON THE QUANTITATIVE EXPLANATION OF STOMATAL TRANSPIRATION

4. GRENNHOUSE TOMATO CROP TRANSPIRATION MODEL APPLICATION TO IRRIGATION CONTROL.

5. Weighing Lysimeters for Developing Crop Coefficients and Efficient Irrigation Practices for Vegetable Crops

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1. Estimation of actual crop evapotranspiration using artificial neural networks in tomato grown in closed soilless culture system;Agricultural Water Management;2023-06

2. Development of a transpiration model for precise irrigation control in tomato cultivation;Scientia Horticulturae;2020-06

3. Estimating transpiration rates of hydroponically-grown paprika via an artificial neural network using aerial and root-zone environments and growth factors in greenhouses;Horticulture, Environment, and Biotechnology;2019-10-25