Assessment of adaptive neuro-fuzzy inference system (ANFIS) to predict production and water productivity of lettuce in response to different light intensities and CO2 concentrations-Reference-Cited by-同舟云学术

Assessment of adaptive neuro-fuzzy inference system (ANFIS) to predict production and water productivity of lettuce in response to different light intensities and CO2 concentrations

Published:2021-12 Issue: Volume:258 Page:107201
ISSN:0378-3774
Container-title:Agricultural Water Management
language:en
Short-container-title:Agricultural Water Management

Author:

Esmaili Maryam,Aliniaeifard Sasan,Mashal Mahmoud,Vakilian Keyvan Asefpour,Ghorbanzadeh Parisa,Azadegan Behzad,Seif Mehdi,Didaran Fardad

Funder

University of Tehran

Iran National Science Foundation

Publisher

Elsevier BV

Subject

Earth-Surface Processes,Soil Science,Water Science and Technology,Agronomy and Crop Science

Reference67 articles.

1. Blue light improves vase life of carnation cut flowers through its effect on the antioxidant defense system;Aalifar;Front. Plant Sci.,2020

2. Optimal control of environmental conditions affecting lettuce plant growth in a controlled environment with artificial lighting: a review;Ahmed;South Afr. J. Bot.,2020

3. Does elevated atmospheric [CO2] alter diurnal C uptake and the balance of C and N metabolites in growing and fully expanded soybean leaves?;Ainsworth;J. Exp. Bot.,2007

4. Landside susceptibility mapping by geographical information system based multivariate statistical and deterministic models: in an artificial reservoir area at northern Turkey;Akgun;Geoscience,2016

5. Effect of solar ultraviolet-b plus end of day light and its exclusion on growth performance and dry weight accumulation of two sweet potato cultivars (Ipomoea batatas L.) on different altitudes;Alemu;Hortic. Sci. Technol.,2020

Cited by 31 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. Modeling Sustainable Biofuel Production from Tobacco Seeds by Implementing Response Surface Methodology (RSM) and Adaptive Neuro‐Fuzzy Inference System (ANFIS);Feedstocks for Sustainable Biodiesel Production;2024-08-30

2. Evaluating machine learning models in predicting GRI drought indicators (case study: Ajabshir area);Applied Water Science;2024-08-22

3. Evaluating machine learning models in predicting dam inflow and hydroelectric power production in multi-purpose dams (case study: Mahabad Dam, Iran);Applied Water Science;2024-08-20

4. Amber LEDs outperform red, blue, and red-blue-amber LEDs for lettuce;The Journal of Horticultural Science and Biotechnology;2024-04-29

5. An approach for flood flow prediction utilizing new hybrids of ANFIS with several optimization techniques: a case study;Hydrology Research;2024-04-29