Prediction of loquat soluble solids and titratable acid content using fruit mineral elements by artificial neural network and multiple linear regression-Reference-Cited by-同舟云学术

Prediction of loquat soluble solids and titratable acid content using fruit mineral elements by artificial neural network and multiple linear regression

Published:2021-02 Issue: Volume:278 Page:109873
ISSN:0304-4238
Container-title:Scientia Horticulturae
language:en
Short-container-title:Scientia Horticulturae

Author:

Huang Xiao,Wang Huakun,Luo Wenjie,Xue Song,Hayat Faisal,Gao Zhihong

Funder

Jiangsu Province Science Technology Independent Innovation Fund CX

Six Talent Peaks Project in Jiangsu Province

Publisher

Elsevier BV

Subject

Horticulture

Reference49 articles.

1. Modeling oil content of sesame (Sesamum indicum L.) using artificial neural network and multiple linear regression approaches.2018;Abdipour;J. Am. Oil Chem. Soc.,2018

2. Artificial neural networks and multiple linear regression as potential methods for modeling seed yield of safflower (Carthamus tinctorius L.);Abdipour;Ind. Crops Prod.,2019

3. Evaluating the potential of red edge position (REP) of hyperspectral remote sensing data for real time estimation of LAI & chlorophyll content of kinnow mandarin (Citrus reticulata) fruit orchards;Ali;Sci. Hortic.,2020

4. Predicting average regional yield and production of wheat in the Argentine Pampas by an artificial neural network approach;Alvarez;Eur. J. Agron.,2009

5. Influence of foliar and ground fertilization on yield, fruit quality, and soil, leaf, and fruit mineral nutrients in apple;Amiri;J. Plant Nutr.,2008

Cited by 57 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. Predictive modeling of patulin accumulation in apple lesions infected by Penicillium expansum using machine learning;Postharvest Biology and Technology;2024-11

2. Prediction of Total Soluble Solids Content Using Tomato Characteristics: Comparison Artificial Neural Network vs. Multiple Linear Regression;Applied Sciences;2024-09-02

3. Evaluation of Nutritional Values of Edible Algal Species Using a Shortwave Infrared Hyperspectral Imaging and Machine Learning Technique;Foods;2024-07-19

4. Critical Drop Height Prediction of Loquat Fruit Based on Some Engineering Properties with Machine Learning Approach;Agronomy;2024-07-13

5. Visualisation of moisture content distribution maps and classification of freshness level of loquats;Journal of Food Composition and Analysis;2024-07