Non-destructive assessment of apricot fruit quality by portable visible-near infrared spectroscopy-Reference-Cited by-同舟云学术

Non-destructive assessment of apricot fruit quality by portable visible-near infrared spectroscopy

Published:2009-07 Issue:6 Volume:42 Page:1125-1131
ISSN:0023-6438
Container-title:LWT - Food Science and Technology
language:en
Short-container-title:LWT - Food Science and Technology

Author:

Camps C.,Christen D.

Publisher

Elsevier BV

Subject

Food Science

Reference31 articles.

1. Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra;Barnes;Applied Spectroscopy,1989

2. Application of Fourier-transform infrared (FT-IR) spectroscopy for the evaluation of quality traits in apricot fruits;Bureau;Acta Horticulturae (ISHS),2006

3. Discrimination of storage duration of apples stored in a cooled room and shelf-life by visible-near infrared spectroscopy;Camps;Journal of Near Infrared Spectroscopy,2007

4. Camps, C., Guillermin, P., Mauget, J. C., & Bertrand, D. (2007b). Measurement of textural properties of apple and their prediction by near infrared reflectance spectroscopy. In FRUTIC 05. Proceeding of the 7th fruit, nut and vegetable production engineering symposium: Information and technology for sustainable fruit and vegetable production. Montpellier, France.

5. Vis-NIR measurement of soluble solids in cherry and apricot by PLS regression and wavelength selection;Carlini;Journal of Agricultural and Food Chemistry,2000

Cited by 130 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. Variability of index of absorbance difference (I_AD) to indicate fruit maturity at harvest for major apple cultivars in Ontario;Canadian Journal of Plant Science;2024-02-01

2. A Performance Evaluation of Two Hyperspectral Imaging Systems for the Prediction of Strawberries’ Pomological Traits;Sensors;2023-12-28

3. Banana Ripeness Classification with Deep CNN on NVIDIA Jetson Xavier AGX;2023 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC);2023-10-11

4. Classification of strawberry ripeness stages using machine learning algorithms and colour spaces;Horticulture, Environment, and Biotechnology;2023-10-02

5. Bibliometrics and Visual Analysis of Non-Destructive Testing Technology for Fruit Quality;Horticulturae;2023-09-30