Models to improve the non-destructive analysis of persimmon fruit properties by VIS/NIR spectrometry

Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy

(2017) Victoria Cortés et al.   JOURNAL OF FOOD ENGINEERING

Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging

(2017) Sandra Munera et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Astringency assessment of persimmon by hyperspectral imaging

(2017) Sandra Munera et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

On-line measure of donkey's milk properties by near infrared spectrometry

(2016) Giuseppe Altieri et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

uality Evaluation of “Tardivo di Ciaculli” Mandarins in Post-Harvest Processing on an Industrial Scale Using a Portable Vis/NIR Device

(2016)   Transactions of the ASABE

Evaluation of Astringency and Tannin Content in ‘Xichu’ Persimmons Using Near Infrared Spectroscopy

(2015) Sirinad Noypitak et al.   INTERNATIONAL JOURNAL OF FOOD PROPERTIES

On-line application of near infrared (NIR) spectroscopy in food production

(2015) Jan U. Porep et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

Evaluation of common pre-processing approaches for visible (VIS) and shortwave near infrared (SWNIR) spectroscopy in soluble solids content (SSC) assessment

(2013) Kim Seng Chia et al.   BIOSYSTEMS ENGINEERING

Towards combinatorial spectroscopy: The case of minor milk fatty acids determination

(2013) I. Stefanov et al.   TALANTA

Prediction of the type of milk and degree of ripening in cheeses by means of artificial neural networks with data concerning fatty acids and near infrared spectroscopy

(2013) Milton Carlos Soto-Barajas et al.   TALANTA

Non-destructive prediction and visualization of chemical composition in lamb meat using NIR hyperspectral imaging and multivariate regression

(2012) Mohammed Kamruzzaman et al.   Innovative Food Science & Emerging Technologies

Measurement of Single Soybean Seed Attributes by Near-Infrared Technologies. A Comparative Study

(2012) Lidia Esteve Agelet et al.   JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY

On-line analysis of intact olive fruits by vis–NIR spectroscopy: Optimisation of the acquisition parameters

(2012) Lourdes Salguero-Chaparro et al.   JOURNAL OF FOOD ENGINEERING

A comparative study for the quantitative determination of soluble solids content, pH and firmness of pears by Vis/NIR spectroscopy

(2012) Jiangbo Li et al.   JOURNAL OF FOOD ENGINEERING

Neural network and principal component regression in non-destructive soluble solids content assessment: a comparison

(2012) Kim-seng Chia et al.   Journal of Zhejiang University-SCIENCE B

Support vector machine regression (SVR/LS-SVM)—an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data

(2011) Roman M. Balabin et al.   ANALYST

Multivariate data analysis applied to spectroscopy: Potential application to juice and fruit quality

(2011) D. Cozzolino et al.   FOOD RESEARCH INTERNATIONAL

Phenolics concentration and antioxidant capacity of different fruit tissues of astringent versus non-astringent persimmons

(2011) Peng-Min Li et al.   SCIENTIA HORTICULTURAE

A comparison of regression tree ensembles: Predicting Sirex noctilio induced water stress in Pinus patula forests of KwaZulu-Natal, South Africa

(2009) R. Ismail et al.   International Journal of Applied Earth Observation and Geoinformation

Nondestructive measurement of soluble solid content of navel orange fruit by visible–NIR spectrometric technique with PLSR and PCA-BPNN

(2009) Yande Liu et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Rapid and non-destructive analysis of apricot fruit quality using FT-near-infrared spectroscopy

(2008) Sylvie Bureau et al.   FOOD CHEMISTRY

A working guide to boosted regression trees

(2008) J. Elith et al.   JOURNAL OF ANIMAL ECOLOGY