Improved prediction of minced pork meat chemical properties with near-infrared spectroscopy by a fusion of scatter-correction techniques

Sequential preprocessing through ORThogonalization (SPORT) and its application to near infrared spectroscopy

(2020) Jean-Michel Roger et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

SPORT pre-processing can improve near-infrared quality prediction models for fresh fruits and agro-materials

(2020) Puneet Mishra et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

VSN: Variable sorting for normalization

(2019) Gilles Rabatel et al.   JOURNAL OF CHEMOMETRICS

Prediction of beef meat fatty acid composition by visible-near-infrared spectroscopy was improved by preliminary freeze-drying

(2019) D. Andueza et al.   MEAT SCIENCE

Investigating the use of visible and near infrared spectroscopy to predict sensory and texture attributes of beef M. longissimus thoracis et lumborum

(2019) Jamie Cafferky et al.   MEAT SCIENCE

Near infrared spectroscopy: A mature analytical technique with new perspectives – A review

(2018) Celio Pasquini   ANALYTICA CHIMICA ACTA

Visible and near infrared spectroscopy as an authentication tool: Preliminary investigation of the prediction of the ageing time of beef steaks

(2018) Lara Moran et al.   MEAT SCIENCE

Predicting pork freshness using multi-index statistical information fusion method based on near infrared spectroscopy

(2018) Fangfang Qu et al.   MEAT SCIENCE

Detection of adulteration with duck meat in minced lamb meat by using visible near-infrared hyperspectral imaging

(2018) Xiaochun Zheng et al.   MEAT SCIENCE

Estimation of the intramuscular fat content of m. longissimus thoracis in crossbred beef cattle based on live animal measurements

(2017) Zenon Nogalski et al.   MEAT SCIENCE

Simple and Effective Way for Data Preprocessing Selection Based on Design of Experiments

(2015) Jan Gerretzen et al.   ANALYTICAL CHEMISTRY

Prediction of pork quality with near infrared spectroscopy (NIRS) 2. Feasibility and robustness of NIRS measurements under production plant conditions

(2012) C. Kapper et al.   MEAT SCIENCE

Preference mapping by PO-PLS: Separating common and unique information in several data blocks

(2011) Ingrid Måge et al.   FOOD QUALITY AND PREFERENCE