PMID- 22483882
OWN - NLM
STAT- MEDLINE
DCOM- 20120813
LR  - 20120409
IS  - 1873-3573 (Electronic)
IS  - 0039-9140 (Linking)
VI  - 93
DP  - 2012 May 15
TI  - A portable Raman sensor for the rapid discrimination of olives according to fruit 
      quality.
PG  - 94-8
LID - 10.1016/j.talanta.2012.01.053 [doi]
AB  - In the real marketplace, providing high-quality olive oil is important from the 
      perspective of both consumers and producers. Quality control should meet all 
      requirements in the production process, from farm to packaging. The quality of 
      olive oil can be affected by several factors, including agricultural techniques, 
      seasonal conditions, farming systems, maturity, method and duration of storage, 
      and process technology. The quality of oil produced also depends largely on the 
      quality of the olives. In an enterprise aimed at producing high-quality oils, 
      olives with defects ('ground'; i.e., fallen to the ground) should be separated 
      from healthy fruit ('sound'; i.e., collected directly from the tree), because a 
      very small portion of low-quality fruit can ruin the whole batch. The fruit falls 
      partly because of its maturation process, but also because of pest and disease 
      attack or weather conditions (strong wind). Fruit that has fallen to the ground 
      can suffer a rapid deterioration in quality. Currently, the separation of fruits 
      is based mainly on visual inspection or information provided by the farmer. These 
      are not very reliable procedures. Methods using analytical parameters to 
      characterize the oil, such as acidity and peroxide value, can be applied, but 
      they require a lot of time and materials. Alternative techniques are therefore 
      needed for the rapid and inexpensive discrimination of olives as part of a 
      quality control strategy. The work described here aims to determine the potential 
      of low-resolution Raman spectroscopy for the discrimination of olives before the 
      oil processing stage in order to detect whether they have been collected directly 
      from the tree (i.e., healthy fruit) or not. Low-resolution Raman spectroscopy was 
      applied together with multivariate procedures to achieve this aim. PCA was used 
      to find natural clusters in the data. Supervised classification methods were then 
      applied: Soft Independent Modeling of Class Analogy (SIMCA), PLS Discriminate 
      Analysis (PLS-DA) and K-nearest neighbors (KNN). The best results were obtained 
      using the KNN method, with prediction abilities of 100% for 'sound' and 97% for 
      'ground' in an independent validation set. These results demonstrated the 
      potential of a portable Raman instrument for detecting good quality olives before 
      the oil processing stage, by developing models that could be applied before this 
      stage, thus contributing to an overall improvement in quality control.
CI  - Copyright (c) 2012 Elsevier B.V. All rights reserved.
FAU - Guzman, Elena
AU  - Guzman E
AD  - IFAPA Centro Venta del Llano, Crta. Nacional Bailen-Motril Km 18.5, 23620 
      Mengibar, Jaen, Spain. elena.guzman.jimenez@juntadeandalucia.es
FAU - Baeten, Vincent
AU  - Baeten V
FAU - Pierna, Juan Antonio Fernandez
AU  - Pierna JA
FAU - Garcia-Mesa, Jose A
AU  - Garcia-Mesa JA
LA  - eng
PT  - Journal Article
DEP - 20120202
PL  - Netherlands
TA  - Talanta
JT  - Talanta
JID - 2984816R
SB  - IM
MH  - Calibration
MH  - Food Handling/economics/*standards
MH  - Fruit/*chemistry
MH  - Olea/*chemistry
MH  - Quality Control
MH  - Reproducibility of Results
MH  - Spectrum Analysis, Raman/*instrumentation
MH  - Time Factors
EDAT- 2012/04/10 06:00
MHDA- 2012/08/14 06:00
CRDT- 2012/04/10 06:00
PHST- 2011/10/20 00:00 [received]
PHST- 2012/01/19 00:00 [revised]
PHST- 2012/01/29 00:00 [accepted]
PHST- 2012/04/10 06:00 [entrez]
PHST- 2012/04/10 06:00 [pubmed]
PHST- 2012/08/14 06:00 [medline]
AID - S0039-9140(12)00094-X [pii]
AID - 10.1016/j.talanta.2012.01.053 [doi]
PST - ppublish
SO  - Talanta. 2012 May 15;93:94-8. doi: 10.1016/j.talanta.2012.01.053. Epub 2012 Feb 
      2.