Identification of Sicilian landraces and Canadian cultivars of lentil using an image analysis system

被引:56
作者
Venora, G.
Grillo, O.
Shahin, M. A.
Symons, S. J.
机构
[1] Stn Sperimentale Granicoltura Sicilia, I-95041 Caltagirone, CT, Italy
[2] Canadian Grain Commiss, Winnipeg, MB R3C 3G8, Canada
关键词
computer technology; image analysis; Lens culinaris Medik; lentil identification;
D O I
10.1016/j.foodres.2006.09.001
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Seed colour and size determine the appearance of grain legumes such as lentils (Lens culinaris Medik.). Currently, these characteristics are assessed by visual inspection of grain; it is slow and subjective, for this reason an objective imaging system was developed in Canada to measure bulk seeds lentil colour and size in a consistent manner for lentil quality colour grading. The Canadian imaging method, using image captured by a flatbed scanner, was modified in collaboration with the Stazione Sperimentale di Granicoltura (Research Institute in Sicily) to measure seed size, shape and mean colour on individual seeds; each seed imaging data were computed with a Linear Discriminant Analysis (Classifier) to identify five Sicilian landraces of Lens culinaris Medik., precisely Aragona, Bronte, Leonforte, Ustica and Villalba and three common Canadian accessions, cv Laird, ev Crimson and cv Eston. The performance of the classifier was 99.8% for the training sets and 97.1% for the independent test set. In addition to commercial international trade, lentil seed characterisation is very important to identify and catalogue in a biodiversity conservation program. Crown Copyright (c) 2006 Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:161 / 166
页数:6
相关论文
共 27 条
[1]  
BOZZINI A, 1988, LINFORMATORE AGRARIO, V25, P35
[2]  
BOZZINI A, 1988, LINFORMATORE AGRARIO, V25, P27
[3]  
CHURCHILL DB, 1992, T ASAE, V35, P61, DOI 10.13031/2013.28570
[4]  
Cubero J. I., 1981, Lentils, P15
[5]  
GALLO G, 1997, CONVEGNO BIODIVERSIT, P279
[6]  
Granitto PM, 2003, J COMPUTER SCI TECHN, V3, P34
[7]  
*ISTAT, 2005, I NAZ STAT ANN REP
[8]   REAL-TIME DETECTION OF COLOR AND SURFACE-DEFECTS OF MAIZE KERNELS USING MACHINE VISION [J].
LIAO, K ;
PAULSEN, MR ;
REID, JF .
JOURNAL OF AGRICULTURAL ENGINEERING RESEARCH, 1994, 59 (04) :263-271
[9]   DISCRIMINATION OF WHEAT CLASS AND VARIETY BY DIGITAL IMAGE-ANALYSIS OF WHOLE GRAIN SAMPLES [J].
NEUMAN, M ;
SAPIRSTEIN, HD ;
SHWEDYK, E ;
BUSHUK, W .
JOURNAL OF CEREAL SCIENCE, 1987, 6 (02) :125-132
[10]   COMPUTER IMAGE ANALYSES FOR DETECTION OF MAIZE AND SOYBEAN KERNEL QUALITY FACTORS [J].
PAULSEN, MR ;
WIGGER, WD ;
LITCHFIELD, JB ;
SINCLAIR, JB .
JOURNAL OF AGRICULTURAL ENGINEERING RESEARCH, 1989, 43 (02) :93-101