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EASY LEAF AREA: AUTOMATED DIGITAL IMAGE ANALYSIS FOR RAPID AND ACCURATE MEASUREMENT OF LEAF AREA
被引:350
作者:
Easlon, Hsien Ming
[1
]
Bloom, Arnold J.
[1
]
机构:
[1] Univ Calif Davis, Dept Plant Sci, Davis, CA 95616 USA
来源:
APPLICATIONS IN PLANT SCIENCES
|
2014年
/
2卷
/
07期
基金:
美国国家科学基金会;
关键词:
Arabidopsis;
digital images;
leaf area;
!text type='Python']Python[!/text;
ARABIDOPSIS-THALIANA;
D O I:
10.3732/apps.1400033
中图分类号:
Q94 [植物学];
学科分类号:
071001 ;
摘要:
Premise of the study: Measurement of leaf areas from digital photographs has traditionally required significant user input unless backgrounds are carefully masked. Easy Leaf Area was developed to batch process hundreds of Arabidopsis rosette images in minutes, removing background artifacts and saving results to a spreadsheet-ready CSV file. Methods and Results: Easy Leaf Area uses the color ratios of each pixel to distinguish leaves and calibration areas from their background and compares leaf pixel counts to a red calibration area to eliminate the need for camera distance calculations or manual ruler scale measurement that other software methods typically require. Leaf areas estimated by this software from images taken with a camera phone were more accurate than ImageJ estimates from flatbed scanner images. Conclusions: Easy Leaf Area provides an easy-to-use method for rapid measurement of leaf area and nondestructive estimation of canopy area from digital images.
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