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Comparison of Laboratory and Field Remote Sensing Methods to Measure Forage Quality

Bibliographic Data

ID15470407
AuthorsXULIN GUO (0000-0001-9428-4267, University of Saskatchewan, corresponding author), John F Wilmshurst (Jasper National Park of Canada, Parks Canada, P.O. Box 10, Jasper, AB T0E 1E0, Canada), John Wilmshurst (0000-0003-4887-1334, Parks Canada), Zhaoqin Li (0000-0002-1020-8425, University of Saskatchewan)
Year2010
Volume7
Issue9
Pages3513-3530
Publication date2010-09-27
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph7093513
PMID20948940
PMCIDPMC2954561
OpenAlexW2054034328
LanguageEN
References cited56

Recent research in range ecology has emphasized the importance of forage quality as a key indicator of rangeland condition. However, we lack tools to evaluate forage quality at scales appropriate for management. Using canopy reflectance data to measure forage quality has been conducted at both laboratory and field levels separately, but little work has been conducted to evaluate these methods simultaneously. The objective of this study is to find a reliable way of assessing grassland quality through measuring forage chemistry with reflectance. We studied a mixed grass ecosystem in Grasslands National Park of Canada and surrounding pastures, located in southern Saskatchewan. Spectral reflectance was collected at both in-situ field level and in the laboratory. Vegetation samples were collected at each site, sorted into the green grass portion, and then sent to a chemical company for measuring forage quality variables, including protein, lignin, ash, moisture at 135 °C, Neutral Detergent Fiber (NDF), Acid Detergent Fiber (ADF), Total Digestible, Digestible Energy, Net Energy for Lactation, Net Energy for Maintenance, and Net Energy for Gain. Reflectance data were processed with the first derivative transformation and continuum removal method. Correlation analysis was conducted on spectral and forage quality variables. A regression model was further built to investigate the possibility of using canopy spectral measurements to predict the grassland quality. Results indicated that field level prediction of protein of mixed grass species was possible (r2 = 0.63). However, the relationship between canopy reflectance and the other forage quality variables was not strong

Agroforestry · Biology · Canopy · Forage · Geography · Grassland · Rangeland · Remote sensing · Vegetation (pathology · Environmental Science · Fire effects on ecosystems · Rangeland and Wildlife Management · Ruminant Nutrition and Digestive Physiology · Ecology

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