We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Simple in‐field evaluation of moisture content in curing forage using normalized differece vegetation index (NDVI).
- Authors
Lim, Jihyun; Watanabe, Nariyasu; Yoshitoshi, Rena; Kawamura, Kensuke
- Abstract
Production of hay at a proper moisture level is critical to reduce the spontaneous heating and nutrient loss during the preservation phase. Herein, we explored a new method for estimating the moisture content (MC) of field curing forages that uses a portable spectroradiometer (400–900 nm) and a hand‐held normalized difference vegetation index (NDVI) meter. The spatial distributions were assessed by a multispectral camera with unmanned aerial vehicle (UAV) platform. Field spectral measurements were conducted daily at 10 random plots over six trials at four forage fields across the entire curing period. Multispectral imagery acquisition by UAV flights was conducted at one trial. The MC (wet basis) was determined using a forced‐air oven. For 400–900 nm spectral reflectance measured by the spectroradiometer, we conducted linear regression analyses between the MC and all available combinations of a normalized difference spectral index (NDSI(Band1, Band2) = (ρBand1 − ρBand2)/(ρBand1 + ρBand2), where ρλ is the apparent reflectance and λ is the wavelength in nm). The combinations that are generally used as greenness indices showed high coefficients of determination, for example, red and near infrared (R2 =.76, RMSE = 10.66%) and green and red (R2 =.81, RMSE = 9.57%). The NDVI meter and multispectral imagery showed the feasibility of NDVI (R2 =.79, RMSE = 8.58% and R2 =.89, RMSE = 6.74%, respectively) as a parameter to estimate the MC. We were able to verify the spatial variability of the MC in the field based on the NDVI imagery, which indicates that our method provides information for site‐specific management (e.g., partial swath manipulation) and for decision‐making regarding the harvest time and location.
- Subjects
NORMALIZED difference vegetation index; FORAGE; RANDOM fields; SPECTRAL reflectance; MOISTURE; DRONE aircraft; MARKOV random fields
- Publication
Grassland Science, 2020, Vol 66, Issue 4, p238
- ISSN
1744-6961
- Publication type
Article
- DOI
10.1111/grs.12275