Abstract
In this study, we develop a spectral method for assessment of pasture quality based only on the spectral information obtained with a small number of wavelengths. First, differences in spectral behavior were identified across the near infrared–shortwave infrared spectral range that were indicative of changes in chemical properties. Then, slopes across different spectral ranges were calculated and correlated with the changes in crude protein (CP), neutral detergent fiber (NDF) and metabolic energy concentration (MEC). Finally, partial least squares (PLS) regression analysis was applied to identify the optimal spectral ranges for accurate assessment of CP, NDF and MEC. Six spectral domains and a set of slope criteria for real-time evaluation of pasture quality were suggested. The evaluation of three level categories (low, medium, high) for these three parameters showed a success rate of: 73%–96% for CP, 72%–87% for NDF and 60%–85% for MEC. Moreover, only one spectral range, 1748–1764 nm, was needed to provide a good estimation of CP, NDF and MEC. Importantly, five of the six selected spectral regions were not affected by water absorbance. With some modifications, this rationale can be applied to further analyses of pasture quality from airborne sensors.
Highlights
Rangelands play a socioeconomic role in semiarid zones as they support the economy and culture of pastoral societies [1]
Increases or decreases in spectral slope as function of crude protein (CP) content were obtained for the other spectral ranges (Figure 1b)
Assessing pasture quality using only slope-based criteria (Table 2), we found that in general, the total success rates were good for: (1) CP at 72%–80%, 50%–74% and 84%–98%; (2) neutral detergent fiber (NDF) at 6%9–77%, 37%–72% and 79%–94%, (3) metabolic energy concentration (MEC) at 56%–87%, 46%–60% and 79%–89%
Summary
Rangelands play a socioeconomic role in semiarid zones as they support the economy and culture of pastoral societies [1]. Rangelands are under constant threat of encroachment by humans, invasion by noxious plants, degradation and erosion processes and drought. It is crucial to monitor pasture quality in these regions. The quality of plants consumed by livestock in pastures is an important factor for their productivity. The potential food’s quality is assessed by indicators, such as: crude protein (CP) concentration, cell-wall components (NDF—neutral detergent fiber and ADF—acid detergent fiber), digestibility, and metabolic energy concentration (MEC). The most widely accepted method for assessing these indicators is chemical analysis [2,3,4]. Chemical measurements are relatively expensive and time-consuming
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