KEYWORDS: Phenology, Vegetation, Diseases and disorders, Climatology, Climate change, Humidity, Random forests, Data modeling, Clouds, Analytical research
The fungus Pestalotiopsis sp. causes aberrant leaf fall, resulting in an annual reduction in rubber production. The loss of latex yield has a significant impact on the income of smallholder farmers. The objective of this study is to estimate NDVI using reflectance from the upper canopy based on Sentinel-2 NDVI time series data and daily climate data, analyze phenological changes of rubber trees using a harmonic model and time-lag cross-correlation, and develop a prediction model of vegetation indices using the random forest regressor (RFR) algorithm. The study was conducted on the rubber plantation of the Indonesian Rubber Research Institute in Sembawa, Indonesia. Three rubber clones aged 10 to 11 years were used to study the wintering trend. The study found that the overall trend of the NDVI decreased significantly from 2019 to 2022. The cycle of defoliation and refoliation changed due to disease and climate change. The time lag effects of vegetation index and climate variables are crucial for predicting vegetation dynamics. Increasing temperature and changing precipitation play significant roles in influencing pathogen incidence. The mean absolute percentage error (MAPE) was used to evaluate the trend of the vegetation indices. The RFR algorithm predicts the vegetation indices with a MAPE of 6.07%, 5.96%, and 8.18% of BPM24, GT1, and RRIC 100, respectively. Our finding indicated that the analysis and prediction model can be used to understand the phenological pattern and predict the wintering pattern to prevent disease spread and minimize latex yield loss due to infestation outbreaks.
Leaf disease in rubber leaves causes a significant effect on latex production, especially Pestalotiopsis sp. This disease has caused a massive leaf fall in many plantations in Indonesia. Hyperspectral-based analysis can identify the difference in spectral leaf due to disease. The site location is Sembawa Rubber Research Institute in Sembawa, Palembang, Indonesia. Further, this study also compared other fungi leaf diseases, namely Oidium sp., Collectotrichum sp., and Corrynesspora sp. The leaf spectral reflectance was measured using Ocean Optics USB 2000+ UV-VIS Spectrometer, which measured the spectral response from 350-850 nm. This study aims at (a) defining the spectral signature of rubber leaf infected by leaf fall disease, b) analyzing whether the spectral response of infected leaf can be distinguished, and (c) defining the most useful wavelengths for discriminating spectral responses. The methodology used in this study is spectral response curve, principal components, and partial least square discriminant analyses. As a result, the average spectra indicated differences in color-infected leaves in the chlorophyll-associated wavelengths 490-589, 681–685, 718-752, and 839-875 nm. At the same time, the identification of disease type based on the spectral response found that it is not separable due to high similarity in the spectral curve.
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