Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology

Abstract

Heavy metal pollution of croplands is a major environmental problem worldwide. Methods for accurately and quickly monitoring heavy metal stress have important practical significance. Many studies have explored heavy metal stress in rice in relation to physiological function or physiological factors, but few studies have considered phenology, which can be sensitive to heavy metal stress. In this study, we used an integrated Normalized Difference Vegetation Index (NDVI) time-series image set to extract remote sensing phenology. A phenological indicator relatively sensitive to heavy metal stress was chosen from the obtained phenological periods and phenological parameters. The Dry Weight of Roots (WRT), which directly affected by heavy metal stress, was simulated by the World Food Study (WOFOST) model; then, a feature space based on the phenological indicator and WRT was established for monitoring heavy metal stress. The results indicated that the feature space can distinguish the heavy metal stress levels in rice, with accuracy greater than 95% for distinguishing the severe stress level. This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice.

Classification of Rice Heavy Metal Stress Levels Based on Phenological Characteristics Using Remote Sensing Time-Series Images and Data Mining Algorithms

“…We selected the date with the maximum value of the first derivative to identify the active tillering phase, and the date that corresponded to zero of the second derivative was considered to be the maturity stage [35,36]. Studies [12,13,14,15,16,17] have shown that: (1) when the rice is exposed to heavy metal stress (e.g., from Cd), enzyme required for chlorophyll formation is inhibited, and chlorophyll content decreased, resulting in chlorosis symptoms in rice, which performed in the NDVI/EVI time-series is the reduction of maximum and minimum NDVI/EVI values; (2) the toxicity of heavy metals can influence the ability of organs to accept and convert photosynthetic products, resulting in reduced growth rate and the length of growth season; (3) the toxicity of heavy metals can also lead to other phenological changes, such as postponed heading date, decreased water content, delayed greening and maturation. Therefore, for unstressed rice, the EVI or NDVI values at heading dates and magnitude of the EVI or NDVI change might be larger than for stressed rice, and the time range from the end of transplanting to the heading date might be shorter compared to stressed rice.…”

“…Reed et al [27] verified that these indicators may not necessarily directly correspond to conventional, ground-based phenological events, but show strong coincidence with expected phenological characteristics. It has been proved that phenology can be a practical indicator for heavy metal stress in rice plants [16,17]; the significance of these indicators lies in the possibility to map out phenological changes in vegetation [58]. Basic details of the phenological signatures are listed in Table 2.…”

“…Combining spectral, temporal, and spatial information, the phenological features extracted using remote sensing technology reflect continuous growth and the stress state of rice throughout the entire growth stage. Time-series and phenological characteristics have been proved to be useful to monitor heavy metal stress in rice [10,16,17,18]. Phenological detection is implemented through analysis of time series of remotely-sensed images [19,20,21,22].…”

Role of Exogenous and Endogenous Hydrogen Sulfide (H2S) on Functional Traits of Plants Under Heavy Metal Stresses: A Recent Perspective

“… Ahmad et al (2020) demonstrated that NaHS treatment can upregulate antioxidant enzyme activity in Cr-exposed cauliflower seedlings, which is central to the amelioration of Cr-related oxidative damages, as well as reduction in metal ion translocation, to aerial plant parts. Root growth is an important predictor of plant productivity in agriculture, while impaired root growth has often been distinguished as one of the most common and earliest symptoms of plant exposure to metal toxicity ( Liu et al, 2018 ). In foxtail millet, Cd-induced root growth inhibition was reversed by an SO 2 derivative compound Na 2 SO 3 ( Han et al, 2020 ).…”

Integrated Method for Rice Cultivation Monitoring Using Sentinel-2 Data and Leaf Area Index

“…One of the main components of rice crop monitoring is yield estimation. Basically, yield of the main cereal crops is a global issue related directly to food security and human life [11] [12]. Crop yield estimation in an adequate time before harvest ensures more effective agricultural management policies.…”