Monitoring effects of heavy metal stress on biochemical and spectral parameters of cotton using hyperspectral reflectance

Toxic effects of atmospheric deposition in mining areas on wheat seedlings

Storage and transportation of coal, as well as operation of coal-fired power plants, produce amounts of metallic exhaust that may lead to different atmospheric environment in the overlapped areas of farmland and coal resource (OAFCR) environment. To investigate the effects of different atmospheric environment in the OAFCR region (north of Xuzhou) on wheat seedlings (AK-58), a box experiment was conducted and compared to an area far from the OAFCR (south of Xuzhou). The study revealed that (1) compared to the southern suburb of Xuzhou, the fresh and dry weight, activities of photosynthetic enzymes and POD of wheat seedlings in the OAFCR reduced obviously. (2) Significantly higher levels of Cr, Cd, Pb, Zn, and Cu were found in the shoots and roots of wheat seedlings in the OAFCR, with lower transfer factor for heavy metals (except Cd and As) in comparison to those in the southern suburb. And the bioconcentration factors of heavy metals (except As) in wheat seedlings in the OAFCR were significantly higher. (3) Nearly 90% of heavy metals (Pb, Cu, Cd, Zn, and Cr) absorbed by wheat were stored in cell walls and soluble fractions, with significantly higher contents of Cu and Cr in wheat seedlings' cell walls and higher contents of Pb, Zn, and Cd in soluble components found in the OAFCR. Our results showed that atmospheric deposition in the mining area has a certain toxic effect on wheat seedlings, and this study provides a theoretical basis for OAFCR crop toxicity management.

Application of Visible/Near-Infrared Spectroscopy and Hyperspectral Imaging with Machine Learning for High-Throughput Plant Heavy Metal Stress Phenotyping: A Review

Heavy metal pollution is becoming a prominent stress on plants. Plants contaminated with heavy metals undergo changes in external morphology and internal structure, and heavy metals can accumulate through the food chain, threatening human health. Detecting heavy metal stress on plants quickly, accurately, and nondestructively helps to achieve precise management of plant growth status and accelerate the breeding of heavy metal-resistant plant varieties. Traditional chemical reagent-based detection methods are laborious, destructive, time-consuming, and costly. The internal and external structures of plants can be altered by heavy metal contamination, which can lead to changes in plants' absorption and reflection of light. Visible/near-infrared (V/NIR) spectroscopy can obtain plant spectral information, and hyperspectral imaging (HSI) can obtain spectral and spatial information in simple, speedy, and nondestructive ways. These 2 technologies have been the most widely used high-throughput phenotyping technologies of plants. This review summarizes the application of V/NIR spectroscopy and HSI in plant heavy metal stress phenotype analysis as well as introduces the method of combining spectroscopy with machine learning approaches for high-throughput phenotyping of plant heavy metal stress, including unstressed and stressed identification, stress types identification, stress degrees identification, and heavy metal content estimation. The vegetation indexes, full-range spectra, and feature bands identified by different plant heavy metal stress phenotyping methods are reviewed. The advantages, limitations, challenges, and prospects of V/NIR spectroscopy and HSI for plant heavy metal stress phenotyping are discussed. Further studies are needed to promote the research and application of V/NIR spectroscopy and HSI for plant heavy metal stress phenotyping.

Biostimulant and Bioinsecticidal Effect of Coating Cotton Seeds with Endophytic Beauveria bassiana in Semi-Field Conditions

Increasing commercial demands from the textile and food industries are putting strong pressure on the cultivation of cotton and its derivatives to produce high yields. At the same time, cotton has high nutrient and irrigation requirements and is highly susceptible to insect pests. Coating cotton seeds with beneficial fungi could address these problems. The aim of this study was to investigate the growth of cotton using (A) conventional seeds and (B) seeds coated with the entomopathogenic fungus Beauveria bassiana (Hypocreales: Cordycipitaceae). The experiment was conducted in a greenhouse of the Department of Agriculture of the University of Ioannina, in a completely randomized design. The growth characteristics of cotton plants were recorded weekly while the fresh weight and dry matter of the leaves, shoots and roots of the developed cotton plants were calculated at the end of the experiment. Weekly determination of total chlorophyll content (TCHL) was used as an indicator of plant robustness during the 80-day experiment. Many cotton growth parameters of treated plants, like number of leaves, shoots and apical buds, plant height, stem diameter, fresh and dried biomass and TCHL, were significantly higher than those of the untreated ones. Apart from plant growth, naturally occurring by Aphis gossypii (Hemiptera: Aphididae) infestation which also monitored for six weeks. A significantly lower aphid population was recorded for inoculated plants after the fifth week compared to the control. The overall evaluation revealed that B. bassiana coating treatments appear to have a significant biostimulatory and bioinsecticidal effect. Our results could represent responsive applications to the demands of intensive cotton growing conditions.