Soil Contaminant Stress in Leafy Greens - Insights from Hyperspectral Imaging and Microbiome Analysis

Abstract

Contamination of agricultural soils is a growing concern, threatening food security and human health. Heavy metals and micro- nanoplastics (MNP) are among the most problematic contaminants, increasingly prevalent in environmental samples. These materials can stress plants, reduce productivity and may increase risk to other external stress factors such as drought. Additionally, they may also be taken up by plant roots and stored within edible tissues, which can be especially problematic for leafy green crops like spinach and lettuce. Strategies to address these challenges include breeding crops with lower contaminant uptake and promoting beneficial root microbial relationships, mediating stress responses and further reducing uptake. However, developing these solutions is difficult, since despite their toxicity, these soil contaminants generally do not produce visible symptoms of plant stress. New technologies such as hyperspectral imaging (HSI) has the potential to help overcome this difficulty by detecting subtle physiological changes and uncovering mechanisms plants use to respond to the presence of these contaminants. To investigate these hypotheses, two studies were conducted in Purdue’s Ag Alumni Phenotyping facility. In the first experiment, HSI and vegetation indices (VI) were used to quantify cadmium (Cd) stress in five spinach genotypes that varied in uptake. Machine learning models were used to assess accuracy across the genotypes, with an artificial neural network (ANN) proving most effective at distinguishing genotypic and treatment differences. A partial least squares model (sPLS-DA) identified several VIs related to water content, anthocyanin levels, and plant senescence as most diagnostic in detecting Cd stress.The second experiment investigated relationships between MNPs, drought, and the soil and root microbiomes effects on lettuce stress. HSI successfully classified the stress treatments with over 80% accuracy while RGB imaging improved this accuracy to 85%. The soil and root microbiomes were more impacted by drought than MNPs, though the presence of the MNPs appeared to partially mitigate drought effects. Both stressors led to the recruitment of specific microbial taxa as well as microbes with potential functioning in amino acid degradation and methane production. These findings demonstrate HSI’s potential as a powerful tool in understanding how leafy green crops respond to soil contaminants. They also provide new scientific insights that will help plant breeders and microbiologists working to develop solutions to this rapidly growing problem.