Integration of RT-qPCR analysis and grey situation decision-making model for evaluating the effects of plant growth regulators on the gene expression in rice seedlings under thiocyanate exposure

Thiocyanate (SCN?) present in irrigation water can have negative effects on plant growth and crop yields. Addition of regulators (PGRs) alleviate toxic stress to plants. In the current study, we established a grey situation decision-making model (GSDM) integrate data RT-qPCR analysis for screening optimal addition PGRs minimise pollution stress. The (i.e., jasmonic acid [JA], indole-3-acetic [IAA] sodium hydrosulfide [NaHS]) abundance IAA oxidation conjugation-related genes rice seedlings under potassium thiocyanate (KSCN) exposure was examined. results obtained from roughly mitigating IAA, JA, NaHS KSCN Integration GSDM further quantified regulatory PGRs. Simulation showed that effect gene expression at is apparently better than JA IAA. Our study provides new simple, efficient, cheap approach identify environmental pollution.