The changes in biomass (including yield), copper (Cu) concentration, and the accumulation of wheat (Triticum aestivum. L) in response to soil Cu pollution under nighttime warming had still not been explored. Hence, this study was carried out, and these variations were analyzed from a physiological perspective. Pot trials were performed at two levels of ambient temperatures (no-warming (NT) and average nighttime warming of 0.28 °C (WT)) and two levels of soil Cu concentrations (control check without Cu application (CK) and 100 mg/kg Cu application (Cu)). Soil was collected from the carbonate cinnamon soil region of central China. The warming effects of the passive nighttime warming system were prominent, and the average increment was 0.28 °C. Antioxidant enzyme activities were promoted by warming (p < 0.05) and Cu. The highest yield was achieved in NT-Cu, mainly attributed to relatively strong root activity and photosynthesis caused by supplemental Cu, but the Cu concentration in its grains was close to the threshold (10 mg/kg) for Cu concentration in foodstuff and could present a potential food safety risk. Though nighttime warming did not increase the total biomass and yield of wheat, it decreased the Cu accumulation of wheat grown in Cu-contaminated soil, especially in grains. Moreover, WT-CK and WT-Cu increased the Cu concentration in the roots and glumes and reduced the Cu concentration in grains by 13.09% and 55.84%, respectively, probably because of a lower transpiration rate. Among them, the Cu concentration of grains in WT-Cu was the lowest and significantly lower than other applications. Our findings reveal that nighttime warming has the potential to reduce the Cu risk of grains in wheat grown in the Cu-contaminated carbonate cinnamon soil region of central China and could then provide a theoretical reference for risk assessment of food quality for wheat subjected to dual stress from nighttime warming and Cu pollution.

Sweetpotato stem rot nematode (Ditylenchus destructor) causes the most devastating disease affecting sweetpotato production in China. The objectives of this study were to (i) establish a quantification method using real-time PCR for D. destructor of sweetpotato; (ii) analyze the effect of D. destructor density at harvest on the percentage of disease incidence in sweetpotatoes; and (iii) evaluate the effect of soil physical properties on disease incidence. Populations of D. destructor isolated from 28 different production areas in Henan Province exhibited identical sequences, and then real-time PCR-specific primers (PRNf and PRNr) were designed. The primer set demonstrated a 100% match with the sequences of D. destructor from three regions in China but did not align perfectly with different species within the genus Ditylenchus isolated from nine other countries. There were two and thirteen base mismatches with the closely related species D. africanus and D. gallaeformans, respectively. The log-transformed number of inoculated nematodes (x) to soil was highly correlated with the corresponding Ct value (y), resulting in the quantification curve (y = −1.0859x + 32.025, R² = 0.9866, P < 0.01). This quantification curve was utilized to evaluate the densities of D. destructor in wheat fields that were not cultivated with sweetpotato and in fields under continuous sweetpotato cultivation. The results showed no detection in the wheat fields, and the densities ranged from 0 to 13,300 ± 1,020 individuals per 20 g of dry soil. At harvest, the D. destructor density established a negative correlation with soil pH (y = −1.7431x + 12.568, R² = 0.6028, P < 0.05). When soil pH values were between 5.6 and 6.8, and the density of D. destructor at harvest was less than 160 ± 30 per 20 g of soil, the percentage of disease incidence at harvest was 0. A significant correlation was established between D. destructor density and the severity of sweetpotato disease. The results indicate that the specific primer set developed in this study allows for the accurate and rapid quantification of D. destructor density in the soil, as well as the prediction of disease incidence in sweetpotato.