Escherichia coli O157:H7 (E. coli O157:H7) is recognized as a hazardous microorganism in the environment and for public health. The E. coli O157:H7 survival dynamics were investigated in 12 representative soils from Jiangsu Province, where the largest E. coli O157:H7 infection in China occurred. It was observed that E. coli O157:H7 declined rapidly in acidic soils (pH, 4.57 – 5.14) but slowly in neutral soils (pH, 6.51 – 7.39). The survival dynamics were well described by the Weibull model, with the calculated td value (survival time of the culturable E. coli O157:H7 needed to reach the detection limit of 100 CFU g−1) from 4.57 days in an acidic soil (pH, 4.57) to 34.34 days in a neutral soil (pH, 6.77). Stepwise multiple regression analysis indicated that soil pH and soil organic carbon favored E. coli O157:H7 survival, while a high initial ratio of Gram-negative bacteria phospholipid fatty acids (PLFAs) to Gram-positive bacteria PLFAs, and high content of exchangeable potassium inhibited E. coli O157:H7 survival. Principal component analysis clearly showed that the survival profiles in soils with high pH were different from those with low pH.

Laboratory studies on Escherichia coli O157:H7 survival in soils from four different land use types: forest, tea plantation, bamboo grove, and vegetable garden were investigated at 25 ± 1 °C with the field capacity (soil water content at -33 kPa). Results showed that E. coli O157:H7 declined quickly in the test soils, but its survival dynamics varied in the soils under different land use types. The survival time needed to reach the detection limit (t d) in the test soils ranged from 2.1 to 3.6 days, with slightly longer t d values being observed in soils from the bamboo grove. Stepwise multiple regression analysis revealed that the t d values were shorter in sandy, lower pH, and lower organic carbon content soils. Different E. coli O157:H7 survival time in the soils under different land uses suggests that it is important to adapt proper management practices for reducing the potential risks of pathogen contamination when diary manure is applied to agricultural land.

Identification and classification of metal-accumulating plant species is essential for phytoextraction. Cluster analysis is used for classifying individuals based on measured characteristics. In this study, classification of plant species for metal accumulation was conducted using cluster analysis based on a practical survey. Forty plant samples belonging to 21 species were collected from an ancient silver-mining site. Five groups such as hyperaccumulator, potential hyperaccumulator, accumulator, potential accumulator, and normal accumulating plant were graded. For Cd accumulation, the ancient silver-mining ecotype of Sedum alfredii was treated as a Cd hyperaccumulator, and the others were normal Cd-accumulating plants. For Zn accumulation, S. alfredii was considered as a potential Zn hyperaccumulator, Conyza canadensis and Artemisia lavandulaefolia were Zn accumulators, and the others were normal Zn-accumulating plants. For Pb accumulation, S. alfredii and Elatostema lineolatum were potential Pb hyperaccumulators, Rubus hunanensis, Ajuga decumbens, and Erigeron annuus were Pb accumulators, C. canadensis and A. lavandulaefolia were potential Pb accumulators, and the others were normal Pb-accumulating plants. Plant species with the potential for phytoextraction were identified such as S. alfredii for Cd and Zn, C. canadensis and A. lavandulaefolia for Zn and Pb, and E. lineolatum, R. hunanensis, A. decumbens, and E. annuus for Pb. Cluster analysis is effective in the classification of plant species for metal accumulation and identification of potential species for phytoextraction.

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