A psychrophilic extracellular protease was isolated from the marine bacterium Planococcus sp. M7 found in the deep-sea mud of the Southern Indian Ocean. The mature protease is about 43 kDa and contains 389 amino acids. Sequence alignment revealed that the protease whose catalytic triad was comprised of Ser224, Lys249, and Gln253 contains a catalytic module belonging to the serralysin-type protease family 41, and displays 46.55% identity with the experimentally verified serine protease from Bacillus subtilis str. 168. The enzyme displayed an alkaline mesophilic preference with an optimum pH of 10.0 and an optimum temperature of 35 °C. The enzyme retained its activity from 5 to 35 °C and was resistant to repeated freezing and thawing, but was completely inactivated at 55 °C. Calcium ions had a protective effect against thermal denaturation. More than 60% of the maximum activity was retained at pH values in the range of 5.0-11.0. Almost no activity loss was detected after 1 h of incubation at pH 8.0-10.0 and 20 °C, or with 1.0% SDS. Most important, this protease also showed good stability and compatibility with the standard enzyme-free detergent, which indicates its special interest for applications in detergent industry.
Body temperature measurement is a very important task in the sow breeding process. The authors used an infrared camera to detect the temperature of the body surface of the sows, relying on calculating the average of the infrared image temperature in the ear root region. Based on the grayscale value of the target image of the infrared image and the corresponding temperature value of 180 infrared images, a G‐T (Gray‐Temperature) model was established by linear least squares method, which achieved temperature inversion of each pixel of the target pig. For the different growth stages and different breeds of sows, the R‐square of the all established models is greater than 0.95. The average relative error of the model inversion of the body temperature was only 0.076977%. This means that the body temperature of the sows could be detected without relying on the software. Based on the G‐T model, the authors design a kind of sow's ear root recognition and body surface temperature detection algorithm for different sow population scenarios.
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