Artificial Breeding Techniques of Whitmania pigra

The artificial breeding technology for juvenile of Whitmania pigra was introduced in the paper,including selection of sites and water quality,construction of spawning pool,hatching pool and escape proof facilities,key technology of leech selection,feeding,cocoon hatching,juvenile feeding and management.

Artificial Breeding of Giant Pandas

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Nutritional and medicinal characteristics of Chinese giant salamander (Andrias davidianus) for applications in healthcare industry by artificial cultivation: A review

Andrias davidianus,i.e.Chinese giant salamander(CGS),is one of the largest and oldest amphibians existing in the world and is also one of the valuable biological resources of China.Wild CGS has been threatened with extinction in the past decades due to over capturing,deterioration of natural environment,the slow breeding and growth of the wild species in nature.However,in the past twenty years,with the breakthrough and progress of artificial breeding technology by artificial insemination,the number of artificially cultivated CGS has increased rapidly.Artificially cultivated CGS can either be released to the CGS living environment to increase the population in nature or legally applied in food and medicinal industry as a feedstock due to the unique nutritional and medicinal values of CGS as recorded historically.In this review,the nutritional components,bioactive components and medicinal activities of the artificially cultivated CGS will be summarized.The mucus,skin,meat and bone of CGS contain many different bioactive substances thereby having various medicinal activities including anti-aging,anti-fatigue,anti-tumor,therapy of burn and anti-infection and other physiological functions.This paper will further discuss the potential applications of the artificially cultivated CGS in healthcare industry and prospects of future technological development.

The Artificial Propagation and Fry Rearing of Lenok (Brachymystax lenok)

[ Objective] This paper aimed to summarize the results of the lenok reproduction in a hatchery, including growth of the artificially bred lenok, artificial propagation and fry rearing. [ Method ] Lenok （ Brachymystax lenok） collected at wild were fed with pelleted feed and cultured to ma- turity in a flowing -water pond. The broodstocks were hormonally induced to spawn, and fry were reared from 2003 to 2010 in order to obtain a suit- able and reliable method for the mass production of lenok juveniles. The embryos were hatched at accumulative temperature of up to 180 -213 day degree at water temperature of 8 -10 ~C. [Result]The results showed that 68% -85% of success rate was obtained with the eyed rate （fertilizing rate） of 32.8% -83%, hatching rate of 56.5% -87%, and emerging rate of 59.9% -90%. The fry developed into swim-up stage 10-12 days post - hatching. There were no significant differences in growth rate, fecundity and the eyed rate in the cultured lenok from those of the wild lenok. [ Conclusion] Mass fry production of lenok could be achieved by hormonally induction.

Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space

In large-scale deer farming image analysis,K-means or maximum between-class variance(Otsu)algorithms can be used to distinguish the deer from the background.However,in an actual breeding environment,the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer.Also,when the target and background grey values are similar,the multiple background targets cannot be completely separated.To better identify the posture and behaviour of deer in a deer shed,we used digital image processing to separate the deer from the background.To address the problems mentioned above,this paper proposes an adaptive threshold segmentation algorithm based on color space.First,the original image is pre-processed and optimized.On this basis,the data are enhanced and contrasted.Next,color space is used to extract the several backgrounds through various color channels,then the adaptive space segmentation of the extracted part of the color space is performed.Based on the segmentation effect of the traditional Otsu algorithm,we designed a comparative experiment that divided the four postures of turning,getting up,lying,and standing,and successfully separated multiple target deer from the background.Experimental results show that compared with K-means,Otsu and hue saturation value(HSV)+K-means,this method is better in performance and accuracy for adaptive segmentation of deer in artificial breeding scenes and can be used to separate artificially cultivated deer from their backgrounds.Both the subjective and objective aspects achieved good segmentation results.This article lays a foundation for the effective identification of abnormal behaviour in sika deer.