No correlative evidence of costs of infection or immunity on leucocyte telomere length in a wild population of Soay sheep.

Telomere length (TL) is a biomarker hypothesized to capture evolutionarily and ecologically important physiological costs of reproduction, infection and immunity. Few studies have estimated the relationships among infection status, immunity, TL and fitness in natural systems. The hypothesis that short telomeres predict reduced survival because they reflect costly consequences of infection and immune investment remains largely untested. Using longitudinal data from a free-living Soay sheep population, we tested whether leucocyte TL was predicted by infection with nematode parasites and antibody levels against those parasites. Helminth parasite burdens were positively associated with leucocyte TL in both lambs and adults, which is not consistent with TL reflecting infection costs. We found no association between TL and helminth-specific IgG levels in either young or old individuals which suggests TL does not reflect costs of an activated immune response or immunosenescence. Furthermore, we found no support for TL acting as a mediator of trade-offs between infection, immunity and subsequent survival in the wild. Our results suggest that while variation in TL could reflect short-term variation in resource investment or environmental conditions, it does not capture costs of infection and immunity, nor does it behave like a marker of an individual's helminth-specific antibody immune response.

Preliminary research on total nitrogen content prediction of sandalwood using the error-in-variable models based on digital image processing.

This paper presents a method for predicting the total nitrogen content in sandalwood using digital image processing. The goal of this study is to provide a real-time, efficient, and highly automated nutritional diagnosis system for producers by analyzing images obtained in forests. Using images acquired from field servers, which were installed in six forest farms of different cities located in northern Hainan Province, we propose a new segmentation algorithm and define a new indicator named "growth status" (GS), which includes two varieties: GSMER (the ratio of sandalwood pixels to the minimum enclosing rectangle pixels) and GSMCC (the ratio of sandalwood pixels to minimum circumscribed circle pixels). We used the error-in-variable model by considering the errors that exist in independent variables. After comparison and analysis, the obtained results show that (1) The b and L channels in the Lab color system have complementary advantages. By combining this system with the Otsu method, median filtering and a morphological operation, sandalwood can be separated from the background. (2) The fitting degree of the models improves after adding the GS indicator and shows that GSMCC performs better than GSMER. (3) After using the error-in-variable model to estimate the parameters, the accuracy and precision of the model improved compared to the results obtained using the least squares method. The optimal model for predicting the total nitrogen content is [Formula: see text]. This study demonstrates the use of Internet of Things technology in forestry and provides guidance for the nutritional diagnosis of the important sandalwood tree species.