An overview of remote monitoring methods in biodiversity conservation

Conservation of biodiversity is critical for the coexistence of humans and the sustenance of other living organisms within the ecosystem. Identification and prioritization of specific regions to be conserved are impossible without proper information about the sites. Advanced monitoring agencies like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) had accredited that the sum total of species that are now threatened with extinction is higher than ever before in the past and are progressing toward extinct at an alarming rate. Besides this, the conceptualized global responses to these crises are still inadequate and entail drastic changes. Therefore, more sophisticated monitoring and conservation techniques are required which can simultaneously cover a larger surface area within a stipulated time frame and gather a large pool of data. Hence, this study is an overview of remote monitoring methods in biodiversity conservation via a survey of evidence-based reviews and related studies, wherein the description of the application of some technology for biodiversity conservation and monitoring is highlighted. Finally, the paper also describes various transformative smart technologies like artificial intelligence (AI) and/or machine learning algorithms for enhanced working efficiency of currently available techniques that will aid remote monitoring methods in biodiversity conservation.

Genetic diversity and fingerprinting of 33 standard flue-cured tobacco varieties for use in distinctness, uniformity, and stability testing

BACKGROUND

At present, the distinctness, uniformity, and stability (DUS) testing of flue-cured tobacco (Nicotiana tabacum L.) depends on field morphological identification, which is problematic in that it is labor intensive, time-consuming, and susceptible to environmental impacts. In order to improve the efficiency and accuracy of tobacco DUS testing, the development of a molecular marker-based method for genetic diversity identification is urgently needed.

RESULTS

In total, 91 simple sequence repeats (SSR) markers with clear and polymorphic amplification bands were obtained with polymorphism information content, Nei index, and Shannon information index values of 0.3603, 0.4040, and 0.7228, respectively. Clustering analysis showed that the 33 study varieties, which are standard varieties for flue-cured tobacco DUS testing, could all be distinguished from one another. Further analysis showed that a minimum of 25 markers were required to identify the genetic diversity of these varieties. Following the principle of two markers per linkage group, 48 pairs of SSR markers were selected. Correlation analysis showed that the genetic relationships revealed by the 48 SSR markers were consistent with those found using the 91 SSR markers.

CONCLUSIONS

The genetic fingerprints of the 33 standard varieties of flue-cured tobacco were constructed using 48 SSR markers, and an SSR marker-based identification technique for new tobacco varieties was developed. This study provides a reliable technological approach for determining the novelty of new tobacco varieties and offers a solid technical basis for the accreditation and protection of new tobacco varieties.