Exploring plant diversity through soil DNA in Thai national parks for influencing land reform and agriculture planning

Environmental DNA as an emerging tool in botanical research

Over the past quarter century, environmental DNA (eDNA) has been ascendant as a tool to detect, measure, and monitor biodiversity (species and communities), as a means of elucidating biological interaction networks, and as a window into understanding past patterns of biodiversity. However, only recently has the potential of eDNA been realized in the botanical world. Here we synthesize the state of eDNA applications in botanical systems with emphases on aquatic, ancient, contemporary sediment, and airborne systems, and focusing on both single-species approaches and multispecies community metabarcoding. Further, we describe how abiotic and biotic factors, taxonomic resolution, primer choice, spatiotemporal scales, and relative abundance influence the utilization and interpretation of airborne eDNA results. Lastly, we explore several areas and opportunities for further development of eDNA tools for plants, advancing our knowledge and understanding of the efficacy, utility, and cost-effectiveness, and ultimately facilitating increased adoption of eDNA analyses in botanical systems.

A New Model for Scheduling Operations in Modern Agricultural Processes

In recent years, the increase in population and the decrease in agricultural lands and water shortages have caused many problems for agriculture and farmers. That is why scheduling is so important for farmers. Therefore, the implementation of an optimal schedule will lead to better use of agricultural land, reduce water consumption in agriculture, increase efficiency and quality of agricultural products. In this research, a scheduling problem for harvesting agricultural products has been investigated. In this problem, there are n number of agricultural lands that in each land m agricultural operations are performed by a number of machines that have different characteristics. This problem is modeled as a scheduling problem in a flexible workshop flow environment that aims to minimize the maximum completion time of agricultural land. The problem is solved by programming an integer linear number using Gams software. The results show that the proposed mathematical model is only capable of solving small and medium-sized problems, and due to the Hard-NP nature of the problem, large-scale software is not able to achieve the optimal solution.