Capsicum frutescens, one of the domesticated species of pepper grown worldwide, is thought to be highly advantageous due to its strong resistance against plant pathogenesis, high productivity, and intense aroma. However, a shortage of molecular markers limits the efficiency and accuracy of genetic breeding for pepper. With the newly developed next-generation sequencing technology, genome sequences of C. frutescens can be generated, which are now available for identifying SSR markers via data mining. In this study, a total of 278,425 SSRs were detected from the pepper genome using MISA software. It was observed that trinucleotides were the dominant repeat motif. This was followed by dinucleotides, tetranucleotides, pentanucleotides, and the hexanucleotides repeat types. (AT)n (TTG)n (AAAT)n (AAATA)n (TATAGA)n is known to be the most common repeat motifs corresponding to dinucleotide to hexanucleotide repeats, respectively. In addition, a total of 240 SSR primers evenly distributed over all 12 chromosomes were designed and screened against 8 C. frutescens cultivars. Of these, 33 SSR markers that have high polymorphism, have been scrutinized for 147 accessions from 25 countries. The dendrogram constructed clustered these accessions into seven major groups. The groups were found to be consistent with their origins. The results obtained in this study provided resources of SSR molecular markers and insight into genetic diversity of the C. frutescens.

The purpose of this paper is to explore a discrete-time cash flow optimization problem of the insurance company with time value of ruin under different interest rates. For the sake of considering the time value of ruin, we assume that the shareholders can get subsidies per unit time, as long as the insurance company is not bankrupt. The switching of different interest rates on the market is controlled by a stationary Markov chain. The dynamic programming principle is used to solve this optimization problem. By using the method of fixed-point theory, we show that the value function is the unique solution of the dynamic programming equation and a numerical algorithm is proposed to solve the value function as well as the optimal policy. Furthermore, two examples are revealed to illustrate the application of the main results obtained in the presented paper.

Pepper, as a vegetable crop with a wide cultivation area worldwide, besides being a significant condiment and food, also has a momentous use for chemistry, medicine, and other industries. Pepper fruits are rich in various pigments, such as chlorophyll, carotenoids, anthocyanins, and capsanthin, which have important healthcare and economic value. Since various pigments are continuously metabolized during the development of pepper fruits, peppers exhibit an abundant fruit-colored phenotype in both the mature and immature periods. In recent years, great progress has been made in the study of pepper fruit color development, but the developmental mechanisms are still unclear systematically dissected in terms of pigment, biosynthesis, and regulatory genes. The article outlines the biosynthetic pathways of three important pigments: chlorophyll, anthocyanin, and carotenoid in pepper and the various enzymes involved in these pathways. The genetics and molecular regulation mechanisms of different fruit colors in immature and mature peppers were also systematically described. The objective of this review is to provide insights into the molecular mechanisms of pigments biosynthesis in pepper. This information will provide theoretical basis for the breeding of high-quality colored pepper varieties in the future.

Pepper is widely grown all over the world, so it faces many abiotic stresses, such as drought, high temperature, low temperature, salt damage, and so on. Stresses causing the accumulation of reactive oxidative species (ROS) in plants are removed by antioxidant defense systems, and ascorbate peroxidase (APX) is an important antioxidant enzyme. Therefore, the present study performed genome-wide identification of the APX gene family in pepper. We identified nine members of the APX gene family in the pepper genome according to the APX proteins’ conserved domain in Arabidopsis thaliana. The physicochemical property analysis showed that CaAPX3 had the longest protein sequence and the largest molecular weight of all genes, while CaAPX9 had the shortest protein sequence and the smallest MW. The gene structure analysis showed that CaAPXs were composed of seven to 10 introns. The CaAPX genes were divided into four groups. The APX genes of groups I and IV were localized in the peroxisomes and chloroplasts, respectively; the group II genes were localized in the chloroplasts and mitochondria; and the group III genes were located in the cytoplasm and extracell. The conservative motif analysis showed that all APX genes in the pepper had motif 2, motif 3, and motif 5. The APX gene family members were distributed on five chromosomes (Chr. 2, 4, 6, 8, and 9). The cis-acting element analysis showed that most CaAPX genes contain a variety of cis-elements related to plant hormones and abiotic stress. RNA-seq expression analysis showed that the expression patterns of nine APXs were different in vegetative and reproductive organs at different growth and development stages. In addition, the qRT-PCR analysis of the CaAPX genes revealed significant differential expression in response to high temperature, low temperature, and salinity stresses in leaf tissue. In conclusion, our study identified the APX gene family members in the pepper and predicted the functions of this gene family, which would provide resources for further functional characterization of CaAPX genes.

In this paper, we solve an optimal reinsurance problem in the mathematical finance area. We assume that the surplus process of the insurance company follows a controlled diffusion process and the constant interest rate is involved in the financial model. During the whole optimization period, the company has a choice to buy reinsurance contract and decide the reinsurance retention level. Meanwhile, the bankruptcy at the terminal time is not allowed. The aim of the optimization problem is to minimize the distance between the terminal wealth and a given goal by controlling the reinsurance proportion. Using the stochastic control theory, we derive the Hamilton-Jacobi-Bellman equation for the optimization problem. Via adopting the technique of changing variable as well as the dual transformation, an explicit solution of the value function and the optimal policy are shown. Finally, several numerical examples are shown, from which we find several main factors that affect the optimal reinsurance policy.