RESUMEN
This paper presents a dataset with 5513 images of individual soybean seeds, which encompass five categories: (â ) Intact, (â ¡) Immature, (â ¢) Skin-damaged, (â £) Spotted, and (â ¤) Broken. Furthermore, there are over 1000 images of soybean seeds in each category. Those images of individual soybeans were classified into five categories based on the Standard of Soybean Classification (GB1352-2009) [1]. The soybean images with the seeds in physical touch were captured by an industrial camera. Subsequently, individual soybean images (227×227 pixels) were divided from the soybean images (3072×2048 pixels) using an image-processing algorithm with a segmentation accuracy of over 98%. The dataset can serve to study the classification or quality assessment of soybean seeds.
RESUMEN
Pest management has been a great challenge since the beginning of human agricultural activities. Since the 1930s, chemical pesticide control has been a major control technology that can solve some of the pest problems in agricultural production. Still, it is harmful to food safety and the ecological environment. Meanwhile, the extensive use of chemical pesticides may lead to the rapid development of pest resistance. Because of the advantages of low cost, eco-friendly advantage, and low side effects, Solar Insecticidal Lamp (SIL) as the main physical control technology has been widely used for pest management in agricultural production in China. Owing to the phototaxis of pests, they have a phototropic rhythm during the nighttime. We can adjust the SIL insecticidal time according to the phototropic rhythm of pests. The purpose of this paper is to provide a comprehensive review of the pest phototactic rhythm in a selection of 24 pest species. It is the first comprehensive survey on the phototactic rhythm of pests and the time segments of this survey are accurate to the hour. The phototactic rhythm of pests are investigated in two different varieties of crops: 1) food crops and 2) economic crops. We also discuss and analyze the various factors (e.g., meteorological conditions, insecticidal devices, physiological states and others) that affect the changing phototactic rhythm of pests. Finally, we highlight some open research challenge issues and future directions.
RESUMEN
Due to the sparsity deployment of nodes, the full connection requirement, and the unpredictable electromagnetic interference on communication caused by high voltage pulse current of Solar Insecticidal Lamps Internet of Things (SIL-IoTs), a Two-Hop Energy Consumption Balanced routing algorithm (THECB) is proposed in this research work. THECB selects next-hop nodes according to 1-hop and 2-hop neighbors' information. In addition, the greedy forwarding mechanism is expressed in the form of probability; that is, each neighbor node is given a weight between 0 and 1 according to the distance. THECB reduces the data forwarding traffic of nodes whose discharge numbers are relatively higher than those of other nodes so that the unpredictable electromagnetic interference on communication can be weakened. We compare the energy consumption, energy consumption balance, and data forwarding traffic over various discharge numbers, network densities, and transmission radius. The results indicate that THECB achieves better performance than Two-Phase Geographic Greedy Forwarding plus (TPGFPlus), which ignores the requirement of the node-disjoint path.