Shunshun Ji, Jiajun Sun, Chao Zhang^*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4017-4029, 2024, DOI:10.32604/cmc.2024.055038

Abstract Asparagus stem blight, also known as “asparagus cancer”, is a serious plant disease with a regional distribution. The widespread occurrence of the disease has had a negative impact on the yield and quality of asparagus and has become one of the main problems threatening asparagus production. To improve the ability to accurately identify and localize phenotypic lesions of stem blight in asparagus and to enhance the accuracy of the test, a YOLOv8-CBAM detection algorithm for asparagus stem blight based on YOLOv8 was proposed. The algorithm aims to achieve rapid detection of phenotypic images of asparagus… More >

Taghreed Alsufyani^1,*, Noura J. Alotaibi², Nour Houda M’sakni¹, Mona A. Almalki¹, Eman M. Alghamdi³

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1523-1542, 2024, DOI:10.32604/phyton.2024.050351

Abstract This study simplifies the complex relationship among grapevine plants, aphids, ladybirds, and ants, which is essential for effective pest management and ecological balance. This study investigated the impact of aphid attacks and the presence of ants and ladybirds on the volatile compounds profile released into the chemosphere of the community consisting of the common vine Vitis vinifera, the aphid Aphis illinoisensis, the ladybird Coccinella undecimpunctata-and the ant Tapinoma magnum. This study aims to analyze the volatile compounds emitted by the grapevine and surrounding insects in response to these intricate interactions. The extraction of volatile organic compounds (VOCs) was carried… More >

Chengxu Qian¹, Qiangwen Chen^1,2, Leiyu Jiang¹, Xiaoyan Yang³, Shen Rao⁴, Weiwei Zhang¹, Feng Xu^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 951-962, 2024, DOI:10.32604/phyton.2024.050893

Abstract The objective of this study was to explain the physiological mechanisms through which NaSeO mitigates the growth and developmental inhibition of pakchoi under HgCl stress. The results showed that treatment with HgCl (40 mg L) led to reduced biomass, dwarfing, root shortening, and root tip necrosis in pakchoi. Compared to control (CK), the activities of superoxide dismutase (SOD) and peroxidase (POD) in Hg treatment increased, and the content of malondialdehyde (MDA) also dramatically increased, which negatively impacted the growth of pakchoi. Low concentrations of NaSeO (0.2 mg L) significantly increased the content of soluble sugars… More >

Xiaozhong Yu^1,2,*, Jinhua Zheng^1,2

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 197-225, 2024, DOI:10.32604/cmc.2023.043943

Abstract In rice production, the prevention and management of pests and diseases have always received special attention. Traditional methods require human experts, which is costly and time-consuming. Due to the complexity of the structure of rice diseases and pests, quickly and reliably recognizing and locating them is difficult. Recently, deep learning technology has been employed to detect and identify rice diseases and pests. This paper introduces common publicly available datasets; summarizes the applications on rice diseases and pests from the aspects of image recognition, object detection, image segmentation, attention mechanism, and few-shot learning methods according to More >

Arnoldo E. Alfaro-Corres¹, Daniel González-Mendoza², Esaú Ruiz-Sánchez^1,*, Carlos Ail-Catzin², Benjamín Valdez-Salas³, Federico Gutiérrez-Miceli⁴, Arturo Reyes-Ramírez¹, Jacques Fils Pierre¹

Journal of Renewable Materials, Vol.11, No.11, pp. 3933-3943, 2023, DOI:10.32604/jrm.2023.031129

Abstract This work was carried out to evaluate the insecticidal effect of mono, bi and trimetallic nanoparticles (NPs) from leaf extract of habanero pepper (Capsicum chinense Jacq.) on the red flour beetle (Tribolium castaneum herbst.) and cotton mealybug (Phenacoccus solenopsis Tinsley). The results showed that Cu NPs, Cu/Mn NPs and Zn/Cu NPs had high insecticidal effect against T. castaneum (63%–80% mortality after 96 h). The Cu NPs and Zn/Cu NPs showed also insecticidal effect against P. solenopsis, but to a lesser extent (20%–28% after 96 h). With regards to the physicochemical characterization, Cu NPs had a zeta potential of 21.1 More > Graphic Abstract

Liying Wang^*, Junzhi Liu, Chong Gao, Xinxin Yan

Journal of Renewable Materials, Vol.11, No.6, pp. 2679-2694, 2023, DOI:10.32604/jrm.2023.025569

Abstract Oil dispersible suspension concentrates are safe, green, and environmentally friendly formulations. Problems such as layering, pasting, and bottoming are frequently encountered during the production, storage, and transportation process. Polyisobutylene succinimide functions as a dispersant and exhibits great potential to improve the physical stability of the oil dispersible suspension concentrate. From a microscopic perspective, the sorption characteristics of the polyisobutylene succinimide dispersant T151 on penoxsulam particle surfaces were comprehensively evaluated with XPS, FTIR, and SEM. The T151 adsorption procedure complied with a pseudo-second-order kinetic adsorption model, and it was a kind of physical sorption with an… More > Graphic Abstract

Saud Yonbawi¹, Sultan Alahmari², T. Satyanarayana murthy³, Ravuri Daniel⁴, E. Laxmi Lydia⁵, Mohamad Khairi Ishak⁶, Hend Khalid Alkahtani^7,*, Ayman Aljarbouh⁸, Samih M. Mostafa⁹

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3847-3864, 2023, DOI:10.32604/csse.2023.036552

Abstract Crop insect detection becomes a tedious process for agronomists because a substantial part of the crops is damaged, and due to the pest attacks, the quality is degraded. They are the major reason behind crop quality degradation and diminished crop productivity. Hence, accurate pest detection is essential to guarantee safety and crop quality. Conventional identification of insects necessitates highly trained taxonomists to detect insects precisely based on morphological features. Lately, some progress has been made in agriculture by employing machine learning (ML) to classify and detect pests. This study introduces a Modified Metaheuristics with Transfer… More >

Muhammad Asad¹, Rashad Rasool Khan^2,*, Ahmed B. Aljuboory³, Muhammad Haroon U. Rashid⁴, Uttam Kumar⁵, Inzamam Ul Haq⁶, Aqsa Hafeez⁷, Ahmed Noureldeen⁸, Khadiga Alharbi^9,*

Phyton-International Journal of Experimental Botany, Vol.92, No.4, pp. 1161-1172, 2023, DOI:10.32604/phyton.2023.026513

Abstract The beet armyworm (BAW), Spodoptera exigua (Lepidoptera: Noctuidae) is a highly destructive pest of vegetables and field crops. Management of beet armyworm primarily relies on synthetic pesticides, which is threatening the beneficial community and environment. Most importantly, the BAW developed resistance to synthetic pesticides with making it difficult to manage. Therefore, alternative and environment-friendly pest management tactics are urgently required. The use of pesticidal plant extracts provides an effective way for a sustainable pest management program. To evaluate the use of pesticidal plant extracts against BAW, we selected six plant species (Lantana camara, Aloe vera, Azadirachta indica, Cymbopogon citratus, Nicotiana tabacum , and… More >

Lin Yuan¹, Qimeng Yu¹, Yao Zhang^2,*, Xiaochang Wang³, Ouguan Xu¹, Wenjing Li¹

Phyton-International Journal of Experimental Botany, Vol.92, No.3, pp. 747-761, 2023, DOI:10.32604/phyton.2023.025502

Abstract Thosea sinensis Walker (TSW) rapidly spreads and severely damages the tea plants. Therefore, finding a reliable operational method for identifying the TSW-damaged areas via remote sensing has been a focus of a research community. Such methods also enable us to calculate the precise application of pesticides and prevent the subsequent spread of the pests. In this work, based on the unmanned aerial vehicle (UAV) platform, five band images of multispectral red-edge camera were obtained and used for monitoring the TSW in tea plantations. By combining the minimum redundancy maximum relevance (mRMR) with the selected spectral features,… More >

R. S. Sandhya Devi^1,*, V. R. Vijay Kumar², P. Sivakumar³

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2249-2263, 2023, DOI:10.32604/csse.2023.032231

Abstract Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of research. To perform the investigation on Plant and pest classification, Transfer Learning (TL) approach is used on EfficientNet-V2. TL requires limited labelled data and shorter training time. However, the limitation of TL is the pre-trained model network’s topology is static and the knowledge acquired is detrimentally overwriting the old parameters. EfficientNet-V2 is a Convolutional Neural Network (CNN) model with significant high speed learning rates… More >