Samra Rehman¹, Muhammad Attique Khan¹, Majed Alhaisoni², Ammar Armghan³, Usman Tariq⁴, Fayadh Alenezi³, Ye Jin Kim⁵, Byoungchol Chang^6,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 697-714, 2023, DOI:10.32604/cmc.2023.035183

Abstract Identifying fruit disease manually is time-consuming, expert-required, and expensive; thus, a computer-based automated system is widely required. Fruit diseases affect not only the quality but also the quantity. As a result, it is possible to detect the disease early on and cure the fruits using computer-based techniques. However, computer-based methods face several challenges, including low contrast, a lack of dataset for training a model, and inappropriate feature extraction for final classification. In this paper, we proposed an automated framework for detecting apple fruit leaf diseases using CNN and a hybrid optimization algorithm. Data augmentation is performed initially to balance the… More >

Mazen Mushabab Alqahtani¹, Ashit Kumar Dutta², Sultan Almotairi³, M. Ilayaraja⁴, Amani Abdulrahman Albraikan⁵, Fahd N. Al-Wesabi^6,7,*, Mesfer Al Duhayyim⁸

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 217-233, 2023, DOI:10.32604/cmc.2023.025280

Abstract Recent developments in digital cameras and electronic gadgets coupled with Machine Learning (ML) and Deep Learning (DL)-based automated apple leaf disease detection models are commonly employed as reasonable alternatives to traditional visual inspection models. In this background, the current paper devises an Effective Sailfish Optimizer with EfficientNet-based Apple Leaf disease detection (ESFO-EALD) model. The goal of the proposed ESFO-EALD technique is to identify the occurrence of plant leaf diseases automatically. In this scenario, Median Filtering (MF) approach is utilized to boost the quality of apple plant leaf images. Moreover, SFO with Kapur's entropy-based segmentation technique is also utilized for the… More >

Mengyao Yan¹, Xianqi Zeng¹, Banghui Zhang¹, Hui Zhang², Di Tan¹, Binghua Cai¹, Shenchun Qu¹, Sanhong Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.1, pp. 193-208, 2023, DOI:10.32604/phyton.2022.023078

Abstract The effect of soil nutrient content on fruit yield and fruit quality is very important. To explore the effect of soil nutrients on apple quality we investigated 200 fruit samples from 40 orchards in Feng County, Jiangsu Province. Soil mineral elements and fruit quality were measured. The effect of soil nutrient content on fruit quality was analyzed by artificial neural network (ANN) model. The results showed that the prediction accuracy was highest (R²= 0.851, 0.847, 0.885, 0.678 and 0.746) in mass per fruit (MPF), hardness (HB), soluble solids concentrations (SSC), titratable acid concentration (TA) and solid-acid ratio (SSC/TA), respectively. The sensitivity… More >

Helong Yu, Xianhe Cheng, Ziqing Li, Qi Cai, Chunguang Bi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 711-738, 2022, DOI:10.32604/cmes.2022.020263

Abstract To solve the problem of difficulty in identifying apple diseases in the natural environment and the low application rate of deep learning recognition networks, a lightweight ResNet (LW-ResNet) model for apple disease recognition is proposed. Based on the deep residual network (ResNet18), the multi-scale feature extraction layer is constructed by group convolution to realize the compression model and improve the extraction ability of different sizes of lesion features. By improving the identity mapping structure to reduce information loss. By introducing the efficient channel attention module (ECANet) to suppress noise from a complex background. The experimental results show that the average… More >

Heru Suryanto^1,2,*, Bili Darnanto Susilo³, Jibril Maulana³, Aminnudin³, Uun Yanuhar⁴, Surjani Wonorahardjo^2,5, Husni Wahyu Wijaya^2,5, Abu Saad Ansari⁶

Journal of Renewable Materials, Vol.10, No.9, pp. 2455-2465, 2022, DOI:10.32604/jrm.2022.020478

Abstract Waste is the main problem for the environment. Handling waste for various useful applications has a benefit for the future. This work has been studied for handling pineapple peel waste to make composite film bacterial cellulose nanocomposite membrane (BCNM) with addition graphite nanoplatelet (GNP). The concentration of GNP in the membrane influence the membrane properties. The bacterial cellulose (BC) pellicle was synthesized by using media from pineapple peel waste extract. BC pellicle is cleaned with water and NaOH solution to be free from impactors. BCNM is synthesized through the mechanical disintegration stage. The results of disintegration using high pressure homogenizer… More > Graphic Abstract

Piyush Kumar Gupta¹, D. Karthik Kumar², M. Thaveena³, Soumya Pandit¹, Somya Sinha⁴, R. Ranjithkumar^2,* , Walaa F. Alsanie⁵, Vijay Kumar Thakur^6,7,8,*

Journal of Renewable Materials, Vol.10, No.12, pp. 3093-3105, 2022, DOI:10.32604/jrm.2022.019335

Abstract Custard apple is a dry land fruit. Its leaves exhibit different pharmacological activities. In the present study, both silver (Ag) nanoparticles and chitosan-coated Ag (Chi-Ag) nanoparticles were fabricated using the aqueous leaf extract of the custard apple plant. During preliminary phytochemical analysis, various types of phytocompounds were found in the aqueous leaf extract of the same plant. Next, both nanoparticles were physiochemically characterized. FTIR analysis exhibited the fingerprint vibrational peaks of active bioactive compounds in plant extract, Ag nanoparticles, and Chi-Ag nanoparticles. UV/Visible spectral analysis revealed the highest absorbance peak at 419 nm, indicating the presence of Ag nanoparticles. XRD… More > Graphic Abstract

MEIGE WANG, JUAN GONG, CHUNHUI SONG, ZHENGYANG WANG, SHANGWEI SONG, JIAN JIAO, MIAOMIAO WANG, XIANBO ZHANG^*, TUANHUI BAI^*

BIOCELL, Vol.46, No.7, pp. 1763-1770, 2022, DOI:10.32604/biocell.2022.018934

Abstract

Drought stress is one of the major environmental obstacles that limit the production and development of apples (Malus domestica Borkh.). The role of melatonin is well known in the protection of plants under environmental stresses. In this study, we investigated the effect of melatonin on apple rootstock M. hupehensis Rehd under drought stress. The results showed that drought inhibited the growth of M. hupehensis and dramatically reduced root surface area, root volume, the number of tips and forks, and root diameter. Drought-induced growth inhibition was significantly decreased by adding melatonin. Net photosynthetic rate (Pn), intercellular CO₂ concentration (Ci), stomatal conductance… More >

Álvaro Rodríguez-Peña¹, Ana C. Gonzalez-Franco¹, Jared Hernández-Huerta¹, Nora A. Salas-Salazar¹, Dámaris L. Ojeda-Barrios¹, Esteban Sánchez², Loreto Robles-Hernández^1,*

Phyton-International Journal of Experimental Botany, Vol.91, No.7, pp. 1341-1351, 2022, DOI:10.32604/phyton.2022.019728

Abstract Antibiotics are widely used in fire blight management programs, yet there are no studies that demonstrate the evaluation of their efficacy in Mexico. Therefore, the present study was conducted to investigate the effects of the active ingredients in five commercial products (Kasumin^® 2L, Agrygent Plus^®, Agricultural Terramycin^®, Agrimicin^® 100, and Actigard^®) on fire blight suppression, and fruit yield and quality of apple (Malus domestica Borkh.) cv. Golden Glory. The experiment was conducted in a commercial orchard using a completely randomized block design, with six treatments: (1) Oxytetracycline [Ox], 110 mg L⁻¹; (2) Kasugamycin [Kas], 4.7 mL L⁻¹; (3) Oxytetracycline + Gentamicin [Ox… More >

Swati Singh¹, Isha Gupta², Sheifali Gupta², Deepika Koundal^3,*, Sultan Aljahdali⁴, Shubham Mahajan⁵, Amit Kant Pandit⁵

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1849-1866, 2022, DOI:10.32604/cmc.2022.021875

Abstract In Agriculture Sciences, detection of diseases is one of the most challenging tasks. The mis-interpretations of plant diseases often lead to wrong pesticide selection, resulting in damage of crops. Hence, the automatic recognition of the diseases at earlier stages is important as well as economical for better quality and quantity of fruits. Computer aided detection (CAD) has proven as a supportive tool for disease detection and classification, thus allowing the identification of diseases and reducing the rate of degradation of fruit quality. In this research work, a model based on convolutional neural network with 19 convolutional layers has been proposed… More >

Fahd N. Al-Wesabi^1,2,*, Amani Abdulrahman Albraikan³, Anwer Mustafa Hilal⁴, Majdy M. Eltahir¹, Manar Ahmed Hamza⁴, Abu Sarwar Zamani⁴

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6223-6238, 2022, DOI:10.32604/cmc.2022.021299

Abstract Precision agriculture enables the recent technological advancements in farming sector to observe, measure, and analyze the requirements of individual fields and crops. The recent developments of computer vision and artificial intelligence (AI) techniques find a way for effective detection of plants, diseases, weeds, pests, etc. On the other hand, the detection of plant diseases, particularly apple leaf diseases using AI techniques can improve productivity and reduce crop loss. Besides, earlier and precise apple leaf disease detection can minimize the spread of the disease. Earlier works make use of traditional image processing techniques which cannot assure high detection rate on apple… More >