Dina M. Ibrahim^1,2,*, Nada M. Elshennawy²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 331-348, 2022, DOI:10.32604/cmes.2022.016419 - 24 January 2022

Abstract Dates are an important part of human nutrition. Dates are high in essential nutrients and provide a number of health benefits. Date fruits are also known to protect against a number of diseases, including cancer and heart disease. Date fruits have several sizes, colors, tastes, and values. There are a lot of challenges facing the date producers. One of the most significant challenges is the classification and sorting of dates. But there is no public dataset for date fruits, which is a major limitation in order to improve the performance of convolutional neural networks (CNN)… More >

Labiba Gillani Fahad¹, Syed Fahad Tahir^2,*, Usama Rasheed¹, Hafsa Saqib¹, Mehdi Hassan², Hani Alquhayz³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5083-5098, 2022, DOI:10.32604/cmc.2022.023357 - 14 January 2022

Abstract The nutritional value of perishable food items, such as fruits and vegetables, depends on their freshness levels. The existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten only. We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories: pure-fresh, medium-fresh, and rotten. We gathered a dataset comprising of 60K images of 11 fruits and vegetables, each is further divided into three categories of freshness, using… More >

Broderick Crawford^1,*, Ricardo Soto¹, Hanns de la Fuente Mella¹, Claudio Elortegui¹, Wenceslao Palma¹, Claudio Torres-Rojas¹, Claudia Vasconcellos-Gaete², Marcelo Becerra¹, Javier Peña¹, Sanjay Misra³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4295-4318, 2022, DOI:10.32604/cmc.2022.023068 - 14 January 2022

Abstract Currently, the industry is experiencing an exponential increase in dealing with binary-based combinatorial problems. In this sense, metaheuristics have been a common trend in the field in order to design approaches to solve them successfully. Thus, a well-known strategy consists in the use of algorithms based on discrete swarms transformed to perform in binary environments. Following the No Free Lunch theorem, we are interested in testing the performance of the Fruit Fly Algorithm, this is a bio-inspired metaheuristic for deducing global optimization in continuous spaces, based on the foraging behavior of the fruit fly, which… More >

Harmandeep Singh Gill^1,*, Osamah Ibrahim Khalaf², Youseef Alotaibi³, Saleh Alghamdi⁴, Fawaz Alassery⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5135-5150, 2022, DOI:10.32604/cmc.2022.022809 - 14 January 2022

Abstract Fruit classification is found to be one of the rising fields in computer and machine vision. Many deep learning-based procedures worked out so far to classify images may have some ill-posed issues. The performance of the classification scheme depends on the range of captured images, the volume of features, types of characters, choice of features from extracted features, and type of classifiers used. This paper aims to propose a novel deep learning approach consisting of Convolution Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) application to classify the fruit images. Classification… More >

Harmandeep Singh Gill^1,*, Osamah Ibrahim Khalaf², Youseef Alotaibi³, Saleh Alghamdi⁴, Fawaz Alassery⁵

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 637-650, 2022, DOI:10.32604/iasc.2022.022589 - 05 January 2022

Abstract Contemporary vision and pattern recognition issues such as image, face, fingerprint identification, and recognition, DNA sequencing, often have a large number of properties and classes. To handle such types of complex problems, one type of feature descriptor is not enough. To overcome these issues, this paper proposed a multi-model recognition and classification strategy using multi-feature fusion approaches. One of the growing topics in computer and machine vision is fruit and vegetable identification and categorization. A fruit identification system may be employed to assist customers and purchasers in identifying the species and quality of fruit. Using More >

HUI-YING JIN^1,2, MAO-SONG PEI^1,2, DA-LONG GUO^1,2,*

BIOCELL, Vol.46, No.4, pp. 941-949, 2022, DOI:10.32604/biocell.2022.016718 - 15 December 2021

Abstract To understand the molecular characteristics of the miR477 gene family of grape (Vvi-miR477) and to predict its target genes, the Vvi-miR477 genes were identified from previous small RNA sequencing data, then phylogenetic analysis and prediction of target gene were conducted. The Vvi-miR477 family consists of two precursor sequences and three mature sequences. The miR477 family members were mostly 19-22nt in length. The sequence is relatively conservative. Vvi-MIR477a and Vvi-MIR477b are located on chromosomes 1 and 2, respectively. These precursor sequences can form the typical stable stem-loop structure. Their minimum folding free energy is −39.10 kcal/mol and −50.90 kcal/mol, More >

Abdul Majid¹, Muhammad Attique Khan¹, Majed Alhaisoni², Muhammad Asfand E. yar³, Usman Tariq⁴, Nazar Hussain¹, Yunyoung Nam^5,*, Seifedine Kadry⁶

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1387-1402, 2022, DOI:10.32604/cmc.2022.017701 - 03 November 2021

Abstract Agriculture has been an important research area in the field of image processing for the last five years. Diseases affect the quality and quantity of fruits, thereby disrupting the economy of a country. Many computerized techniques have been introduced for detecting and recognizing fruit diseases. However, some issues remain to be addressed, such as irrelevant features and the dimensionality of feature vectors, which increase the computational time of the system. Herein, we propose an integrated deep learning framework for classifying fruit diseases. We consider seven types of fruits, i.e., apple, cherry, blueberry, grapes, peach, citrus,… More >

Tarun Kumar Upadhyay^1,*, V. S. Varun Kumar², Amit Baran Sharangi³, Vijay J. Upadhye¹, Fahad Khan⁴, Pratibha Pandey⁴, Mohammad Amjad Kamal^5,6,7, Abrar Yasin Baba⁸ and Khalid Rehman Hakeem^9,*

Phyton-International Journal of Experimental Botany, Vol.91, No.3, pp. 471-487, 2022, DOI:10.32604/phyton.2022.017258 - 26 October 2021

Abstract Horticulture is a branch of Agricultural science where it is defined as the science and art of cultivating and handling fruits, vegetables, ornamental plants and several plants having unique medicinal and aromatic values. Horticultural crops provide farmers with high income and have good export quality, but they have a concern about postharvest losses. Hence, increasing productivity and decreasing post-harvest losses by using scientific studies and techniques like biotechnology and nanotechnology could be the simplest possible solution to the above-mentioned problems. Using nanotechnology which is having the characteristics of nanoparticles is proven to be very useful… More >

JIANFEI GAO¹, KANGNING XIONG^2,*, WEIJIE LI¹, WEI ZHOU³

BIOCELL, Vol.46, No.1, pp. 285-296, 2022, DOI:10.32604/biocell.2021.016253 - 29 September 2021

Abstract Kadsura coccinea (Lem.) is a woody wine plant with a peculiar fruit enriched in important health-promoting compounds. The non-editable part of the fruit, i.e., the seed and peel, represents more than 60% of the fruit and is considered a biowaste. This significantly restricts the development of the K. coccinea fruit industry. Clarifying the metabolic components of the different fruit parts can help to improve the utilization rate and valorization of K. coccinea. Herein, we evaluated K. coccinea fruit peel, pulp, and seed using widely-targeted metabolomics and quantified a set of 736 bioactive compounds from 11 major metabolite classes. The… More >

LINGJIAO FAN¹, DAN SONG¹, YINGWEI KHOO², MENGMENG WU¹, TENGFEI XU¹, XIAOLI ZHAO¹, HONGQING WANG¹

BIOCELL, Vol.46, No.1, pp. 263-273, 2022, DOI:10.32604/biocell.2022.016306 - 28 September 2021

Abstract

Strawberry mottle virus (SMoV) and strawberry vein banding virus (SVBV) cause diseases on strawberry plants, but the effect of coinfection of SMoV and SVBV on the growth, development, and defense system of strawberry (Fragaria × ananassa Duchesne) remains unknown. We investigated the effect of SMoV and SVBV co-infection on strawberry cultivar ‘Benihope’. The results showed that stem diameter, leaf size, leaf number, relative chlorophyll content, total chlorophyll content, photosynthetic parameters, and stomatal aperture of SMoV and SVBV co-infected strawberry (VIS) plants were in a weaker level than uninfected control plants, indicating that viruses inhibited the growth and

… More >