Yanjiao Zheng¹, Zaiqiang Yang^1,2,*, Tingting Wei¹, Heli Zhao¹

Phyton-International Journal of Experimental Botany, Vol.91, No.9, pp. 2033-2054, 2022, DOI:10.32604/phyton.2022.019468

Abstract The combined stress of high temperature and high relative air humidity is one of the most serious agrometeorological disasters that restricts the production capacity of protected agriculture. However, there is little information about the precise interaction between them on tomato fruit quality. The objectives of this study were to explore the effects of the combined stress of high temperature and relative humidity on the sugar and acid metabolism and fruit quality of tomato fruits, and to determine the best relative air humidity for fruit quality under high temperature environments. Four temperature treatments (32°C, 35°C, 38°C, 41°C), three relative air humidity… 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 >

Xiaolan Guo¹, Chenyan Liu¹, Muhammad Shakeel², Delu Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.91, No.6, pp. 1289-1302, 2022, DOI:10.32604/phyton.2022.019774

Abstract The root system plays an important role in the growth and development of blueberry. The aim of this study was to assess the impacts of different fertilizers on the root growth and root–yield relationship of blueberry to provide insight into the regulation of root growth and fruit yield by fertilizing from the perspective of the root system. Rabbiteye blueberry variety ‘Britewell’ as the test material, and six fertilizers, including BF, OR, CF, SF, HF, and RT were used in single-factor fertilization experiments to analyze the effects of different fertilizer treatments on the root morphology, root distribution, and fruit yield of… More >

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

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) models and avoid the overfitting… 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

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 hand-held cameras. The recognition and… 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

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 usually has much better sensory… 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

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 accuracy depends on the extracted… 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

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 Convolution Neural Network (CNN), Recurrent… 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

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, respectively. The… 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

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, and strawberry. The proposed method… More >