Qi Lu^1,2, Longfei Jin², Cuiling Tong³, Feng Liu², Bei Huang², Dejian Zhang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 661-679, 2024, DOI:10.32604/phyton.2024.049733 - 29 April 2024

Abstract A Plant Biostimulant is any substance or microorganism applied to plants to enhance nutrition efficiency, abiotic stress tolerance, and/or crop quality traits, regardless of its nutrient content. The application of Plant biostimulants (PBs) in production can reduce the application of traditional pesticides and chemical fertilizers and improve the quality and yield of crops, which is conducive to the sustainable development of agriculture. An in-depth understanding of the mechanism and effect of various PBs is very important for how to apply PBs reasonably and effectively in the practice of crop production. This paper summarizes the main More >

Medhat A. Tawfeek^1,2, Nacim Yanes^3,4, Leila Jamel^5,*, Ghadah Aldehim⁵, Mahmood A. Mahmood^1,6

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2545-2564, 2023, DOI:10.32604/cmc.2023.042179 - 29 November 2023

Abstract The trend towards smart greenhouses stems from various factors, including a lack of agricultural land area owing to population concentration and housing construction on agricultural land, as well as water shortages. This study proposes building a full farming adaptation model that depends on current sensor readings and available datasets from different agricultural research centers. The proposed model uses a one-dimensional convolutional neural network (CNN) deep learning model to control the growth of strategic crops, including cucumber, pepper, tomato, and bean. The proposed model uses the Internet of Things (IoT) to collect data on agricultural operations… More >

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 - 03 April 2023

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 >

Sasa Jing¹, Yuan Tian¹, Heng Zhang², John T. Hancock³, Ying Zhu^2,*, Ping Li^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.4, pp. 1203-1214, 2023, DOI:10.32604/phyton.2023.026305 - 06 January 2023

Abstract The crop seeds have been a staple food for humans, and seed yield is important for sustaining agriculture development and enhancing human adaptability to food risks. The phenomenon of pre-harvest sprouting (PHS), caused by seed dormancy deficiency, and the phenomenon of low seedling emergence caused by seed deep dormancy, will lead to a reduction in agricultural production. Therefore, it is particularly important to understand the regulation mechanisms of seed dormancy. There are many studies on the regulation of seed dormancy in rice, but there are few studies on the regulation of seed dormancy in other More >

Shafaq Abbas¹, Muhammad Attique Khan¹, Majed Alhaisoni², Usman Tariq³, Ammar Armghan⁴, Fayadh Alenezi⁴, Arnab Majumdar⁵, Orawit Thinnukool^6,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1139-1159, 2023, DOI:10.32604/cmc.2023.028824 - 22 September 2022

Abstract Manual diagnosis of crops diseases is not an easy process; thus, a computerized method is widely used. From a couple of years, advancements in the domain of machine learning, such as deep learning, have shown substantial success. However, they still faced some challenges such as similarity in disease symptoms and irrelevant features extraction. In this article, we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases recognition. The proposed architecture consists of five steps. In the first step, data augmentation is performed to increase the numbers of training samples.… More >

P. Nithya^*, A. M. Kalpana

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3743-3755, 2023, DOI:10.32604/iasc.2023.030394 - 17 August 2022

Abstract Agriculture plays a vital role in economic development. The major problem faced by the farmers are the selection of suitable crops based on environmental conditions such as weather, soil nutrients, etc. The farmers were following ancestral patterns, which could sometimes lead to the wrong selection of crops. In this research work, the feature selection method is adopted to improve the performance of the classification. The most relevant features from the dataset are obtained using a Probabilistic Feature Selection (PFS) approach, and classification is done using a Neural Fuzzy Classifier (NFC). Scaling Conjugate Gradient (SCG) optimization More >

Shahid Hussain^*

Phyton-International Journal of Experimental Botany, Vol.91, No.12, pp. 2687-2697, 2022, DOI:10.32604/phyton.2022.021158 - 29 August 2022

Abstract Heavy metal(loid) accumulation in agricultural soils is a threat to the soil capacity, quality, and productivity. It also increases human exposure to heavy metal(loid)s via consumption of contaminated plant-based foods. The detrimental effects of soil contamination also deteriorate the environment of plants and animals. For sustainable agriculture, therefore, the soil must be protected from toxic levels of heavy metal(loid)s. Studies on heavy metal(loid) balances in agricultural soils are important in predicting future risks to sustainable production from agro-ecological zones and human exposure to heavy metal(loid)s. The latest and continuous indexing of the problem seems a 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 >

Na Kuang, Huabin Zheng, Qiyuan Tang^*, Yuanwei Chen, Xiaomin Wang, Youyi Luo

Phyton-International Journal of Experimental Botany, Vol.90, No.4, pp. 1119-1230, 2021, DOI:10.32604/phyton.2021.014637 - 27 April 2021

Abstract Rice ratooning, or the production of a second rice crop from stubble after the harvest of the main crop, is considered to be a green and resource-efficient rice production system. The present study was conducted to examine variance in amylose content (AC), grain morphology, crystal structure, and thermal properties of starch between main- and ratoon-season rice of seven varieties. Ratoon-season rice grains had higher ACs and significantly lower transition gelatinization temperatures (To, Tp, and Tc) than did main-season rice grains. The relative crystallinity and lamellar peak intensity of ratoon-season rice starch were 7.89% and 20.38% lower, respectively, More >

R. Ariza-Flores¹, D. Trujillo-García², M. A. Otero-Sánchez², E. Canales Sosa², C. H. Avendaño-Arrazate^3,*, L. A. Gálvez-Marroquín⁴, P. Cadena Iñiguez⁵

Phyton-International Journal of Experimental Botany, Vol.90, No.3, pp. 933-947, 2021, DOI:10.32604/phyton.2021.013227 - 30 March 2021

Abstract The aim of this study was to evaluate some physiological aspects of papaya crops in semi conventional and organic production systems. The following factors assessed in this experiment were: 1. Production systems (organic and semi conventional); 2. Genotypes (Maradol and Maradona F1), and 3. Cover crop plants (Canavalia, vegetative cover and no cover). Twelve treatments were obtained -product of factors’ combination- and distributed under a threerepetition experimental design of subdivided parcels. The factors examined in this study, that changed the CO₂ assimilation rate, were production system and genotype. It was determined that the greatest gas exchange More >