Fen Zhang¹, Weili Tian¹, Lu Cen¹, Litang Lv², Xiaofang Zeng¹, Yulu Chen¹, Yichen Zhao^2,*, Yan Li^1,*

Phyton-International Journal of Experimental Botany, Vol.91, No.4, pp. 791-809, 2022, DOI:10.32604/phyton.2022.018104 - 09 December 2021

Abstract Duyun Maojian tea is a famous tea in China. In this study, the specific-locus amplified fragment (SLAF) sequencing method was used to analyze the population structure and conduct a genome-wide association study (GWAS) of 2 leaf traits of 123 tea plants in Qiannan, China. A total of 462,019 SLAF tags and 11,362,041 single-nucleotide polymorphism (SNP) loci were obtained. The results of phylogenetic tree analysis, cluster analysis, and principal component analysis showed that 123 tea germplasms were clustered into three groups, and the heterozygosity rates for Groups I, II, and II were 0.206, 0.224, and 0.34,… 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 - 03 November 2021

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… 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 - 11 October 2021

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… More >

Nazar Hussain¹, Muhammad Attique Khan¹, Usman Tariq², Seifedine Kadry^3,*, MuhammadAsfand E. Yar⁴, Almetwally M. Mostafa⁵, Abeer Ali Alnuaim⁶, Shafiq Ahmad⁷

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3281-3294, 2022, DOI:10.32604/cmc.2022.019036 - 27 September 2021

Abstract Agriculture is an important research area in the field of visual recognition by computers. Plant diseases affect the quality and yields of agriculture. Early-stage identification of crop disease decreases financial losses and positively impacts crop quality. The manual identification of crop diseases, which are mostly visible on leaves, is a very time-consuming and costly process. In this work, we propose a new framework for the recognition of cucumber leaf diseases. The proposed framework is based on deep learning and involves the fusion and selection of the best features. In the feature extraction phase, VGG (Visual… More >

Wei Yang, Yuke Lin, Yanbin Xue, Meiqin Mao, Xuzixing Zhou, Hao Hu, Jiawen Liu, Lijun Feng, Huiling Zhang, Jiaheng Luo, Jun Ma^*

Phyton-International Journal of Experimental Botany, Vol.91, No.2, pp. 333-348, 2022, DOI:10.32604/phyton.2022.016862 - 26 September 2021

Abstract Ananas comosus var. bracteatus is an important ornamental plant because of its green/white chimeric leaves. The accumulation of anthocyanin makes the leaf turn to red especially in the marginal part. However, the red fades away in summer and winter. Light intensity is one of the most important factors affecting leaf color along the seasons. In order to understand the effects of light intensity on the growth and coloration of the chimeric leaves, Ananas comosus var. bracteatus was grown under full sunlight, 50% shade and 75% shade for 75 days to evaluate the concentration of pigments, the color parameters… More >

Abdul Muiz Fayyaz¹, Kawther A. Al-Dhlan², Saeed Ur Rehman¹, Mudassar Raza¹, Waqar Mehmood³, Muhammad Shafiq⁴, Jin-Ghoo Choi^4,*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 507-522, 2022, DOI:10.32604/iasc.2022.016392 - 03 September 2021

Abstract Crops are very important to the financial needs of a country. Due to various diseases caused by different pathogens, a large number of crops have been destroyed. As humanoids, our basic need is food for survival, and the most basic foundation of our food is agriculture. For many developing countries, it is mainly an important source of income. Bacterial diseases are one of the main diseases that cause improper production and a major economic crisis for the country. Therefore, it is necessary to detect the disease early. However, it is not easy for humans to… More >

Yuanyuan Liu, Zhen Li, Lie Xu, Qiang Fu^*, Yongjian Wang

Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 115-128, 2022, DOI:10.32604/phyton.2022.015395 - 16 August 2021

Abstract A key scientific challenge relating to the threat of invasive plants on agriculture at the region level is to understand their adaptation and evolution in functional traits. Leaf functional traits, related to growth and resource utilization, might lead to adaptation of invasive plants to the geographical barriers (region or elevation). In the field experiment, we discussed the effects of region and elevation on leaf functional traits on invasive plant Erigeron annuus in farmland habitats in China. We compared leaf size, coefficient of variation (CV) of leaf traits, and fluctuating asymmetry (FA) of E. annuus from three regions… More >

Rabia Saleem¹, Jamal Hussain Shah^1,*, Muhammad Sharif¹, Ghulam Jillani Ansari²

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3581-3601, 2021, DOI:10.32604/cmc.2021.017700 - 24 August 2021

Abstract Due to the high demand for mango and being the king of all fruits, it is the need of the hour to curb its diseases to fetch high returns. Automatic leaf disease segmentation and identification are still a challenge due to variations in symptoms. Accurate segmentation of the disease is the key prerequisite for any computer-aided system to recognize the diseases, i.e., Anthracnose, apical-necrosis, etc., of a mango plant leaf. To solve this issue, we proposed a CNN based Fully-convolutional-network (FrCNnet) model for the segmentation of the diseased part of the mango leaf. The proposed… More >

Muhammad Rizwan Latif¹, Muhamamd Attique Khan¹, Muhammad Younus Javed¹, Haris Masood², Usman Tariq³, Yunyoung Nam^4,*, Seifedine Kadry⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2917-2932, 2021, DOI:10.32604/cmc.2021.017364 - 24 August 2021

Abstract Globally, Pakistan ranks 4 in cotton production, 6 as an importer of raw cotton, and 3 in cotton consumption. Nearly 10% of GDP and 55% of the country's foreign exchange earnings depend on cotton products. Approximately 1.5 million people in Pakistan are engaged in the cotton value chain. However, several diseases such as Mildew, Leaf Spot, and Soreshine affect cotton production. Manual diagnosis is not a good solution due to several factors such as high cost and unavailability of an expert. Therefore, it is essential to develop an automated technique that can accurately detect and recognize these… More >

K. K. Thyagharajan, I. Kiruba Raji^*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2061-2076, 2021, DOI:10.32604/cmc.2021.017591 - 21 July 2021

Abstract This paper proposes an approach to detecting diseases in neem leaf that uses a Fuzzy-Higher Order Biologically Inspired Neuron Model (F-HOBINM) and adaptive neuro classifier (ANFIS). India exports USD 0.28-million worth of neem leaf to the UK, USA, UAE, and Europe in the form of dried leaves and powder, both of which help reduce diabetes-related issues, cardiovascular problems, and eye disorders. Diagnosing neem leaf disease is difficult through visual interpretation, owing to similarity in their color and texture patterns. The most common diseases include bacterial blight, Colletotrichum and Alternaria leaf spot, blight, damping-off, powdery mildew,… More >