Jackson Silva Nóbrega^1,*, Geovani Soares de Lima¹, Jean Telvio Andrade Ferreira², Julio Cesar Agostinho da Silva¹, Lauriane Almeida dos Anjos Soares¹, Valéria Fernandes de Oliveira Sousa¹, Paulo Vinicius de Oliveira Freire¹, Reynaldo Teodoro de Fátima¹, Flávia de Sousa Almeida¹, Hans Raj Gheyi², Josemir Moura Maia³

Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1587-1600, 2025, DOI:10.32604/phyton.2025.063633 - 29 May 2025

Abstract The Northeast region is the main producer of guava in Brazil, generating employment and income. However, water availability means that producer’s resort to using water with high salinity, which harms plant development, especially during the seedling formation phase. The adoption of techniques that mitigate the deleterious effect of salinity is increasingly necessary, such as the use of elicitors such as ascorbic acid. The purpose of this study was to analyze the morphophysiology of guava seedlings under saline and ascorbic acid levels. The study was carried out by applying treatments composed of five saline levels (SL… More >

Javed Rashid^1,2, Imran Khan¹, Irshad Ahmed Abbasi³, Muhammad Rizwan Saeed⁴, Mubbashar Saddique^5,*, Mohamed Abbas^6,7

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3897-3920, 2023, DOI:10.32604/cmc.2023.040356 - 08 October 2023

Abstract Many plant species have a startling degree of morphological similarity, making it difficult to split and categorize them reliably. Unknown plant species can be challenging to classify and segment using deep learning. While using deep learning architectures has helped improve classification accuracy, the resulting models often need to be more flexible and require a large dataset to train. For the sake of taxonomy, this research proposes a hybrid method for categorizing guava, potato, and java plum leaves. Two new approaches are used to form the hybrid model suggested here. The guava, potato, and java plum More >

Javed Rashid^1,2, Imran Khan¹, Ghulam Ali³, Shafiq ur Rehman⁴, Fahad Alturise⁵, Tamim Alkhalifah^5,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1235-1257, 2023, DOI:10.32604/cmc.2023.032005 - 22 September 2022

Abstract The guava plant has achieved viable significance in subtropics and tropics owing to its flexibility to climatic environments, soil conditions and higher human consumption. It is cultivated in vast areas of Asian and Non-Asian countries, including Pakistan. The guava plant is vulnerable to diseases, specifically the leaves and fruit, which result in massive crop and profitability losses. The existing plant leaf disease detection techniques can detect only one disease from a leaf. However, a single leaf may contain symptoms of multiple diseases. This study has proposed a hybrid deep learning-based framework for the real-time detection… More >

Omar Almutiry¹, Muhammad Ayaz², Tariq Sadad³, Ikram Ullah Lali⁴, Awais Mahmood^1,*, Najam Ul Hassan⁵, Habib Dhahri¹

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1915-1926, 2021, DOI:10.32604/cmc.2021.017702 - 21 July 2021

Abstract Guava is one of the most important fruits in Pakistan, and is gradually boosting the economy of Pakistan. Guava production can be interrupted due to different diseases, such as anthracnose, algal spot, fruit fly, styler end rot and canker. These diseases are usually detected and identified by visual observation, thus automatic detection is required to assist formers. In this research, a new technique was created to detect guava plant diseases using image processing techniques and computer vision. An automated system is developed to support farmers to identify major diseases in guava. We collected healthy and… More >

Valera-Montero LL, PJ Muñoz-Rodríguez, H Silos-Espino, S Flores-Benítez

Phyton-International Journal of Experimental Botany, Vol.85, pp. 176-183, 2016, DOI:10.32604/phyton.2016.85.176

Abstract Guava fruit produced in Calvillo, Aguascalientes (Mexico) is considered to be of the best quality in this country. Nevertheless, growers from this place empirically know that there is a noticeable variation among individual trees within the same orchard, and variation among individuals from different orchards. In order to have a clear evidence of this, morphology analysis of guava was performed taking data from seventy nine individuals out of thirty six orchards, while RAPD was performed on a subset of twenty six individuals. Similarity was found for morphology data ranging from 87-100%, while similarity from RAPD More >