Results 51 to 60 of about 3,575 (122)

Optimisation and Scale‐Up of the Heterologous Production of the Antifungal Protein PeAfpA From Penicillium expansum in Stirred‐Tank Bioreactors

Microbial Biotechnology, Volume 19, Issue 7, July 2026.
This work demonstrates the feasibility of scaling up laboratory processes to pilot scale production of antifungal proteins for diverse applications and exemplifies the possibilities that recyclable CRISPR/Cas9 methodology offers for fungal biotechnology.
Stefani de Ovalle, Sandra Garrigues, Jose V. Gimeno‐Alcañiz, Josep V. Mercader, Antonio Abad‐Fuentes, Jose F. Marcos, Paloma Manzanares   +6 more
wiley   +1 more source

Cucumber green mottle mosaic virus: A persistent seed‐borne threat to cucurbits

Annals of Applied Biology, Volume 189, Issue 1, July 2026.
Cucumber green mottle mosaic virus (CGMMV) is a highly stable, seed‐borne tobamovirus that threatens global cucurbit production. Its efficient mechanical and seed transmission, long‐term environmental persistence, and the spread of Clade II CGMMV isolates drive its rapid dissemination and cause severe yield losses.
Esperanza Gea‐Caballero, Miguel A. Aranda   +1 more
wiley   +1 more source

Do fawn‐footed mosaic‐tailed rats experience age‐related cognitive decline in novel object recognition?

Journal of Zoology, Volume 329, Issue 3, Page 247-256, July 2026.
We explored age‐related cognitive decline in captive fawn‐footed mosaic‐tailed rats (Melomys cervinipes) using a novel object recognition task. Contrary to expectations, recognition memory did not decline with age, but recognition memory was lower in intermediate‐aged rats compared to both older and younger individuals.
K. DiBenedetto, M. K. Rowell, T. L. Rymer   +2 more
wiley   +1 more source

Viruses in natural populations of wild hop in the south of Western Siberia

Acta Biologica Sibirica
Wild hops are abundant in the southern regions of Western Siberia, Russia, where the natural conditions are favorable for growing commercially valuable varieties.
Lyubov P. Khlebova, Elena S. Brovko, Olga V. Bychkova, Olga N. Mironenko, Anastasiya V. Nebylitsa   +4 more
doaj   +1 more source

AI-Enabled Intelligent System for Automatic Detection and Classification of Plant Diseases Towards Precision Agriculture

Informatics
Technology-driven agriculture, or precision agriculture (PA), is indispensable in the contemporary world due to its advantages and the availability of technological innovations.
Gujju Siva Krishna, Zameer Gulzar, Arpita Baronia, Jagirdar Srinivas, Padmavathy Paramanandam, Kasharaju Balakrishna   +5 more
doaj   +1 more source

Introduction pages, NBHA-CN 53(1), 2025

Notulae Botanicae Horti Agrobotanici Cluj-Napoca
The papers published in Notulae Botanicae Horti Agrobotanici Cluj-Napoca, Issue 1, Volume 53, 2025, represent new exciting research in different topics of life science, respectively in plant science, horticulture, agronomy, crop science, and forestry ...
Radu E. SESTRAS
doaj   +1 more source

Class Imbalance-Aware Deep Learning Approach for Apple Leaf Disease Recognition

AgriEngineering
Apple leaf disease identification with high precision is one of the main challenges in precision agriculture. The datasets usually have class imbalance problems and environmental changes, which negatively impact deep learning approaches.
Emrah Fidan, Serra Aksoy, Pinar Demircioglu, Ismail Bogrekci   +3 more
doaj   +1 more source

Api based automated plant disease analysis using transfer learning on pre-trained vision transformer model

Discover Artificial Intelligence
Plant disease significantly impacts the agricultural economy. It also affects the morphology and colour of leaves, which serve as key markers for diagnosis. Manual classification of disease requires trained professionals; it is tedious and time consuming.
Vijay R. N. Prabhakar, Pranav Misra, Sunita Bhatt, Richa Gupta, Satish Kumar Dubey   +4 more
doaj   +1 more source

Estimating the severity of apple mosaic disease with hyperspectral images

International Journal of Agricultural and Biological Engineering, 2019
Songtao Ban, Minglu Tian, Qingrui Chang
openaire   +1 more source

AgroDualNet: a dual deep learning-based crop disease forecasting and fruit ripening detection. [PDF]

Sci Rep
K M, C V, N K.
europepmc   +1 more source