The penetration of digital technologies to enhance market participation by farmers, and intensify farmers' access to support services such as finance, farm inputs, and agricultural production information is on the rise in developing countries. However, the drivers and intensity of the adoption of these technologies by Ghanaian farmers have received little attention in policy and academic circles. This study analyzed the factors that drive the adoption and intensity of adoption of digital agricultural solutions by smallholder farmers in the Bono East Region of Ghana. The study used a survey questionnaire to collect data from 1199 randomly selected smallholder farmers in 2023. The multivariate probit model and the Heckpoisson regression model were used to analyze the drivers of different digital agricultural solutions and the intensity of adoption of these solutions, respectively. The results show that there is a joint demand for technologies that enhance access to extension services and those that accelerate access to inputs. Market-oriented solutions and agricultural extension solutions exhibited a complementary relationship. In addition to selected socio-demographic factors, the study found that membership in farmer-based organizations, access to credit, and participation in agronomic training increased farmers' propensity to adopt different digital agricultural solutions and increased the number of solutions adopted by farmers. Receiving visits from extension officers reduced the likelihood and intensity of adopting digital agricultural solutions. The results suggest that government and development partners should enhance access to credit and promote capacity development programmes among farmers. This will capacitate them to adopt digital agricultural solutions.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10731230PMC
http://dx.doi.org/10.1016/j.heliyon.2023.e23023DOI Listing

Publication Analysis

Top Keywords

digital agricultural
24
agricultural solutions
20
intensity adoption
16
smallholder farmers
12
solutions
9
drivers intensity
8
adoption digital
8
agricultural
8
technologies enhance
8
enhance access
8

Similar Publications

The prevalence, distribution, and diversity of Salmonella isolated from pork slaughtering processors and retail outlets in the Shandong Province of China.

Meat Sci

December 2024

Laboratory of Beef Processing and Quality Control, College of Food Science and Engineering, Shandong Agricultural University, Tai'an, Shandong 271018, PR China; National R&D Center for Beef Processing Technology, Tai'an, Shandong 271018, PR China; International Joint Research Lab (China and Greece) of Digital Transformation as an Enabler for Food Safety and Sustainability, Tai'an, Shandong 271018, PR China. Electronic address:

Salmonella is a foodborne pathogen of global significance and is highly prevalent in pork. This study investigated the prevalence, contamination distribution, virulence genes and antibiotic resistance of Salmonella in 3 pork processors in the Shandong Province of China. Samples were collected from 13 different sampling sources across the slaughter procedures (600 samples) as well as at retail outlets supplied by these processors (45 samples).

View Article and Find Full Text PDF

The Green Revolution in Pakistan introduced intensive agricultural practices aimed at enhancing food security and economic growth. However, these measures have degraded the country's fertile agricultural land and exacerbated climate pollution due to farmers' overexploitation of resources in pursuit of higher yields. Addressing this issue requires identifying factors that can influence farmers' behavior toward adopting sustainable practices.

View Article and Find Full Text PDF

Potato late blight leaf detection in complex environments.

Sci Rep

December 2024

Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650504, China.

Potato late blight is a common disease affecting crops worldwide. To help detect this disease in complex environments, an improved YOLOv5 algorithm is proposed. First, ShuffleNetV2 is used as the backbone network to reduce the number of parameters and computational load, making the model more lightweight.

View Article and Find Full Text PDF

Fine-grained restoration of Mongolian patterns based on a multi-stage deep learning network.

Sci Rep

December 2024

College of Computer and Information Engineering, Inner Mongolia Agricultural University, Huhhot, 010000, Inner Mongolia, China.

Mongolian patterns are easily damaged by various factors in the process of inheritance and preservation, and the traditional manual restoration methods are time-consuming, laborious, and costly. With the development of deep learning technology and the rapid growth of the image restoration field, the existing image restoration methods are mostly aimed at natural scene images. They do not apply to Mongolian patterns with complex line texture structures and high saturation-rich colors.

View Article and Find Full Text PDF

The early microbial colonization of the porcine gut is an important priming factor for gut and immune development. Nevertheless, little is known about the composition of microbes that translocate into the ileo-cecal lymph nodes (ICLN) in the neonatal phase. This study aimed to characterize age- and nutrition-related changes in the metabolically active bacterial and fungal composition of the ICLN in suckling and newly weaned piglets.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!