Showing posts with label agricultural technology. Show all posts
Showing posts with label agricultural technology. Show all posts

Wednesday, 4 August 2021

Technology Acceptance Model (TAM): A Framework for Predicting Farmers’ Adoption of Modern Rice Production and Postharvest Technologies | Chapter 9 | Cutting-edge Research in Agricultural Sciences Vol. 12

Using the Technology Acceptance Model, an empirical study was done among rice farmers to determine the factors that influence the adoption of current rice technologies (TAM). The link between the variables was investigated using Partial Least Squares Structural Equation Modeling (PLS-SEM). According to the results of the hypothesised model, the farmers' attitudes toward technology use are influenced only by perceived utility and relative advantage. Furthermore, the proposed model demonstrates that farmers' intentions in employing current rice technologies influence their decision to accept the technology.

Author (S) Details

Ryan Mark A. Ambong
Research, Development, and Extension Unit, Occidental Mindoro State College, Philippines.

View Book :- https://stm.bookpi.org/CRAS-V12/article/view/2370

Friday, 18 June 2021

Contributions of Lower Niger River Basin Development Authority in Transfer of Agrochemical Technologies to Rice Farmers in Kwara State, Nigeria | Chapter 8 | Cutting-edge Research in Agricultural Sciences Vol. 10

 The study looked into the Lower Niger River Basin Development Authority's role in transferring agrochemical technologies to rice farmers in Kwara State, Nigeria. This study determined the types of recommended agro-chemicals used in the study area, as well as the reasons why some respondents did not use recommended agro-chemicals. Data was collected using a structured interview schedule from 178 rice farmers who were chosen at random from a list of registered rice farmers with the Lower Niger River Basin Development Authority in Kwara state. The information was analyzed using Means, percentages, frequency counts, and Pearson Product Moment Correlation are examples of statistical tools. The recommended agrochemicals transferred to rice farmers were systemic (glyphosate, delsate, forceup), selective (2.4D amine and Orizo plus), non-systemic (paraquate, paraforce, Grammmzone), pre-emergence (Atrazine powder, Atrazine Liquid, Bentazone), fungicides (Blasticdine and Karate), and post-harvest (Blasticdine and Karate) (Lambacynolathin). Farmers avoided using agrochemicals due to a lack of availability, adaptation issues, the dangers associated with agrochemical use, and high prices. The weighted mean of the agricultural show was the highest. It received a weighted mean score (WMS) of 1.22 and was ranked first (1st) as a major source of information by LNRBDA. Under LNRBDA recommendations, the most commonly used agrochemicals among rice farmers were 2,4-D Amine and Orizo Plus. The provision of protective equipment was ranked first as the most important way in which LNRBDA contributed to the transfer of agrochemicals to rice farmers. As a result, the study recommended that the agency make an effort to raise awareness and provide information through LNRBDA activities in the media.

Author (S) Details

Oyetoro John Oyewole

Department of Agricultural Extension& Rural Development, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.

Mr. Salihu Abogude Aliyu
Lower Niger River Basin Development Authority, Ilorin, Kwara State, Nigeria.

View Book :- https://stm.bookpi.org/CRAS-V10/article/view/1565