Pattarapon Witthayakhun, Arthit Panyasak, Pakasinee Khaodang, Nittaya Thongtip, Rung Mulom,
Qiongxian Yan, Suntorn Wittayakun*
J. Sci. Agri. Technol. (2025) Vol. 6 (2): 40 – 50

DOI: https://doi.org/10.14456/jsat.2025.9

Abstract

The study was conducted to explore relationships and predictive models using quantitative information
based on populations of beef, dairy cattle, and farmers in upper northern Thailand from 2008 to 2023, aiming to
describe the strength and relationship of variables to create a basic predictive model that may benefit planning and
decision-making in entrepreneurship. Quantitative data were provided by the Information and Statistics Group,
Information and Communication Technology Center, Department of Livestock Development, Thailand, including
the numbers of beef and dairy cattle populations, and farmers who raised beef and dairy cattle. Data for beef cattle
were classified into four categories, while dairy cattle were classified into three. The results indicated highly
significant relationships between all beef categories and household farmers (p<0.01), and four effective predictive
models were generated. Simultaneously, significant relationships were found among all categories of dairy cattle
and household farmers (p<0.05), and three predictive models were initiated. In comparison, the population of the
beef herd was superior to the dairy herd (p<0.01) at a ratio of approximately 8.74:1. Likewise, the population of
beef farmers was greater than the dairy farmers (p<0.01) at a ratio of about 36.04:1. In conclusion, there is clear
statistical evidence that shows strengthen relationship between animal numbers and farmers that may able to be
simple tools for prediction related to agricultural production and entrepreneurship in upper northern Thailand.
Further research should be conducted to determine more criteria that may deal with simultaneous influence,
maximum likelihood estimation of parameters.

Keywords: Relationship, Predictive model, Beef, Dairy, Upper northern Thailand

Received: November 6, 2025.Revised: December 22, 2025. Accepted: December 29, 2025.

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