Analysis of Management, Labor and Economics of Milking Systems in Intensive Goat Farms

Abstract

Dairy goat farms are growing in the world, but their technological level and, particularly, milking equipment are less developed than those of dairy cow farms. This study aims to evaluate milking parlors in the current situation in modern goat farms and suggest possible solutions or improvements. Ten goat farms located in various municipalities of the Friuli-Venezia Giulia region (Northeast Italy) adopting different milking systems (parallel milking parlors, milking carts, and milking buckets) were monitored. The mathematical model developed originally for the evaluation of milking parlors for dairy cows was modified and adapted to goat milking systems. Time for milking and final specific direct costs are the main parameters that enable evaluation and choice of suitable milking parlor; neglect or promotion of only one of the mentioned criteria may lead to an uneconomic investment or impaired operation of a farm. The research results showed that the modern milking systems, with a greater number of stalls and milking clusters, have a greater capacity and require less time for milking a goat than bucket and cart systems. The study also demonstrated that increasing the capacity of dairy goat farms enables a reduction of the final specific costs for milking.

Research on Navigation Path Extraction and Obstacle Avoidance Strategy for Pusher Robot in Dairy Farm

“…At this time, the coordinates of the target point are set to (8,8), the coordinates of the obstacle are set to (9,9), and the maximum action radius of the repulsive potential field of the obstacle is 1.5 m. The mobile robot reaches the target point smoothly according to the planned path. Figure 13 shows the simulation results when the obstacle is set between the starting point and the target point, and the resultant force is on the connection line between the two, in which the position coordinates of the obstacle in Figure 13a are (5,5); the position coordinates of the obstacles in Figure 13b Figure 12 shows the situation where the obstacle is located on the extension line between the robot and the target point, and the target point is within the repulsive potential field of the obstacle. At this time, the coordinates of the target point are set to (8,8), the coordinates of the obstacle are set to (9,9), and the maximum action radius of the repulsive potential field of the obstacle is 1.5 m. The mobile robot reaches the target point smoothly according to the planned path.…”

“…At this time, the coordinates of the target point are set to (8,8), the coordinates of the obstacle are set to (9,9), and the maximum action radius of the repulsive potential field of the obstacle is 1.5 m. The mobile robot reaches the target point smoothly according to the planned path. Figure 13 shows the simulation results when the obstacle is set between the starting point and the target point, and the resultant force is on the connection line between the two, in which the position coordinates of the obstacle in Figure 13a are (5,5); the position coordinates of the obstacles in Figure 13b Figure 13 shows the simulation results when the obstacle is set between the starting point and the target point, and the resultant force is on the connection line between the two, in which the position coordinates of the obstacle in Figure 13a are (5,5); the position coordinates of the obstacles in Figure 13b are (5,5), (4.5, 5.5), (4, 6), (3.5, 6.5), and (3,7). It can be seen that the robot can successfully get rid of the minimum point and avoid obstacles when it falls into a local minimum value during the movement process, and finally can move to the target point.…”

“…[3,4]. In the past few years, China's dairy industry has developed rapidly, and its output value and scale are at the forefront of the world [5]. According to the data released by the Ministry of Agriculture and Rural Affairs, China's milk production in 2020 was 35.3 million tons, an increase of 7% over 2015, on the other hand, the proportion of farming with more than 100 heads reached 67.2%, an increase of 18.9% compared with 2015.…”

“…Figure13shows the simulation results when the obstacle is set between the starting point and the target point, and the resultant force is on the connection line between the two, in which the position coordinates of the obstacle in Figure13aare(5,5); the position coordinates of the obstacles in Figure13bare (5, 5), (4.5, 5.5), (4, 6), (3.5, 6.5), and (3, 7). It can be seen that the robot can successfully get rid of the minimum point and avoid obstacles when it falls into a local minimum value during the movement process, and finally can move to the target point.…”