Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
38,377
result(s) for
"AGRICULTURAL MACHINERY"
Sort by:
Planters
Sowing crops on a farm would be backbreaking working without the machines called planters. These tractor-pulled tools can look quite different. Some are small, sowing just one row, and some can plant as many as 48 rows at a time. Readers will find out how these machines work and see their parts in motion in labeled photographs. Theyll also discover how technology is changing this farm machine as well as some other seeding devices.
Book
Applications of Discrete Element Method in the Research of Agricultural Machinery: A Review
As a promising and convenient numerical calculation approach, the discrete element method (DEM) has been increasingly adopted in the research of agricultural machinery. DEM is capable of monitoring and recording the dynamic and mechanical behavior of agricultural materials in the operational process of agricultural machinery, from both a macro-perspective and micro-perspective; which has been a tremendous help for the design and optimization of agricultural machines and their components. This paper reviewed the application research status of DEM in two aspects: First is the DEM model establishment of common agricultural materials such as soil, crop seed, and straw, etc. The other is the simulation of typical operational processes of agricultural machines or their components, such as rotary tillage, subsoiling, soil compaction, furrow opening, seed and fertilizer metering, crop harvesting, and so on. Finally, we evaluate the development prospects of the application of research on the DEM in agricultural machinery, and look forward to promoting its application in the field of the optimization and design of agricultural machinery.
Journal Article
Inserting machines, displacing people: how automation imaginaries for agriculture promise ‘liberation’ from the industrialized farm
An emerging discourse about automated agricultural machinery imagines farms as places where farmers and workers do not
need
to be, but also implicitly frames farms as intolerable places where people do not
want
to be. Only autonomous machines, this story goes, can relieve farmers and workers of this presumed burden by letting them ‘farm at a distance’. In return for this distanced autonomy, farmers are promised increased control over their work-life balance and greater farm productivity from letting ‘smart’ robots assume control over the operational environment. Drawing upon the ways that these machines are promoted by manufacturers in various media, we trace the nascent contours of what we term a liberatory sociotechnical imaginary for agricultural automation across three cases—automated milking systems, self-driving tractors, and robotic strawberry pickers. We show how promises for new freedoms and autonomy are flexibly deployed to respond to distinct frictions that farmers, workers, and even farm animals experience in different modes of industrial agriculture. However, underlying these promises is the purposefully understated self-interest of manufacturers, who stand to gain further control over farms if automated technologies assume a central role in agriculture. Through the liberatory rhetoric, we contend, the imaginary seeks to enroll farmers into a socio-technical network that creates new relations of dependence upon the companies who design, sell, maintain, and often retain ownership over automated technologies. While potentially powerful, this imaginary may nonetheless fail to coalesce as farmers, workers, and agroecosystems exert their own agency on automated imaginaries and technological futures for agriculture.
Journal Article
Vehicles on the farm
An introduction to combines, harvesters, and other common farm vehicles and the important jobs they do.
Book
A Study on the Utilization Rate and Influencing Factors of Small Agricultural Machinery: Evidence from 10 Hilly and Mountainous Provinces in China
Hilly and mountainous areas are weak places for the development of agricultural mechanization in China. The way to improve the utilization rate of small agricultural machinery widely used in hilly and mountainous areas is of positive significance for optimizing resource allocation efficiency of agricultural production and ensuring food security supply. Taking microtillers as a representative tool, this study systematically analyzed the main factors affecting the utilization rate of small agricultural machines and its influencing mechanism. Then, based on the survey data of 4905 farmers in 100 counties in 10 hilly and mountainous provinces of China, empirical analysis was carried out by some econometric models, such as censored regression and the mediating effect model. Results show the following.: (1) Among farmers in hilly and mountainous areas, the average use time of each microtiller is 218.41 h per year. (2) Age, social identity, terrain conditions, crop types, land area, the number of microtillers, the number of large tractors, and the machinery purchase subsidy policy are the significant factors affecting the utilization rate of microtillers. (3) The increase of cultivated land area not only directly improves the utilization rate of microtillers, but also indirectly improves the utilization rate of microtillers due to the increase in quantity.
Journal Article
Planters
The seeds on a farm don't sow themselves, but luckily farmers have sophisticated machinery to help them transform a fertile field into a bountiful breadbasket. This book takes readers out to the fields to see planters at work.
Book
Farm size and pesticide use: evidence from agricultural production in China
PurposeChina is the world's largest consumer of pesticides. To increase the use efficiency and achieve more sustainable and environmentally friendly use of pesticides in China, it is crucial to understand why Chinese farmers use such a large amount of pesticides.Design/methodology/approachThe relationship between farm size and pesticide use was investigated by using national household-level panel data from 1995 to 2016.FindingFarms that are small and fragmented lead to the use of large amounts of pesticides in China. For a given crop type, three factors contribute to a negative relationship between farm size and pesticide use: the spillover effect from the use of pesticides by other farmers in the same village, the level of mechanization and the management ability of farmers. The first two factors play important roles in the cultivation of grain crops, while the last factor is the main reason why farmers with larger plots of land use fewer pesticides in the cultivation of vegetables. In addition, the effect of agricultural machinery services on reducing the use of pesticides is currently limited, and the service system in China is still insufficient, which has been pointed out that it is also due to the prevalence of small and fragmented farms.Originality/valueThe authors investigate and compare the farm size–pesticide use relationship in both grain and cash crop production. Moreover, the authors systematically explore and explain how farm size is related to a reduction in pesticide use in the cultivation of grain crops and cash crops. These results can help to better understand the role of land scale in pesticide use, lay a foundation for the formulation of policies to reduce pesticide use and provide valuable knowledge about pesticide use for other developing countries around the world.
Journal Article
Cultivators
Introduces young readers to the cultivators used on farms, discussing what they do, how they operate, and why their job is important.
Book
Visual Navigation and Obstacle Avoidance Control for Agricultural Robots via LiDAR and Camera
Obstacle avoidance control and navigation in unstructured agricultural environments are key to the safe operation of autonomous robots, especially for agricultural machinery, where cost and stability should be taken into account. In this paper, we designed a navigation and obstacle avoidance system for agricultural robots based on LiDAR and a vision camera. The improved clustering algorithm is used to quickly and accurately analyze the obstacle information collected by LiDAR in real time. Also, the convex hull algorithm is combined with the rotating calipers algorithm to obtain the maximum diameter of the convex polygon of the clustered data. Obstacle avoidance paths and course control methods are developed based on the danger zones of obstacles. Moreover, by performing color space analysis and feature analysis on the complex orchard environment images, the optimal H-component of HSV color space is selected to obtain the ideal vision-guided trajectory images based on mean filtering and corrosion treatment. Finally, the proposed algorithm is integrated into the Three-Wheeled Mobile Differential Robot (TWMDR) platform to carry out obstacle avoidance experiments, and the results show the effectiveness and robustness of the proposed algorithm. The research conclusion can achieve satisfactory results in precise obstacle avoidance and intelligent navigation control of agricultural robots.
Journal Article