AMACA: Agricultural MAchine Cost Analysis app (original) (raw)

A Web-Based Information System for Agricultural Machinery Use Cost Analysis

2016

Agricultural machinery has the highest resources cost contribution in farm businesses. Moreover, in the last years high in power and size machines, new technologies, higher prices for spare parts, and energy consumption contributed to the rising of the machinery direct and indirect cost. The potential of having an estimation of such cost beforehand is a critical factor for strategic and tactical decision making. However, available web-based applications for agricultural machinery cost estimation are lacking of a mobile application module. The aim of this work is to present the development of an easy-to-se mobile app, to determine the actual machinery cost in different field operations and makes them available via web mobile application using a cross-platform approach. The web mobile app was built using HTML language for the content, JavaScript for the logic part, and CSS as a presentation style. To accelerate the development, the jQuery Mobile (JQM), a touch-optimized JavaScript lib...

A web mobile application for agricultural machinery cost analysis

Computers and Electronics in Agriculture, 2016

(AAM) is copyrighted and published by Elsevier. It is posted here by agreement between Elsevier and the University of Turin. Changes resulting from the publishing process-such as editing, corrections, structural formatting, and other quality control mechanisms-may not be reflected in this version of the text. The definitive version of the text was subsequently published in COMPUTERS AND ELECTRONICS

AMACA: Agricultural Machine Application Cost Analysis

2015

Today users want to be connected to useful information at any time and place. For this reason the use of mobile technology is growing rapidly, but despite the growth of usage of mobile technology, the agricultural sector is slower in its adoption when compared to other types of business. Machinery and equipments are major cost items in farm since many years in different countries. In the last years, moreover, high power machines, new technologies, higher prices for spare parts and energy contributed to the rising of the machines costs. There is not an unique rule to determine machine costs and the most accurate method of determining them is the complete records of the actual costs incurred: unfortunately this method is not usable for prompt forecast purposes. The possibility to know in advance such costs is strategic for the farmers, but the agricultural machine cost determination available by internet applications are lacking of a mobile app. Aim of this work is to fill this gap with an easy to use mobile app, to determine the real machineries costs in different field operations and makes them available via web mobile application using a cross-platform approach. A web mobile app called AMACA (Agricultural Machine App Cost Analysis), which allows the analysis of traction costs and operation costs, was studied and developed. This paper describes this app AMACA, created using the HTML language for the content, the JavaScript for the logic part and the CSS as a presentation style. To accelerate the development, the jQuery Mobile (JQM, a touch-optimized JavaScript library) was used. Discussion is made applying AMACA to a case studio and comparing it with the results produced by other on-line applications. The tool is readily available, and at no cost, without the need for any installation on the end users' devices.

Web and Hybrid Application Based Decision Support System for Farm Machinery Cost Estimation

AkiNik Publications, 2020

A web and hybrid application Decision Support System, namely Farm Machinery Decision Support System (FarMeD) for estimation of overall farm machinery costs was developed. The application can calculate the break-even units, custom hiring charges, net profit, and payback period in addition to the fixed and variable costs. The application is free with a user-friendly interface and can be accessed online from any computer or mobile phone with an internet connection. The application can also be deployed by using standalone packages for offline use on Windows-based PCs or as a standalone app on any Android device to work in the absence of internet connectivity. The user can make subsequent calculations by varying the various input parameters and compare the results to make decisions regarding whether to purchase a machine or to go for custom hiring and also to determine custom hiring rates in case he intends to offer his machine for custom hiring.

A Pocket Information System for Farm Contractors (APIS)

2017

Farm contractors have the necessity to quickly know if an agricultural operation request is convenient or not, using their agricultural machineries. Field dimension, shape and slope are key factors to determine operations costs. In addition, high machinery power and characteristics, spare parts, and energy consumption are main components difficult to quickly evaluate to understand the operation benefit or loss. The possibility to estimate such costs beforehand is a critical factor for strategic and tactical decision making. Nowadays there are few web-based mobile applications for agricultural machinery cost estimation to help farm contractors in their decision. Aim of this work is to present a quick and easy-to-use mobile web app, that allow the users to insert their machineries, the shape and the area of the field to evaluate the economic feasibility of a specific field operation. The app was built using the open-source Drupal framework with a module that use a cross-platform appro...

Crop-Machinery Management System For Farm Cost Analysis

International Journal of Scientific & Technology Research, 2013

Assessment of the total costs of agricultural farm is important to decide for selection of optimum combination of machinery, crops and farming system that can maximize profit. The decision on optimum combination of these factors by customary way is quite difficult due to their natural complexity. A computer system was develop in Excel-Visual basic software for farm management decision making, and to estimate machinery and the whole farm costs and net return from crops grown under different farming systems. The system deals with four crops and three farming systems by using tractor and six machines. The input data includes: crops type, operations, machine and inputs cost. The system was verified, validated, analyzed and its accuracy was approved. The system outputs change with various input parameters like farm size, machines used and crops combination. Application of the system showed that annual working hours, size and age of machines affect the fixed and total operation costs. The least operation cost was obtained by conventional farming system followed by zero tillage and heavy machinery system. Different crops varied in their costs when grown alone or in combinations in different farming systems. The lowest and highest net returns were obtained by growing sorghum alone with heavy machinery farming system and by growing the four crops in Zero-Tillage farming system. The system can be used as pre-season planning and management decision tool.

A web-based decision support system to select proper machinery size and tractor power

TURKISH JOURNAL OF AGRICULTURE AND FORESTRY, 2016

One of the most important key factors for efficient and profitable agricultural production is agricultural mechanization. Since agricultural mechanization system expenses are nearly 30% of an agricultural enterprise investment, the mechanization system should be planned very carefully. Since internet technologies have spread into all areas, including agriculture, a web-based decision support system (DSS) was developed to plan an agricultural machinery system to be used in Turkey's farm enterprises. The developed DSS was written in PHP and the databases were created using the MySQL database administration system. Several tables to select proper machine size and tractor power, including tractor test report data, technical data of the machines produced in Turkey, field work days for Turkey's climatic conditions, and typical working speed and efficiencies of the machines, were included in the databases. For the areas over 10 ha surveys were done for collecting data according to main production and machinery commonly used. Average daily working time data were also estimated. By conducting simulations using the developed DSS based on the survey data, for the machines that are used for producing the most common products in the Adana region, machinery fleets were created and tractor power sizes were selected. According to the results, for farms smaller than 40 ha, one tractor of less than 157 kW would be sufficient, and for the areas that are over 40 ha, two or three tractors would be sufficient to complete the agricultural activities in an effective amount of time.

Crop-machinery management system for field operations and farm machinery selection

Journal of Agricultural Biotechnology and Sustainable Development, 2013

The main objective of this study is to develop a computer system for farm management and selection of required farm machinery to perform field operations in time for crops grown in rotations. Excel and Visual basic software were used to develop the program. The input data included 4 crops (sorghum, sesame, sunflower and cotton), 3 field operations (seedbed preparation, seeding, and weeding operations) and 3 farming systems (zero-tillage, conventional, and heavy machines farming systems). In addition, tractor and 6 implements (wide level disk, disk harrow, chisel plow, row crop planter, interrow cultivator and sprayer) were also used. The system estimates the size and number of machine, power requirement and fuel consumption for the implements and operations. Verification showed that, the system has the ability to estimate the required parameters as soon as input data was entered. System validation indicated no significant differences between predicted results and actual data. The sensitivity analysis showed that, changing of input variables affects the output parameters and consequently selection is possible. The system was applied to estimate the required output variables in the mechanized rainfed agriculture in Gedarif, Sudan. It can be used for proper crop and machinery management as pre-season decision making with great confidence.

Mobile Appllication for Agricultural Crops

American Journal of Agricultural Science, Engineering and Technology, 2021

Farmers’ awareness on fast-moving developments in technologies affects the agriculture operations. Smartphones have been useful in agriculture for their mobility and accessibility. The mobile-based application for agricultural crops of Silang was designed to provide information about crops. Information includes health benefits of the fruits, uses of the crops, and how its different parts can be develop to another product. The application is the first step towards understanding the benefits of the byproducts of the crop in interactive way. The software development was anchored on agile model. The performance of the application was evaluated by 40 persons composed of subject matter experts including crops farmers and agriculturist, IT experts and potential users. The developed application was rated using Core App Quality Standard utilizing the criteria of Visual Design and User Interaction, Functionality, Compatibility, Performance and Stability, and Security. The app’s performance was adherent to the standard as verified by the app’s overall rating of excellent. The application will be able to help the crop farmer to get information in utilizing wastes into by-products, hence would be an opportunity to augment their income. It is recommended that the application may be added with crops available from other regions and consider a dynamic and cross-platform version of the app to maximize potential users.