Farm management information system for fruit orchards

Fruticulture faces increasing market pressures that threaten its long-term viability. In the light of the real need to practically improve the environmental performance, to increase yield and to optimize product quality of fruticulture, the overall aim of this study was to develop a farm management information system (FMIS) for real time data recording, analysis and incorporating decision rules for specific field operations. The FMIS was composed of 3 major components: The system geodatabase, the web application and the Android application. Through Android application, spatial data storage in terms of field boundaries, tree positions and individual tree and area variables was possible, while access to the data and reports was available using the web interface

Financial and environmental performance of integrated precision farming systems

Smart farming technologies have a wide potential to improve agricultural performance, ranging from improved use of crop nutrients and plant protection products, increased crop quality and reduced overlaps to better production economy. In order to reduce the use of inputs and to diminish the adverse effects on the environment, more and more focus is put on site-specific application of fertilizers, pesticides and irrigation water. However, the costs of implementing these technologies are often quite high, compared to the benefits. Therefore, a comprehensive methodology approach that facilitates the understanding of investments, costs and benefits can provide an overview of the most feasible pathways for farmers to implement precision agriculture (PA) and may offer the chance to significantly enhance the level of adoption of the most suitable technologies. The objective of this study is to describe an overall integrated methodology approach to support cost-benefit analysis related to PA. A number of scenarios and their financial and environmental performance are presented either as single technologies or as a combination of different technologies. Key outputs of the analysis are net present value with selected environmental indicators such as change in fuel, pesticides and water use compared with conventional practices from other similar technologies. Findings from this study indicate that PA is mainly beneficial to large scale farms

Development of an Energy Efficient and Fully Autonomous Low-Cost IoT System for Irrigation Scheduling in Water-Scarce Areas Using Different Water Sources

Politicians and the general public are concerned about climate change, water scarcity, and the constant reduction in agricultural land. Water reserves are scarce in many regions in the world, negatively affecting agricultural productivity, which makes it a necessity to introduce sustainable water resource management. Nowadays, there is a number of commercial IoT systems for irrigation scheduling, helping farmers to manage and save water. However, these systems focus on using the available fresh water sources, without being able to manage alternative water sources. In this study, an Arduino-based low-cost IoT system for automated irrigation scheduling is developed and implemented, which can provide measurements of water parameters with high precision using low-cost sensors. The system used weather station data combined with the FAO56 model for computing the water requirements for various crops, and it was capable of handling and monitoring different water streams by supervising their quality and quantity. The developed IoT system was tested in several field trials, to evaluate its capabilities and functionalities, including the sensors’ accuracy, its autonomous controlling and operation, and its power consumption. The results of this study show that the system worked efficiently on the management and monitoring of different types of water sources (rainwater, groundwater, seawater, and wastewater) and on automating the irrigation scheduling. In addition, it was proved that the system is can be used for long periods of time without any power source, making it ideal for using it on annual crops. © 2022 by the authors

Management information system for spatial analysis of tractor- implement draft forces

With the recent increases in fuel costs, producers are searching for ways to minimize costs and to increase productivity. The ability to monitor and collect data about tractor/implement performance can benefit farm machinery management decisions and lead to fuel savings. The draft force required to pull an implement is of great importance, since it determines fuel consumption and the tractor power required. The aim of this study was to design and develop a Farm Management Information System (FMIS) to handle draft forces data and generate spatial performance maps. This analysis could be useful to analyze tillage operations in order to maintain soil quality and reduce energy consumption

Farm management information systems: Current situation and future perspectives

Farm Management Information Systems (FMIS) in agriculture have evolved from simple farm record-keeping into sophisticated and complex systems to support production management. The purpose of current FMIS is to meet the increased demands to reduce production costs, comply with agricultural standards, and maintain high product quality and safety. This paper presents current advancements in the functionality of academic and commercial FMIS. The study focuses on open-field crop production and centeres on farm managers as the primary users and decision makers. Core system architectures and application domains, adoption and profitability, and FMIS solutions for precision agriculture as the most information-intensive application area were analyzed. Our review of commercial solutions involved the analysis of 141 international software packages, categorized into 11 functions. Cluster analysis was used to group current commercial FMIS as well as examine possible avenues for further development. Academic FMIS involved more sophisticated systems covering compliance to standards applications, automated data capture as well as interoperability between different software packages. Conversely, commercial FMIS applications targeted everyday farm office tasks related to budgeting and finance, such as recordkeeping, machinery management, and documentation, with emerging trends showing new functions related to traceability, quality assurance and sales

Use of NDVI to predict yield variability in a commercial apple orchard

Apple orchards are a vital component of the economies of many countries worldwide. Producers are looking for ways to reduce production cost by reducing inputs. Apple yield prediction is one method which can help the farmers to manage the inputs more efficiently. A study was conducted in 2011 and 2012 in a commercial apple orchard in Greece in order to determine the relationship between normalized difference vegetation index (NDVI) measurements of the tree canopy with the apple yield. The results proved that there is correlation between NDVI measurements and yield in early June of each year (2011: r=0.81; 2012: r=0.52)

A Comparative Analysis Between Battery‐ and Solar‐Powered Wireless Sensors for Soil Water Monitoring

Wireless sensor networks (WSN) have found wide applications in many fields (such as agriculture) over last few years, and research interest is constantly increasing. However, power supply to the sensor nodes remains an issue to be resolved. Batteries are usually used to power the sensor nodes, but they have a limited lifetime, so solar energy harvesters are a good alternative solution. This study provides a comparative analysis between battery and solar energy harvesters for sensor nodes used for soil water monitoring. Experimental results show that small‐sized solar panels with low‐power energy harvester circuits and rechargeable batteries distinctly outperform secondary batteries in outdoor and continuous‐operation applications. The power level of the energy storage device of sensor node 1, which was powered by a small PV panel, remained constantly close to 90% for all days. The power of the other three nodes, which were powered by a rechargeable battery, was initially at 100% of the charge and gradually started to reduce. Sensor node 1 performed a total of 1288 activations during the experimental period, while sensor nodes 2 and 4 behaved satisfactorily and performed a total of 781 and 803 activations, respectively. In contrast, sensor node 3 did not exhibit the same behavior throughout the experiments. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Farm machinery management information system

Management of farming operations is currently rapidly changing toward a systems perspective integrating the surroundings in terms of environmental impact, public entities and documentation of quality and growing conditions. The latest developments in Information and Communication Technologies (ICT) and the prevailing lack of interoperability between agricultural tractors, implements and on-board computers has led to the development of ISO 11783 (ISOBUS) international standard for securing a more effective communication between these entities. Precision agriculture requires an increasing amount of information in order to be sufficiently managed and the abilities of the ISOBUS protocol is a significant step toward this goal as it will provide a wealth of automated data acquisition for improving the management of crop production. However, there is an urgent need to organize and specify the pathways of this large amount of information as prerequisites for subsequently turning it into knowledge and decision support. The aim of this study was to analyze and design a future farm machinery management information system to handle tractor and implement data together with the interactions with their surroundings. Soft systems methodology was used to analyze the human activities and to identify user requirements in relation to the use of farm machinery and the management of the information generated and pertaining to the tractor and the farm implements. The empirical data to extract this information was gathered from 30 targeted interviews with tractor operators and farm managers located in Greece and Denmark, and pertaining to questions about the optimal use of farm machinery data and tractor-implement performance. A rich picture of the whole system was developed and from that a conceptual model that infers to daily operations with the tractor, implement and the interactions with the surroundings. The conceptual models were developed for both conventional farm machinery and agricultural robots. The conceptual model function will serve as a blueprint for further development of required sensors, communication technology, and information processing capabilities. The developed conceptual models were tested and validated with 15 farm managers from the initial reviewing panel in order to reveal supplemental additions and concerns. (C) 2014 Elsevier B.V. All rights reserved

An underground experimental mobile platform for soil moisture monitoring

Abstract This paper presents an experimental underground pipeline mobile platform that can be used for monitoring soil moisture changes along or across an agricultural field in real time. A modified commercial soil moisture sensor was placed on two circular wheeled bases; each of them being driven by a small electric wheel motor. A single prototyping board allows the user to control the platform by sending commands (move one step forward or backwards) from a remote control. Experiments were carried out in laboratory conditions, on an artificial soil tank 10 m long, 1 m wide, and with a soil depth of 0.4 m. The plastic pipeline was placed horizontally 0.10 and 0.30 m under the soil surface. The results showed that the determination of soil moisture using the proposed method was much more effective than when measuring the soil moisture status at a particular point