Computers and Electronics in Agriculture (COMPUT ELECTRON AGR)

Publisher: Elsevier

Journal description

Computers and Electronics in Agriculture provides international coverage of advances in the application of computer hardware, software and electronic instrumentation and control systems to agriculture, forestry and related industries. The latter include horticulture (in both its food and amenity aspects), forest products, aquaculture, animal/livestock science, veterinary medicine and food processing.The journal publishes original papers, reviews, applications notes and book reviews on topics including computerized decision-support aids (e.g., expert systems and simulation models) pertaining to any aspect of the aforementioned industries; electronic monitoring or control of any aspect of livestock/crop production (e.g. soil and water, environment, growth, health, waste products) and post-harvest operations (such as drying, storage, production assessment, trimming and dissection of plant and animal material). Relevant areas of technology include artificial intelligence, sensors, machine vision, robotics and simulation modelling.

Current impact factor: 1.76

Impact Factor Rankings

2016 Impact Factor Available summer 2017
2014 / 2015 Impact Factor 1.761
2013 Impact Factor 1.486
2012 Impact Factor 1.766
2011 Impact Factor 1.846
2010 Impact Factor 1.431
2009 Impact Factor 1.312
2008 Impact Factor 1.273
2007 Impact Factor 1.242
2006 Impact Factor 0.851
2005 Impact Factor 0.802
2004 Impact Factor 0.863
2003 Impact Factor 0.686
2002 Impact Factor 0.556
2001 Impact Factor 0.626
2000 Impact Factor 0.379
1999 Impact Factor 0.358
1998 Impact Factor 0.347
1997 Impact Factor 0.466

Impact factor over time

Impact factor

Additional details

5-year impact 2.09
Cited half-life 6.00
Immediacy index 0.31
Eigenfactor 0.01
Article influence 0.52
Website Computers and Electronics in Agriculture website
Other titles Computers and electronics in agriculture (Online)
ISSN 0168-1699
OCLC 38840899
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details


  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Authors pre-print on any website, including arXiv and RePEC
    • Author's post-print on author's personal website immediately
    • Author's post-print on open access repository after an embargo period of between 12 months and 48 months
    • Permitted deposit due to Funding Body, Institutional and Governmental policy or mandate, may be required to comply with embargo periods of 12 months to 48 months
    • Author's post-print may be used to update arXiv and RepEC
    • Publisher's version/PDF cannot be used
    • Must link to publisher version with DOI
    • Author's post-print must be released with a Creative Commons Attribution Non-Commercial No Derivatives License
    • Publisher last reviewed on 03/06/2015
  • Classification

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this study, a mobile, field-based, high-throughput phenotyping platform was developed for rapid measurement of plant characteristics. The platform consisted of three sets of sensors mounted on a high-clearance vehicle. Each set contained two infrared thermometers (IRT), one ultrasonic sensor, one Crop Circle multi-spectral crop canopy sensor, and one GreenSeeker crop sensing system. Each sensor set measured canopy temperature, crop height, and canopy spectral reflectance of a plant plot. Thus, three plots were measured simultaneously in a single pass. In addition to the sensors, the platform was equipped with a laser distance sensor to measure the height of the sensor beam and an RTK-GPS system that provided precise, accurate position data for georeferencing sensor measurements. Software for collecting, georeferencing, and logging sensor data was developed using National Instruments LabVIEW on a laptop computer. The hardware and software design was modular, allowing easy addition and removal of sensors and flexible system expansion. The fast sampling rates for sensors allowed the phenotyper to operate in field at a ground speed of 3.2 km/h. Two verification tests were conducted to evaluate the phenotyping system. In the first test, data timestamps were analyzed to determine if the system could collect data at the required rates and if the time delays would cause significant position errors. Test results showed that data from all sensors were received within the desirable time frame and the largest position error was 17.9 cm when the phenotyper was moving at a speed of 3.2 km/h. The position errors can be corrected during data post processing. The second test determined whether changes in ambient light and ambient temperature had statistically significant effects on the accuracy of the sensor measurements. For the IRT sensors, a correction method using ground truth temperature measurement made during two periods within a day was recommended to correct the errors in surface temperature measured by the IRTs.
    No preview · Article · Mar 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: Large area bold type spraying of chemical herbicide is not only a waste of herbicides and labor, but also leads to environmental pollution and food quality problems. Traditional methods have the problems of high light and sample quality etc requirements. Therefore, accurately identifying weeds and precisely spraying are important strategies for promoting agricultural sustainable development. To avoid the influence of different illumination on images, this paper adopts the color model and then proposes component to gray images; the vertical projection method and the linear scanning method are combined to quickly identify the center line of the crop rows; the classic Weeds Infestation Rate (WIR) is modified to decrease the computational complexity and the improved horizontal scanning method is taken to calculate within cells; finally, Modified Weeds Infestation Rate (MWIR) is used to realize real-time decision through the minimum error ratio of Bayesian decision under normal distribution. The experimental results show that the accuracy of this algorithm is 92.5%, which exceeds the BP algorithm and SVM algorithm.
    No preview · Article · Mar 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: Predictions of the Chinese solar greenhouse temperatures are important because they play a vital role in greenhouse cultivation, with solar greenhouse crops susceptible to potential losses because of cold and hot temperatures. Therefore, it is important to set up a precise predictive model of temperature that can predict the occurrence of temperatures several hours before head to reduce financial losses. This paper presents a novel temperature prediction model based on a least squares support vector machine (LSSVM) model with parameters optimized by improved particle swarm optimization (IPSO). The IPSO with probability of mutation was employed to optimize the required hyper parameters of the LSSVM model. The performance of the IPSO–LSSVM model was compared with traditional modeling approaches by applying it to predict solar greenhouse temperatures, and the results showed that its predictions of the maximum and minimum temperature were more accurate than those of the standard support vector machine (SVM) and Back propagation neural network (BPNN). Therefore, it is a suitable and effective method for predicting the Chinese solar greenhouse temperatures.
    No preview · Article · Mar 2016 · Computers and Electronics in Agriculture

  • No preview · Article · Mar 2016 · Computers and Electronics in Agriculture

  • No preview · Article · Mar 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: Today, there is no integrated land administration system within cadastre and land registry for land use and management of tea agricultural croplands. So, it is needed to a comprehensive development agenda for enabling land management driven land use policy reforms integrated geo-spatial data with cadastre through parcel-based registration and recording system on tea agricultural croplands. A wide range of uses of spatial data and geo-information in these reforms brings real ability to enable achieving global initiatives on sustainable and interoperable tea agricultural systems. To support sustainable tea agriculture for current and future agricultural trends, an application-oriented modeling for monitoring, mapping and registration system is needed to shape and management of tea agricultural croplands and cropping facilities. Having said this firstly registration and recording of recognized property rights are crucial especially for land certification process. So improved property rights (rights, restrictions and responsibilities (RRR)) on certificated croplands are the basis for the building of management system. This system is coming to the fore also to make sound creating standards at global level in the well-designed and long-term initiative supports for sustainable tea agricultural cropping management. Reflecting this, it is also essential to enable modeling of production to consumption process to draw attention through increasing tea agricultural productivity with recording of tea agricultural outputs. So in this paper it is revealed what the initiatives are for support to spatial design and planning of tea agricultural croplands integrated global tea agricultural development by comparison current tea agricultural system. In order to accomplish a broad range of applications as especially registration, recording and monitoring system the spatio-temporal changes based on Geographical Information System (GIS) and Remote Sensing (RS) would be chosen. Our results show that it is coming to the fore together with growing concerns in global agricultural world by lack of a comprehensive integration of cadastre and land administration system for management of tea agricultural croplands having uneven geographic distribution. It has been also found evidence of the certification type of current tea agricultural cropland that is required to register with a certificate integrated land registry and cadastre to enable tea agricultural farming facilities on it by tea parties. They are having been led to mapping by using unique certification types, namely as “certificated cropland”. So, for the future work, it is showed that intended to building a National Tea Agricultural System for environmentally-related tea agricultural croplands development practise in all concerned countries.
    No preview · Article · Mar 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: The aim of this work was to evaluate the performance of hyperspectral data coupled with chemometrics methods in characterizing and detecting the non-visible mechanical damage of blueberries with time evolution. Reflectance and transmittance as well as interactance hypercubes were automatically segmented by the region growing based algorithms. The maximum-normalized spectra were pretreated by the Standard Normal Variate algorithm, and subsequently the Competitive Adaptive Reweighted Sampling algorithm was applied to extract the damage-specific wavelengths. Based on confusion matrices and area under Receiver Operating Characteristics curves, transmittance showed relatively superior performance to reflectance and interactance. Application of new sample set subjected to impact tests with time evolution, results demonstrated that it was especially difficult to distinguish fresh damage in blueberry. At 2 days after impacted, several transmittance-based classifiers obtained satisfactory accuracies for classifying damaged (sound) blueberries: logistic regression 79.1% (85.7%), multilayer perceptron-back propagation 74.4% (92.1%) and logistic function tree 72.1% (95.2%). Furthermore, the physical property preliminarily proved to be more pronounced than the absorbed impact energy for damage incidence and severity of blueberry via the use of multiple comparison.
    No preview · Article · Mar 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: The biomass supply chain is a multiple-segment chain characterized by prominent complexity and uncertainty, and as such, it requires increased managerial efforts as compared to the case of a single operation management. This paper deals with the supply chain management of green (e.g. grass) biomass. Specifically, three different supply chain systems, in terms of machinery configurations, were analyzed and evaluated in terms of task times and cost performance. By using a functional modeling methodology, the structural representations of the systems, in terms of activities, actions, processes, and operations, were generated and implemented by the ExtendSim® simulation software. It was shown that the models can identify the bottlenecks of the systems and can be further used as a decision support system by testing various alternatives, in terms of the resources used and their dimensioning. Finally, the models were evaluated against the sensitivity on input parameters which are known with a level of uncertainty, i.e. the expected yield and the expected machinery performance.
    No preview · Article · Mar 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: The use of robotic systems for horticultural crops is widely known. However, the use of these systems in cruciferous vegetables remains a challenge. The case of cauliflower crops is of special relevance because it is a hand-harvested crop for which the cutting time is visually chosen. This methodology leads to a yield reduction, as some inflorescences are cut before ripening because the leaves hide their real state of maturity. This work proposes the use of depth cameras instead of visual estimation. Using Kinect Fusion algorithms, depth cameras create a 3D point cloud from the depth video stream and consequently generate solid 3D models, which have been compared to the actual structural parameters of cauliflower plants. The results show good consistency among depth image models and ground truth from the actual structural parameters. In addition, the best time for individual fruit cutting could be detected using these models, which enabled the optimization of harvesting and increased yields. The accuracy of the models deviated from the ground truth by less than 2 cm in diameter/height, whereas the fruit volume estimation showed an error below 0.6% overestimation. Analysis of the structural parameters revealed a significant correlation between estimated and actual values of the volume of plants and fruit weight. These results show the potential of depth cameras to be used as a precise tool in estimating the degree of ripeness during the harvesting of cauliflower and thereby optimizing the crop profitability.
    No preview · Article · Mar 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: The pesticide drift in aerial spray applications is harmful both to environment and human beings but hard to be measured. We demonstrated a new method for real-time evaluation of pesticide drift which used infrared thermal imaging technology to detect the thermal differences before and after spraying process and then measured the range and concentration distribution of droplets. The drift distribution and spray range are detected using infrared thermal imaging system combined with image processing algorithms. The experiments were carried out in both ground spray and aerial spray applications. The results showed that this method had the ability to detect the tiny thermal differences during spray application and thus to monitor the aerial drifts. Furthermore, the testing results using this method had well agreement with the water-sensitive paper method. Therefore, it is verified that infrared thermal imaging method combined with infrared image processing algorithms can be used to monitor the pesticide drift in aerial spray application with advantages of fast, non-contact and able to realize real-time measurement.
    No preview · Article · Feb 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: Today the global world is faced to address and meet the key challenges of agricultural development reliant on research and innovation actions. One of these actions is especially linked to the socio-economic requirements, foundational resources and rights of farmers to support agricultural production and outputs. As an agricultural output, some agricultural crops are proposed to satisfy as specialty agricultural crops according to the local and regional needs to enable improvements for all parties to provide good income, promotes equity, growth better livelihood and agricultural employment. These crops have some specific features and become increasingly important to have influenced on regional, national and multi-state agricultural research, development and extension initiatives. And also, they have leading effects on (i) food security, (ii) livelihood security and (iii) agricultural and rural development to make integration with the criteria such as economically significance, interests and feasibility of parties. Although the Agriculture Modality Paper, for agricultural issues released by The Chairman of the World Trade Organization (WTO) Negotiations on Agriculture, covers some criteria helping to define these crops, exactly there have been no globally common standards for identification them. However, it is questioned that how develop the specialty agricultural crops beyond identification of them. In this paper, firstly, it is aimed to address the key needs for future improvements of specialty agricultural crops. This mainly for designation of a framework for these crops covering all components in respond to this question integrated with agricultural innovation units and agricultural development sustainability within the innovation including their attributes and dimensions. Further, this schema focused on the prerequisites framework within the key priorities and the initiatives of innovation based specialty agricultural growth to make integration with ongoing agricultural policy and practice around the world. In follows, it is described the innovation units to improve production efficiency for specialty agricultural crops. Finally, it is represented the attributes and dimensions of sustainability with innovation through the specialty agricultural crop development. Integrated all these stages would provide a basis and methodology for sustainable specialty agricultural crops development strategies, growing under state guarantee in several world countries, following the drivers of agricultural innovation. And also it is expected to contribute to create an opportunity for farmers/organizations to produce such crops by accelerating the rate of innovation adoption within well-established priorities in agricultural rights. So, it is enabled to have an ability to cope with the effects of global agricultural challenges and emerging opportunities.
    No preview · Article · Feb 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: A fast and fully automated software for image analysis (named IMAFISH_ML) was developed to measure 27 fish morphometric traits (technological traits) on three commercially relevant fish species: gilthead seabream (Sparus aurata L., from 12.5 to 36.6 cm length), meagre (Argyrosomus regius, from 17.5 to 58.4 cm length) and red porgy (Pagrus pagrus, from 16.3 to 29 cm length). This analysis was performed by using two images of each fish from different angles (lateral and dorsal). The computer vision algorithm was programmed in MATLAB® v.7.5 and is freely available to aquaculture industry and research, and it is possible to modify or combine traits in order to obtain new ones, according to specific interests and competence. Additionally, an appropriate, easy-to-perform and reproducible protocol to take photographs was also described. In order to validate the software, 500 fish of each species were laterally and dorsally photographed, and the images were processed by using the IMAFISH_ML. Each fish was manually processed to measure its fork length, body weight and fillet weight (phenotypic traits). Correlation coefficients between each fish technological and phenotypic traits were calculated, all of them were statistically significant (P<0.01). Fork length measured by technological and phenotypic methods showed correlation coefficients between 0.98 and 0.99. The average photograph processing time was 10 seconds and 9.7 seconds for lateral and dorsal images, respectively. IMAFISH_ML software provides fish farmers and researchers with an efficient, fast and automatic tool to objectively asses morphological and growth traits. It is a practical and economical way to evaluate products for industrial purposes. Moreover, it is an especially useful tool to be included within genetic breeding programs, as it provides a high number of fast, easy-to-perform and non-invasive traits measurements, which additionally can be correlated to other production traits.
    No preview · Article · Feb 2016 · Computers and Electronics in Agriculture
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    ABSTRACT: Rice is one of the most consumed cereals in the world and the main food product in the diet of the Brazilian population. Brazil itself is among the ten largest producers of rice, and most of the harvest comes from the South and Midwest regions. This paper presents a data mining study of samples of rice obtained from producers in Goiás (Midwest region) and Rio Grande do Sul (South region), and builds classification models capable of predicting the geographical origin of a rice sample based on its chemical components. We use three popular classification techniques, support vector machines, random forests and neural networks, along with the F-score formula which measures the relative importance of the input variables. We achieved very good performances for the SVM, RF and MLP models with 93.66%, 93.83% and 90% prediction accuracy, respectively, on the 10-fold cross validation. The F-score shows that Cd(cadmium), Rb(rubidium), Mg(magnesium) and K(potassium) are the four most relevant components for prediction.
    No preview · Article · Feb 2016 · Computers and Electronics in Agriculture