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"precision agriculture"

Qi Li, Guiping Hu, Talukder Zaki Jubery, Baskar Ganapathysubramanian
Farmland management involves several planning and decision making tasks including seed selection and irrigation management. A farm-level precision farmland management model based on mixed integer linear programming is proposed in this study. Optimal decisions are designed for pre-season planning of crops and irrigation water allocation. The model captures the effect of size and shape of decision scale as well as special irrigation patterns. The authors illustrate the model with a case study on a farm in the state of California in the U...
2017: PloS One
Pouria Sadeghi-Tehran, Kasra Sabermanesh, Nicolas Virlet, Malcolm J Hawkesford
Recording growth stage information is an important aspect of precision agriculture, crop breeding and phenotyping. In practice, crop growth stage is still primarily monitored by-eye, which is not only laborious and time-consuming, but also subjective and error-prone. The application of computer vision on digital images offers a high-throughput and non-invasive alternative to manual observations and its use in agriculture and high-throughput phenotyping is increasing. This paper presents an automated method to detect wheat heading and flowering stages, which uses the application of computer vision on digital images...
2017: Frontiers in Plant Science
Erico Leão, Carlos Montez, Ricardo Moraes, Paulo Portugal, Francisco Vasques
The use ofWireless Sensor Network (WSN) technologies is an attractive option to support wide-scale monitoring applications, such as the ones that can be found in precision agriculture, environmental monitoring and industrial automation. The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable topology to build wide-scale WSNs. Despite some of its known advantages, including timing synchronisation and duty-cycle operation, cluster-tree networks may suffer from severe network congestion problems due to the convergecast pattern of its communication traffic...
January 27, 2017: Sensors
María L Pérez-Bueno, Mónica Pineda, Francisco M Cabeza, Matilde Barón
The negative impact of conventional farming on environment and human health make improvements on farming management mandatory. Imaging techniques are implemented in remote sensing for monitoring crop fields and plant phenotyping programs. The increasingly large size and complexity of the data obtained by these techniques, makes the implementation of powerful mathematical tools necessary in order to identify informative parameters and to apply them in precision agriculture. Multicolor fluorescence imaging is a useful approach for the study of plant defense responses to stress factors at bench scale...
2016: Frontiers in Plant Science
Yang Zheng, Bingfang Wu, Miao Zhang, Hongwei Zeng
Timely and efficient monitoring of crop phenology at a high spatial resolution are crucial for the precise and effective management of agriculture. Recently, satellite-derived vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), have been widely used for the phenology detection of terrestrial ecosystems. In this paper, a framework is proposed to detect crop phenology using high spatio-temporal resolution data fused from Systeme Probatoire d'Observation de la Tarre5 (SPOT5) and Moderate Resolution Imaging Spectroradiometer (MODIS) images...
December 10, 2016: Sensors
Naisen Liu, Weixing Cao, Yan Zhu, Jingchao Zhang, Fangrong Pang, Jun Ni
Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have k-connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect...
December 9, 2016: Sensors
Ramón Martínez, Juan Ángel Pastor, Bárbara Álvarez, Andrés Iborra
Wireless sensor networks (WSNs) represent one of the most promising technologies for precision farming. Over the next few years, a significant increase in the use of such systems on commercial farms is expected. WSNs present a number of problems, regarding scalability, interoperability, communications, connectivity with databases and data processing. Different Internet of Things middleware is appearing to overcome these challenges. This paper checks whether one of these middleware, FIWARE, is suitable for the development of agricultural applications...
November 23, 2016: Sensors
S Peukert, B A Griffith, P J Murray, C J A Macleod, R E Brazier
One of the major challenges for agriculture is to understand the effects of agricultural practices on soil properties and diffuse pollution, to support practical farm-scale land management. Three conventionally managed grassland fields with similar short-term management, but different ploughing histories, were studied on a long-term research platform: the North Wyke Farm Platform. The aims were to (i) quantify the between-field and within-field spatial variation in soil properties by geostatistical analysis, (ii) understand the effects of soil condition (in terms of nitrogen, phosphorus and carbon contents) on the quality of discharge water and (iii) establish robust baseline data before the implementation of various grassland management scenarios...
July 2016: European Journal of Soil Science
Tao Huang, Siyu Yan, Fan Yang, Jiang Liu
Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control...
November 6, 2016: Sensors
Jianfeng Zhang, Jinyang Hu, Lvwen Huang, Zhiyong Zhang, Yimian Ma
Precision agriculture is the trend of modern agriculture, and it is also one of the important ways to realize the sustainable development of agriculture. In order to meet the production requirements of precision agriculture-efficient use of agricultural resources, and improving the crop yields and quality-some necessary field information in crop growth environment needs to be collected and monitored. In this paper, a farmland information collection system is developed, which includes a portable farmland information collection device based on STM32 (a 32-bit comprehensive range of microcontrollers based on ARM Crotex-M3), a remote server and a mobile phone APP...
October 22, 2016: Sensors
Marien Havé, Anne Marmagne, Fabien Chardon, Céline Masclaux-Daubresse
As a result of climate changes, land use and agriculture have to adapt to new demands. Agriculture is responsible for a large part of the greenhouse gas (GHG) emissions that have to be urgently reduced in order to protect the environment. At the same time, agriculture has to cope with the challenges of sustainably feeding a growing world population. Reducing the use of the ammonia-nitrate fertilizers that are responsible for a large part of the GHGs released and that have a negative impact on carbon balance is one of the objectives of precision agriculture...
October 5, 2016: Journal of Experimental Botany
Ronan Le Cointe, Thomas E Simon, Patrick Delarue, Maxime Hervé, Melen Leclerc, Sylvain Poggi
Reducing our reliance on pesticides is an essential step towards the sustainability of agricultural production. One approach involves the rational use of pesticides combined with innovative crop management. Most control strategies currently focus on the temporal aspect of epidemics, e.g. determining the optimal date for spraying, regardless of the spatial mechanics and ecology of disease spread. Designing innovative pest management strategies incorporating the spatial aspect of epidemics involves thorough knowledge on how disease control affects the life-history traits of the pathogen...
2016: PloS One
Khalid A Al-Gaadi, Abdalhaleem A Hassaballa, ElKamil Tola, Ahmed G Kayad, Rangaswamy Madugundu, Bander Alblewi, Fahad Assiri
Crop growth and yield monitoring over agricultural fields is an essential procedure for food security and agricultural economic return prediction. The advances in remote sensing have enhanced the process of monitoring the development of agricultural crops and estimating their yields. Therefore, remote sensing and GIS techniques were employed, in this study, to predict potato tuber crop yield on three 30 ha center pivot irrigated fields in an agricultural scheme located in the Eastern Region of Saudi Arabia...
2016: PloS One
Rui-Tao Liu, Lu-Qi Tao, Bo Liu, Xiang-Guang Tian, Mohammad Ali Mohammad, Yi Yang, Tian-Ling Ren
Recently, precision agriculture has become a globally attractive topic. As one of the most important factors, the soil nutrients play an important role in estimating the development of precision agriculture. Detecting the content of nitrogen, phosphorus and potassium (NPK) elements more efficiently is one of the key issues. In this paper, a novel chip-level colorimeter was fabricated to detect the NPK elements for the first time. A light source-microchannel photodetector in a sandwich structure was designed to realize on-chip detection...
2016: Sensors
Moacir Ponti, Arthur A Chaves, Fabio R Jorge, Gabriel B P Costa, Adimara Colturato, Kalinka R L J C Branco
Low cost remote sensing imagery has the potential to make precision farming feasible in developing countries. In this article, the authors describe image acquisition from eucalyptus, bean, and sugarcane crops acquired by low-cost and low-altitude systems. They use different approaches to handle low-altitude images in both the RGB and NIR (near-infrared) bands to estimate and quantify plantation areas.
July 2016: IEEE Computer Graphics and Applications
Yeyin Shi, J Alex Thomasson, Seth C Murray, N Ace Pugh, William L Rooney, Sanaz Shafian, Nithya Rajan, Gregory Rouze, Cristine L S Morgan, Haly L Neely, Aman Rana, Muthu V Bagavathiannan, James Henrickson, Ezekiel Bowden, John Valasek, Jeff Olsenholler, Michael P Bishop, Ryan Sheridan, Eric B Putman, Sorin Popescu, Travis Burks, Dale Cope, Amir Ibrahim, Billy F McCutchen, David D Baltensperger, Robert V Avant, Misty Vidrine, Chenghai Yang
Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e...
2016: PloS One
Francisco Javier Ferrández-Pastor, Juan Manuel García-Chamizo, Mario Nieto-Hidalgo, Jerónimo Mora-Pascual, José Mora-Martínez
The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of these main barriers are expensive equipment, the difficulty to operate and maintain and the standard for sensor networks are still under development. Nowadays, new technological development in embedded devices (hardware and communication protocols), the evolution of Internet technologies (Internet of Things) and ubiquitous computing (Ubiquitous Sensor Networks) allow developing less expensive systems, easier to control, install and maintain, using standard protocols with low-power consumption...
2016: Sensors
Dionisio Andújar, José Dorado, César Fernández-Quintanilla, Angela Ribeiro
The use of depth cameras in precision agriculture is increasing day by day. This type of sensor has been used for the plant structure characterization of several crops. However, the discrimination of small plants, such as weeds, is still a challenge within agricultural fields. Improvements in the new Microsoft Kinect v2 sensor can capture the details of plants. The use of a dual methodology using height selection and RGB (Red, Green, Blue) segmentation can separate crops, weeds, and soil. This paper explores the possibilities of this sensor by using Kinect Fusion algorithms to reconstruct 3D point clouds of weed-infested maize crops under real field conditions...
2016: Sensors
Ahmed G Kayad, Khalid A Al-Gaadi, ElKamil Tola, Rangaswamy Madugundu, Ahmed M Zeyada, Chariton Kalaitzidis
Understanding the temporal and spatial variability in a crop yield is viewed as one of the key steps in the implementation of precision agriculture practices. Therefore, a study on a center pivot irrigated 23.5 ha field in Saudi Arabia was conducted to assess the variability in alfalfa yield using Landsat-8 imagery and a hay yield monitor data. In addition, the study was designed to also explore the potential of predicting the alfalfa yield using vegetation indices. A calibrated yield monitor mounted on a large rectangular hay baler was used to measure the actual alfalfa yield for four alfalfa harvests performed in the period from October 2013 to May 2014...
2016: PloS One
Lin Gao, Chang-chun Li, Bao-shan Wang, Yang Gui-jun, Lei Wang, Kui Fu
With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively...
January 2016: Ying Yong Sheng Tai Xue Bao, the Journal of Applied Ecology
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