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Gilat Center
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| BEN GAL ALON |
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Team:Dr Aviva Peeters (TerraVisionLab), Yafit Cohen (Agricultural Engineering, ARO Volcani) |
| Decision-making tools for precision irrigation |
We have models for optimization of a|) predicting factors of interest as a function of their spatial variability, b) delineating management zones, and c) sensor/sample placement based on big data from years of field experiments in vineyards, orchards, and field crops. We now want to bring these to decision-makers as accessible applications for practical use. We need you to work with the models, code and program them into APPs. Interactions with international (EU, China, USA) funded projects and their researchers. Initial project will involve developing a web-based application based on an existing Python model.
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| Education requirements |
| Programming. Full Stack developer |
| Scientific experience |
| Programming a must. GIS advantage. Precision agriculture data processing advantage |
| Skills |
| • Python, HTML/JavaScript/CSS • Programming skills in a GIS environment, an advantage |
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| Table grapes fertilization with Nitrogen (N) potassium (K) and phosphorus (P) |
Numerous environmental conditions and viticultural practices are known to alter the vine growth and productivity and grapes quality. Key factors among these are climatic conditions (temperature, solar radiation, and humidity), grapevine cultivars and rootstocks used, irrigation, crop load, and canopy management practices.The impact of vine nutrient supply, particularly on productivity and quality parameters is less understood.In the current study we plan to use an innovative growing system, which worked successfully in determining the fertilization requirements of olive, pomegranates and almond. In this system, we grow the trees in containers in perlite media with full control of the nutritional elements arriving with the water. . We will test two table grapes cultivar, the early bearing, green 'Early Sweet' and the late bearing, purple color, 'Crimson', which will be grown in 500-L containers filled with perlite. In each variety, we will test five levels of N (10, 20 ,70, 100 and 20
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| Education requirements |
| Ph. D. In plant sciences/ soil-water-plant interaction. |
| Scientific experience |
| Plant nutrition |
| Skills |
| Fluent English, good background in statistics, experience in plant physiology and plant nutrition research. |
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| BEN-YOSEF MICHAEL |
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Team:Dr. Yafit Cohen, Department of sensing, information and mechanization engineering, Institute of agricultural engineering |
| The urban dimension in the spatial distribution of pest fruit flies in Israel |
The spatial distribution and population dynamics of pests often extend beyond agro-ecosystems into other habitats surrounding the agricultural area. Of these, the urban dimension, due to its extensive development and increasing integration with agricultural lands, has an increasing contribution to the preservation and dissemination of agricultural pests. In this study, we will characterize the effect of settlements on the spatio-temporal dynamics of fruit fly populations in surrounding fruit orchards, using geostatistics, eco-informatics and spatio-temporal analyses of a large monitoring database. Our ultimate aim is to set the grounds for a pest control interface that will be applied to settlements in order to reduce the presence of pest flies in fruit orchards.
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| Education requirements |
| Ph. D. |
| Scientific experience |
| eco-informatics, data science, spatial ecology |
| Skills |
| statistics, programming, managing big data |
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| Precise citrus fertilization - guiding mineral applications by high-throughput diagnoses |
We intend to advance intensive farming to precise mineral applications that maximize cost-effectiveness and eliminate contaminating runoffs. Up-to-date, there are few resources to guide mineral applications because there are finite diagnostic tools. The limited datasets of seasonal changes in the mineral composition of crops are not sufficient for breakthroughs in computational approaches to fertilization. Hence, we are upgrading the experimental and analytical facilities in ARO-Gilat to: ? Treat citrus trees with deficient to excessive nutritional applications in a large lysimeter setup. ? Determine the nutritional composition of leaves with a wide range of mineral concentrations. ? Develop and calibrate chemometric tools for micro-elements and macro-elements leaf analyses. ? Construct a seasonal dataset of nutrients uptake and the corresponding leaf mineral composition. ? Associate between leaves’ mineral composition and their vegetative or reproductive physiological performance
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| Education requirements |
| Ph.D. in agronomy, biology, or earth sciences |
| Scientific experience |
| Complete thesis in agronomy, biology, or earth sciences |
| Skills |
| Scientific writing, data processing, statistics, laboratory essays, field monitoring, and farming knowledge. |
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| Updated on: 17/05/22 11:39 |
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