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הנהלה מרכז מידע - ספריה תלמידי מחקר יחידה עסקית דוברות מכוני מחקר אודות
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מכון למדעי הקרקע, המים והסביבה

כימיה של הקרקע והזנת הצמח

  • גרבר אלן e-mail צוות: none
    Issues in Rehabilitation of Cacao Forests due to Cu Toxicity
    Vast numbers of trees in the major cacao growing regions of West Africa (2/3 of global production of cacao) are dying from diseases. Moreover, many trees are old and long past their productive years. For these reasons, widespread cacao plantation rehabilitation via new plantings (upwards of 50 to 80 million new seedlings) is a key goal of these countries. However, a major barrier to successful cacao sector rehabilitation is a low seedling survival rate following planting-out. We suspect that a major contributor to the low planting-out success rate is soil contamination by Cu due to repetitive high-dose applications of Cu-fungicides in cacao farms over the previous 20 years. While Cu is an essential plant micro-nutrient, excess soil Cu can cause iron (Fe) chlorosis in plants, affecting productivity. Excess Cu can also be highly toxic and detrimental to development of cocoa seedling roots. Excess Cu tends to accumulate in plant roots, where it causes oxidative stress and disrupts uptake
    Ph.D. in soil chemistry, plant science, microbiology, or toxicology
    Hands on experience in chemical laboratory (making up solutions, using analytical equipment) is essential; all the rest can be taught
    Ability to quickly learn and integrate knowledge from several different disciplines into a comprehensive whole, interest in working with plants and in the chemical laboratory, able to work well in teams and with foreign scientists, excellent English reading, writing and speaking skills

פיזיקה סביבתית והשקיה

  • רוזנשטיין עופר e-mail צוות: various
    Remote sensing models for irrigation and fertilization in precision agriculture and soil sciences.
    Using satellite and UAV remote sensing to model crop water use against evapotranspiration measurements from an eddy covariance tower. Improving yield predictions by assimilating remote sensing estimations of evapotranspiration into mechanistic crop models. Remote sensing modeling of surface energy balance and evapotranspiration. Meteorological modeling of evapotranspiration. Machine learning and artificial intelligence for evapotranspiration estimates. Spatial estimations of evapotranspiration based on meteorological measurements. The use of SAR interferometry for soil degradation studies.
    Ph.D. relevant to modelling in engineering, agricultural and/or physical sciences;
    The candidate is expected to have a strong publication record.
    Good knowledge of statistics, model performance evaluation, optimization techniques and database management; Abilities to use and write scripts in Matlab / Python or another scientific programming language; Basic knowledge in climatology, micrometeorology, agronomy and use of earth observation data.
מעודכן לתאריך: 21/04/20 13:51
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