4.3 Article

Diagnosing early disorders in Jatropha curcas to calcium, magnesium and sulfur deficiency

Journal

JOURNAL OF PLANT NUTRITION
Volume 43, Issue 11, Pages 1604-1616

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/01904167.2020.1730899

Keywords

Jatropha curcas L; nutrient deficiency; nutritional imbalances; photosynthesis

Categories

Funding

  1. FAPESP (Sao Paulo Research Foundation) [2011/15208-0]
  2. CNPq (National Council for Scientific and Technological Development) [310572/2017-7]

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Jatropha is an excellent plant model to evaluate physiological responses involving species tolerance to abiotic stresses, such as low calcium (Ca), magnesium (Mg) and sulfur (S) availability. Moreover, Ca, Mg and S are essential for the establishment of this plant in large areas. Better acknowledgment of appropriate nutrient levels can help with proper fertilization. This study aimed to gain insight during initial growth in Jatropha plants deficient in Ca, Mg and S by measuring leaf gas exchange, nutrient uptake efficiency (UpE), nutrient use efficiency (UtE) and biomass partitioning at plant harvest. Chlorophyll, carotenoid concentration, net photosynthesis rate (A), stomatal conductance (g(S)), transpiration (E), leaf-scale intrinsic water use efficiency (IWUE) and instantaneous carboxylation efficiency (k) in leaves of Ca-, Mg- and S-deficient plants revealed imbalances prior to visual symptom appearance. Nutrient deficiencies decreased A, which in turn hindered plant growth and biomass partitioning among leaves, stem and roots. However, S-deficient plants maintained values of UtE (at 120 days after S withdrawal), as well as of A, g(S), E, k and biomass allocation similar to those of control plants, during all evaluation periods. Jatropha was highly and very sensitive to Ca and Mg deficiency, respectively, with all results were dramatically decreased in contrast to the control. In conclusion, early physiological evaluation of Ca and Mg status in starved young plants with contrasting UtE values may be a reliable tool with which to predict early nutritional deficiencies before visual symptom appearance.

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