Advances in Crop Science and Technology
Open Access

Research Article

Using Spatial Analysis of ANR1 Gene Transcription Rates for Detecting Nitrate Irregularities in Cherry Tomatoes (Solanum lycopersicum var. cerasiforme) Organic Greenhouses

¹The Department of Geography and Environmental Development, Ben Gurion University of the Negev, Bee’r Sheva, Israel

²TheDepartment of Soil and Water Sciences, Hebrew University, Rehovot, Israel

³Technological Center, Biotechnology Unit, Beer Sheva, Israel

⁴Katif R&D Center for Coastal Deserts Development Ministry of Science, Israel

*Corresponding Author:

Amir Mor-Mussery
Ben Gurion University of the Negev
Bee’r Sheva
Israel
Tel: 9720502213141
E-mail: Amir.mussery@gmail.com

Received date: January 15, 2017; Accepted date: June 27, 2017; Published date: July 04, 2017

Citation: Mor-Mussery A, Edelbaum O, Budovsky A, Ben Asher J (2017) Using Spatial Analysis of ANR1 Gene Transcription Rates for Detecting Nitrate Irregularities in Cherry Tomatoes (Solanum lycopersicum var. cerasiforme) Organic Greenhouses. Adv Crop Sci Tech 5: 286. doi: 10.4172/2329-8863.1000286

Copyright: © 2017 Mor-Mussery A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Organic fertilizers differ from the chemical ones by high inconsistency in their mineralization rates in the soil. This intrinsic property occasionally results in formation of distinct ‘soil patches’ different from one another with regard to the concentrations of soluble nutrients. This feature together with the different nutritional requirements during the crop’s physiological development complicates the designing of appropriate organic fertilization scheme. To overcome these difficulties a methodology was designed and tested based on analysis of molecular indicators. As a case study we tested cherry tomato (Solanum lycopersicum var. cerasiforme) organically grown in greenhouse located in Netzer Hazani village, Northern Negev, Israel at 2001. As a model nutrient we chose the soluble nitrate, due to its importance for the crop growth and development. We found that the best indicator of nitrate content were the ANR1 gene transcription rates which values were best correlated to the measured soluble nitrate in soil and the crop’s needs during development. Practically, the spatial analysis helped identifying the surpluses and deficits of soluble nitrate in soil patches which were subsequently treated in a quick and precise manner. Implementing this methodology on other crops and nutrients will allow constructing accurate and economical fertilization scheme which decrease the damages to ecosystems.

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