Effect of External Factors on Trace Element Profile and Biomass of Mustard (Brássica júncea L.) Microgreens: Neural Network Analysis

Author:

Puhalsky Yan1ORCID,Vorobyov Nikolai2ORCID,Loskutov Svyatoslav1ORCID,Chukaeva Mariia3ORCID,Glushakov Ruslan44ORCID,Babyka Andrew5ORCID,Meshcheriakov Denis6ORCID,Yakubovskaya Alla7ORCID

Affiliation:

1. All-Russian Research Institute for Food Additives

2. All-Russia Research Institute for Agricultural Microbiology

3. Saint-Petersburg Mining University

4. S.M. Kirov Military Medical Academy

5. “Pharmorganic” LLC

6. “Led for Plant” LLC

7. Scientific Research Institute of Agriculture of Crimea

Abstract

Growing organic microgreens indoors requires a unified technological procedure with various external elicitors. The quality of seedlings depends on their ability to accumulate essential microelements. This research assessed the nutrient profile of mustard microgreens using the method of fractal calculation with repeating numerical series. The experiment involved mustard (Brássica júncea L.) of the Nika variety grown in a closed box for 15 days under aggregation with an intensive 16-h photocycle (440 µmoL m2/s). The plants were inoculated with the endomycorrhizal fungus Glomus mosseae. A solution of fulvic acids (100 mg/L) served as a stabilizing organic additive and was introduced into the coconut substrate. The physical treatment included weak static electromagnetic field with magnetic induction (20 mT). The elemental analysis was performed by inductively coupled plasma atomic emission spectrometry on an ICPE-9000 device (Shimadzu, Japan). According to the calculated indices of the microelement biocomposition, the best result belonged to the sample treated with fulvic acids and weak electromagnetic field (IndBcomL = 0.27). The resulting biomass of dry powder for elemental analysis was 10.2 g, which was twice as high as the values obtained in the control sample, not subjected to any external influences (5.2 g). All the variants with mycorrhization produced no positive effect on the total pool of microelements during vegetation. The increase in biomass averaged as low as 20%. Zinc increased by 33.3% while aluminum and iron decreased by 59.5 and 18.0%, respectively. The neural network analysis of the microelements in mustard microgreens proved effective as a mathematical model for biochemical diagnostics of biomass quality. The method could be used to optimize the biotechnological process for other indoor crops as it makes it possible to partially substitute mineral fertilizers with organic and bacterial complex.

Publisher

Kemerovo State University

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