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Mitigation of the effect of secondary salinization by micro soil conditioning
Published May 20, 2020

This research has the general goal to meet the customization of agriculture in small scale farming. We are developing a technique using micro doses of soil conditioners and organic material applied in the root zone of vegetable crops. We expected to change the physical and chemical properties of the affected soil, which has been irrigated w...ith salty water. Two different soil conditioners were tested. A lysimeter experiment including 8 simple drainage lysimeters was set up in the Research Institute of Karcag IAREF University of Debrecen in 2017. The main goal was to study the effect of different soil conditioners on the soil endangered by secondary salinization induced by irrigation with saline water. In order to compare the difference between the treatments, we collected soil samples, water samples, and determined the yields. Chili pepper (Capsicum annuum) was used as an indicator crop during one specific agricultural season. The technique called micro soil conditioning is rational because several reasons. The roles of the technique are various, for example it can serve as a source of carbon or a container for soil amendments and can minimize evaporation. We found this technique not to interfere with the chemical reaction or the interaction with the plants. However, the micro doses of soil amendments had the role to minimize the risk of soil degradation and do not significantly influence soil respiration. In addition, by improving soil properties, soil conditioning increases the leaching of the excess of salts from the root zone. In fact, this technique can decrease the cost of the inputs and improves the production of vegetables, and at the same time mitigates the effect of secondary salinization.

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The effect of different shading net on the Quantum Efficiency of PS II in chilli pepper cultivar ‘Star Flame’
Published December 15, 2019

The study was undertaken to identify the effect of different shading net on the quantum efficiency of PS II on ‘Star Flame’ chilli pepper (Capsicum annuum) over a period of time cultivated under plastic house environment. ‘Star Flame’ pepper was grown under red shading net and samples without shading were used as control. Analysis of ph...otosynthetic activity revealed a significant difference (p<0.05) between Fv/Fm values in control and red shading at the end of July (p = 0.031) after the first harvest. Chlorophyll fluorescence parameter Fv/Fm reflects the maximum quantum efficiency of photosystem II (PS II) used in the detection of early stress in plants.


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Effect of Selenium Supplementation on in vitro Radish and Green Pepper Seedlings Germination
Published December 6, 2005

Selenium (Se) is an essential trace element for animals, microorganisms and some other eukaryotes. It has become increasingly evident that Se plays a significant role in reducing the incidence of lung, colorectal and prostate cancer in humans. Although there is evidence that selenium is needed for the growth of algae, the question of essentiali...ty of Se in vascular plants is unresolved. Therefore Raphanus sativus (Se accumulator) and Capsicum annuum (non Se accumulator) were treated with 0-200 mg/l natrium-selenate. The results showed that lower (2 mg/l) concentration natrium-selenate increased the fitomass and total antioxodant capacity in seedlings.

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Evaluation of the correlations between the normalized difference vegetation index (NDVI) and yield in a seasoning paprika (Capsicum annuum L. var. longum) stand
Published September 18, 2014

...5); font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;">The aim of our examination was to evaluate the correlations between the normalized difference vegetation index (NDVI) and yield, as well as to examine the possibility of yield estimation basedon NDVI in a seasoning paprika population.

Significant correlations were observed during the examination of the correlation between NDVI and yield. Furthermore, it was concluded that yield can be estimated with a 6.6–8.3% mean error based on the regression equations. No significant difference was shown between the error of estimations performed with various regression types and that of the estimations performed at various dates. For this reason, the identification of the optimum estimation method and the determination of the optimum date for estimation call for further examinations.

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