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Franc Bavec

Researcher at Life Sciences Institute

Publications -  12
Citations -  383

Franc Bavec is an academic researcher from Life Sciences Institute. The author has contributed to research in topics: Organic farming & Living mulch. The author has an hindex of 7, co-authored 12 publications receiving 325 citations. Previous affiliations of Franc Bavec include University of Maribor.

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Biodynamic agriculture research progress and priorities

TL;DR: In this paper, a fair share of the available peer-reviewed research results of controlled field experiments as well as case studies show effects of BD preparations on yield, soil quality and biodiversity, and BD preparations express a positive environmental impact in terms of energy use and efficiency.
Book

Organic Production and Use of Alternative Crops

Franc Bavec, +1 more
TL;DR: An attempt is made to evaluate the phytochemical properties of wheatgrass, which has potential in finding its application in organic agriculture, as well as other crops, such as barley and oats.
Journal ArticleDOI

Influence of industrial and alternative farming systems on contents of sugars, organic acids, total phenolic content, and the antioxidant activity of red beet (Beta vulgaris L. ssp. vulgaris Rote Kugel).

TL;DR: The contents of sugars, organic acids, total phenolic content, and the antioxidant activity were quantified in the flesh of red beet from conventional (CON), integrated (INT), organic (ORG), biodynamic (BD), and control farming systems using established methods.
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Cover crops in organic field vegetable production

TL;DR: In this paper, the authors discuss the use of cover crop species and management practices based on the needs and goals of sustainable production in vegetable production and summarised studies show that further research is needed for best practices of vegetable production especially using living mulches and roller crimper for termining cover crops before planting vegetables.
Journal ArticleDOI

The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification

TL;DR: An interesting result of successful distinguishing between the infected and uninfected parts of the seed surface is produced and these components could be used in further studies for the development of a sorting model by combining data from multispectral imaging and SKNIR for identifying disease(s) and varieties.