Wheat seeds and biophotons

Research papers concerning agrohomeopathy, homeopathy (if relevant to agriculture), and so forth.
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Wheat seeds and biophotons

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Biophoton emission in high-potency research on wheat seed models.

Peters G, van Wijk R, Endler PC.

Abstract
Background: Researchers at the interuniversity college for health and development
Graz/Castle of Seggau, showed in a model with seeds (Triticum aestivum), that
homeopathic gibberellic acid (GA3) D30 is able to influence the growth length of the
seeds, which had been measured after 7 days. The inhibition or the stimulation of
the growth length correlated to the time period in which the researches had been
done (winter, spring or autumn).

Objective: Is it possible to recognize the long-term effects from homeopathic
gibberellic acid on the growth length, in very early stages, by studying coherence
effects with biophoton emission measurings?

Materials and methods: The biophoton emission from Triticum aestivum was
measured in dry and wet conditions for different time periods. For wet conditions 4
different trigger solutions were chosen: gibberellic acid (GA3) D30, water D30,
gibberellic acid (GA3) molecular and water molecular. The homeopathic agents were
ultra-high dilutions above the Avogadro number to prevent molecular interactions.
Results: In total 64,000 measuring points on the different samples were corrected by
the background signal and evaluated. The trigger solutions showed significantly
different photon emission patterns during early development.

Conclusion: The results back the hypothesis, that the effects of homeopathic agents
on biological systems may be recognized in very early stages by biophoton
coherence measurings. The observations of the present data showed similarities
with the growth length experiments, which had been done in the same time period.
The wheat seed model which showed some fluctuations, has to be refined, and
might thus be an interesting model for studying coherence interactions in relation to
homeopathic agents. Further research is required to make the model more stable, to
define his boundaries and to increase the amount of data.