Implementation of theoretical non-photochemical quenching (NPQ(T)) to investigate NPQ of chickpea under drought stress with High-throughput Phenotyping.

Non-photochemical quenching (NPQ) is a protective mechanism for dissipating excess energy generated during photosynthesis in the form of heat. The accelerated relaxation of the NPQ in fluctuating light can lead to an increase in the yield and dry matter productivity of crops. Since the measurement of NPQ is time-consuming and requires specific light conditions, theoretical NPQ (NPQ(T)) was introduced for rapid estimation, which could be suitable for High-throughput Phenotyping. We investigated the potential of NPQ(T) to be used for testing plant genetic resources of chickpea under drought stress with non-invasive High-throughput Phenotyping complemented with yield traits. Besides a high correlation between the hundred-seed-weight and the Estimated Biovolume, significant differences were observed between the two types of chickpea desi and kabuli for Estimated Biovolume and NPQ(T). Desi was able to maintain the Estimated Biovolume significantly better under drought stress. One reason could be the effective dissipation of excess excitation energy in photosystem II, which can be efficiently measured as NPQ(T). Screening of plant genetic resources for photosynthetic performance could take pre-breeding to a higher level and can be implemented in a variety of studies, such as here with drought stress or under fluctuating light in a High-throughput Phenotyping manner using NPQ(T).

Quantitative monitoring of Arabidopsis thaliana growth and development using high-throughput plant phenotyping.

With the implementation of novel automated, high throughput methods and facilities in the last years, plant phenomics has developed into a highly interdisciplinary research domain integrating biology, engineering and bioinformatics. Here we present a dataset of a non-invasive high throughput plant phenotyping experiment, which uses image- and image analysis- based approaches to monitor the growth and development of 484 Arabidopsis thaliana plants (thale cress). The result is a comprehensive dataset of images and extracted phenotypical features. Such datasets require detailed documentation, standardized description of experimental metadata as well as sustainable data storage and publication in order to ensure the reproducibility of experiments, data reuse and comparability among the scientific community. Therefore the here presented dataset has been annotated using the standardized ISA-Tab format and considering the recently published recommendations for the semantical description of plant phenotyping experiments.

Allergen sanitation in the food industry: a systematic industrial scale approach to reduce hazelnut cross-contamination of cookies.

Recently, we investigated the impact of shared equipment on cross-contamination of cookies at a pilot plant scale. Based on those findings, this study investigated the extent and subsequent sanitation of hazelnut cross-contamination (HNCC) of cookies at the industrial scale. Similarly, a product change from cookies with hazelnut ingredient to cookies without hazelnut was performed on standard equipment. HNCC in the hazelnut-free follow-up product was quantified by enzyme-linked immunosorbent assay for each production device and the applied cleaning procedure. All experiments were repeated in duplicate. The highest HNCC was found in concordance with previous studies after mere mechanical scraping: more than 1,000 mg of hazelnut protein per kg was quantified in the follow-up product after processing by a cookie machine. Additional cleaning with hot water decreased the HNCC irrespective of the processing device to levels at or below 1 mg of hazelnut protein per kg. Furthermore, raw materials for cookie production were monitored over a period of 24 months for unwanted preloads of hazelnut and peanut: hazelnut was quantified in 16% of the investigated raw materials as being between 0.26 and 90 mg/kg. Further critical control points at the industrial scale, where cross-contamination might occur, were identified but did not display noteworthy sources of cross-contamination. In conclusion, the quantitative monitoring of the cleaning efficiency at the industrial scale confirmed the procedure of manual scraping plus wet cleaning as a qualified sanitation procedure to effectively reduce the hazelnut protein cross-contamination down to a level at which severe hazelnut-related allergic reactions are unlikely to occur.