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Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit
(2017)
(1) Background: The aim of the study was to use innovative sensor technology for non-destructive determination and prediction of optimum harvest date (OHD), using sweet cherry as a model fruit, based on different ripening parameters. (2) Methods: Two cherry varieties in two growing systems viz. field and polytunnel in two years were employed. The fruit quality parameters such as fruit weight and size proved unsuitable to detect OHD alone due to their dependence on crop load, climatic conditions, cultural practices, and season. Coloration during cherry ripening was characterized by a complete decline of green chlorophyll and saturation of the red anthocyanins, and was measured with a portable sensor viz. spectrometer 3-4 weeks before expected harvest until 2 weeks after harvest. (3) Results: Expressed as green NDVI (normalized differential vegetation index) and red NAI (normalized anthocyanin index) values, NAI increased from -0.5 (unripe) to +0.7 to +0.8 in mature fruit and remained at this saturation level with overripe fruits, irrespective of variety, treatment, and year. A model was developed to predict the OHD, which coincided with when NDVI reached and exceeded zero and the first derivative of NAI asymptotically approached zero. (4) Conclusion: The use of this sensor technology appears suitable for several cherry varieties and growing systems to predict the optimum harvest date.
The design of future materials for biotechnological applications via deposition of molecules on surfaces will require not only exquisite control of the deposition procedure, but of equal importance will be our ability to predict the shapes and stability of individual molecules on various surfaces. Furthermore, one will need to be able to predict the structure patterns generated during the self-organization of whole layers of (bio)molecules on the surface. In this review, we present an overview over the current state of the art regarding the prediction and clarification of structures of biomolecules on surfaces using theoretical and computational methods.
Beta-ketothiolase deficiency, also known as mitochondrial acetoacetyl-CoA thiolase (T2) deficiency, is an autosomal recessive disease caused by mutations in the acetylCoA acetyltransferase 1 (ACAT1) gene. A German T2deficient patient that developed a severe ketoacidotic episode at the age of 11 months, was revealed to be a compound heterozygote of a previously reported null mutation, c.472A>G (p.N158D) and a novel mutation, c.949G>A (p.D317N), in ACAT1. The c.949G>A mutation was suspected to cause aberrant splicing as it is located within an exonic splicing enhancer sequence (c. 947CTGACGC) that is a potential binding site for serine/argininerich splicing factor 1. A mutation in this sequence, c.951C>T, results in exon 10 skipping. A minigene construct was synthesized that included exon 9truncated intron 9exon 10truncated intron 10exon 11, and the splicing of this minigene revealed that the c.949G>A mutant construct caused exon 10 skipping in a proportion of the transcripts. Furthermore, additional substitution of G for C at the first nucleotide of exon 10 (c.941G>C) abolished the effect of the c.949G>A mutation. Transient expression analysis of the c.949G>A mutant cDNA revealed no residual T2 activity in the mutated D317N enzyme. Therefore, c.949G>A (D317N) is a pathogenic missense mutation, and diminishes the effect of an exonic splicing enhancer and causes exon 10 skipping. The present study demonstrates that a missense mutation, or even a synonymous substitution, may disrupt enzyme function by interference with splicing.