Green mathematics: Benefits of including biological variation in your data analysis
Biological variation is omnipresent in nature. It contains useful information that is neglected by the usually applied statistical procedures. To extract this information special procedures have to be applied. Biological variation is seen in properties (e.g. size, colour, firmness), but the underlying issue is almost always to the variation in development or maturity in a batch of individuals generated by small scale environmental differences. The principles of assessing biological variation in batches of individuals are explained without putting emphasis on mathematical details. Obtained explained parts increase from about 60 to 80 % for the usual approach to 95 when the biological variation is taken into account. When technical variation or measuring error is small even 99 % can be achieved. The benefit of the presented technology is highlighted based on a number of already published studies covering the colour of apples during growth and storage and the firmness of cut tomatoes during storage.
The biological shift factor. Biological age as a tool for modelling in pre- and postharvest horticulture
Individuals differ in development stage or biological age. This difference can be taken into account when modelling the quality behaviour of various fruits and vegetables. Even on a batch level, the same principle can be applied, provided the variation within a batch is not too large. By applying the biological shift factor, i.e. a shift in calendar time, the effects of different growing and harvesting condition can be included in modelling quality behaviour, which widely opens alleys for producing models applicable in the entire globalised food chain. The variation in biological shift factor over individuals in a batch and over several batches seems to exhibit a normal distribution pattern.
Instrumentation and Automated Photometric Titration Procedure for Total Acidity Determination in Red Wine Employing a Multicommuted Flow System
An automated procedure for photometric titration of red wine and associated instrumentation is described. The procedure was based on the flow-batch approach implemented employing multicommutation. The photometric detection was carried out using a homemade LED-based photometer. The mixing device, LED, and photodetector were attached to the titration chamber in order to form a compact and small-sized unit. The flow system comprised an automatic injector and three-way solenoid valves, which were controlled by a microcomputer through an electronic interface card. The software, written in Quick BASIC 4.5, was designed with abilities to accomplish all steps of the titration procedure including data acquisition and real-time processing to decide about the course of titration in the following step and so forth, until the titration endpoint was reached. The usefulness of the proposed titration system was demonstrated by analyzing red wine samples. When results were compared with those obtained using the AOAC reference method, no significant difference was observed at the 95% confidence level. A relative standard deviation of ca  2% (n=9 ) was obtained when processing a typical red wine sample containing 7.3 gl -1 total acidity expressed as tartaric acid.