VARIABLES TO BE MEASURED. Chilling injury (Lenticel spots, peel discoloration, darkening of the pulp, and aroma); weight loss, peel color, firmness, pulp color, and TSS. Detailed description of the methodology For each variety in a determined packinghouse 62 fruit per treatment were gotten (2 boxes with 31 fruit each). Fruit were collected just after washing and already classified for quarantine hot water treatment for 75 or 90 min. Then, they were separated according to ripening stage considering partially ripe fruit (flat shape without full cheeks and shoulders below the pedicel insertion; pulp color values between 1 and 2 and total soluble solids content of < 7.3 °Bx in Xxxxx, Xxxx and Xxxxx as well as < 6.0 °Bx in Ataulfo) and ripe fruit (round shape with full cheeks and shoulders above the pedicel insertion; pulp color values between 2 and 3 and total soluble solids content of > 7.3 °Bx in Xxxxx, Xxxx and Xxxxx as well as > 6.0 °Bx in Ataulfo). Fruit were with excellent external appearance, free of mechanical damage, pests, and diseases. Immediately quarantine hot water treatment for each variety and size was applied according to USDA-APHIS protocol. Then, fruit were stored at different temperatures (45.5±1.5ºF, 50.0±1.5ºF and 54.5±1.5ºF) in commercial cold rooms up to three weeks with weekly transfers to marketing simulation (71.6±3 °F; 75±10 % RH) until ready to eat stage. Sampling was done at the beginning, at the end of refrigerated period and then at consumption stage.
VARIABLES TO BE MEASURED. 4..4........
VARIABLES TO BE MEASURED. ND research is generally interested in many different aspects of the traffic task and, therefore, needs to measure many different variables. Which variables these exactly are depends again on the research questions. The variables can be grouped by • Demographic and personality variables (e.g. age, gender); • Driving behaviour variables (e.g. number of lane changes); • Driver distraction and state variables (e.g. mental workload, fatigue); • Vehicle condition variables (e.g. vehicle type, presence of ACC); • Vehicle variables (e.g. speed, steering wheel angle); • Weather and light conditions variables (e.g. precipitation, temperature); • Traffic condition variables (e.g. traffic density, traffic composition); • Road variables (e.g. speed limit, lane width) Appendix III contains a comprehensive list of variables that may be relevant to be measured during an ND study. In general it is useful to gather as many variables as practically possible. Even if no specific impacts are expected of certain variables, some outcomes may be explained better with more knowledge about the drivers, the roads or the vehicles. Driver distraction is described in a separate list of variables. The reason is that the 100- car ND study in the U.S. (see Chapter 2) found that distraction was a potentially con- tributing factor in more than 80 percent of all safety-critical events. Therefore, the prevalence and risk of (various forms of) distraction is an important road safety topic and it is a topic that is difficult to measure with research methods other than ND. Rele- vant variables are mental workload, fatigue/drowsiness, distraction from the primary task (e.g. eye tracking), presence and use of in-car devices and the performance of tasks other than the driving task. With respect to road variables, as a minimum, the three main road categories have to be differentiated: urban, rural, and motorway. Subcategories can be distinguished if relevant for the research question at stake. Subsequently, roads can be classified ac- cording to, for example, their design and layout (number of lanes, horizontal and longi- tudinal profile, etc.) and legal aspects (speed limits, right of way, etc.). In principle, this type of data can be scored on the basis of the ND video recordings from the vehicle. However, to facilitate the task and to save analysis time, it is to be preferred to have this type of information available in an electronic map linked to the geographical posi- tion of the vehicle. Thi...
