This study was aimed at exploring data analysis techniques for generating accurate estimates of the loss in quality of fresh fruits, vegetables and cut flowers in chilled supply chains based on data from advanced sensors. It was motivated by the recent interest in the application of advanced sensors, by emerging concepts in quality controlled logistics, and by the desire to minimise quality losses during transport and storage of the produce. Cut roses were used in this work although the findings will also be applicable to other produce. The literature has reported that whilst temperature was considered to be the most critical post-harvest factor, others such as growing conditions could also be important in the senescence of cut roses. Kinetic modelling was the most commonly used modelling approach for shelf life predictions of foods and perishable produce, but not for estimating vase life (VL) of cut flowers, and so this was explored in this work along with multiple linear regression (MLR) and partial least squares (PLS). As the senescence of cut roses is not fully understood, kinetic modelling could not be implemented directly. Consequently, a novel technique, called Kinetic Linear System (KLS), was developed based on kinetic modelling principles. Simulation studies of shelf life predictions for tomatoes, mushrooms, seasoned soybean sprouts, cooked shrimps and other seafood products showed that the KLS models could effectively replace the kinetic ones. With respect to VL predictions KLS, PLS and MLR were investigated for data analysis from an in-house experiment with cut roses from Cookes Rose Farm (Jersey). The analysis concluded that when the initial and final VLs were available for model calibration, effective estimates of the post-harvest loss in VL of cut roses could be obtained using the post-harvest temperature. Otherwise, when the initial VLs were not available, such effective estimates could not be obtained. Moreover, pre-harvest conditions were shown to correlate with the VL loss but the correlation was too weak to produce or improve an effective estimate of the loss. The results showed that KLS performance was the best while PLS one could be acceptable; but MLR performance was not adequate. In another experiment, boxes of cut roses were transported from a Kenyan farm to a UK distribution centre. Using KLS and PLS techniques, the analysis showed that the growing temperature could be used to obtain effective estimates of the VLs at the farm, at the distribution centre and also the in-transit loss. Further, using post-harvest temperature would lead to a smaller error for the VL at the distribution centre and the VL loss. Nevertheless, the estimates of the VL loss may not be useful practically due to the excessive relative prediction error. Overall, although PLS had a slightly smaller prediction error, KLS worked effectively in many cases where PLS failed, it could handle constraints while PLS could not.In conclusion, KLS and PLS can be used to generate effective estimates of the post-harvest VL loss of cut roses based on post-harvest temperature stresses recorded by advanced sensors. However, the estimates may not be useful practically due to significant relative errors. Alternatively, pre-harvest temperature could be used although it may lead to slightly higher errors. Although PLS had slightly smaller errors KLS was more robust and flexible. Further work is recommended in the objective evaluations of product quality, alternative non-linear techniques and dynamic decision support system.

The master´s thesis describes the basic information on the reporting of water losses. Means and methods to reduce water losses. Devices used to monitoring water supply, or detect malfunctioning of water supply line. Describes and evaluates the functionality of UFR on the laboratory model.

Submitted in fulfillment of the requirements For the degree of Master of Technology: Environmental Health, Durban University of Technology, Durban, South Africa, 2016. / Work related injuries are of major public importance and have adverse economic and social impacts. Forestry work is one of the most hazardous occupations worldwide and accounts for a large proportion of occupational injuries. Employers frequently train workers in the proper and safe use of equipment, however the efficacy of these programmes are seldom rigorously evaluated. The aim of this study was to assess the effectiveness of health and safety training in reducing injuries among forestry workers in Kwa-Zulu Natal. A descriptive study was conducted among 300 Kwa-Zulu Natal harvesting contract workers. A questionnaire to assess the efficiency of health and safety training was administered. A retrospective review of the injury register and medical records of employees who sustained work related injuries, fatalities during 2009–2013 was done. The company injury data for harvesting contractors from 2009- 2013 reported 3 fatalities and 68 lost time injuries during post commencement of training. About 23.3% workers reported injuries during the study period. Slip, trip and fall injuries were the most reported cause of injuries. Almost 95% of respondents reported that they had received health and safety training at work, with 84% reporting satisfaction with the quality of training received. A decreased prevalence of work related injuries was reported post training. The health and safety program was successful in increasing workers awareness and responsibility of health and safety issues. On- going specific job training, sustained work place inspections and adult learning for supervisors will improve health and safety of workers and reduce injuries in the forestry industry. / M