General Writing

Data Science Cheat Sheet
Here is a personal (Growing) collection of concepts I consider to be important for data science and general analysis. Orginally I developed this to use when having remote job interviews for analyst roles, but found I never actually needed it.

Here are my Academic publications

Growth temperature influences postharvest glucosinolate concentrations and hydrolysis product formation in first and second cuts of rocket salad

Rocket salad species (Diplotaxis tenuifolia and Eruca sativa; also known as E. vesicaria) are known for their high concentrations of health-related isothiocyanates, which are derived from secondary metabolites called glucosinolates. Increases in temperature due to climate change and extreme weather event frequencies over the coming decades are likely to influence not only the growth of leafy vegetables, but also their nutritional density. It is therefore essential to determine the impacts of these in order to mitigate crop losses and nutritional decline in future. Our data show there is a strong influence of pre-harvest growth temperatures on glucosinolate biosynthesis and formation of glucosinolate hydrolysis products postharvest, and that this is genotype dependent. High growth temperature (40 °C) severely retarded germination, growth, regrowth, and survival of rocket plants. Highest glucosinolate concentrations were observed in first and second cuts at 40 °C, but did not correspond to highest isothiocyanate concentrations (observed at 30 °C, second cut). Hydrolysis product formation is proportionately not as great as glucosinolate increases at 40 °C, possibly due to inhibition of enzyme function(s) at higher temperatures. These data indicate that high growth temperatures increase glucosinolate accumulation, but growth and productivity is significantly reduced. Much greater emphasis is needed for breeding cultivars tolerant to high growth temperatures in order to maximise nutritional benefits imparted by temperature stress.
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Determining the quality of leafy salads: Past, present and future

The relatively high proportion of avoidable waste from leafy salads and the under-consumption of fruits and vegetables generally is contributing toward renewed interest in the value of on-pack dates, particularly those that indicate quality. Current methods of predicting shelf-life in fresh vegetables and salad are relatively conservative due to the high variability of the product and few reliable markers that can be used to predict shelf-life. This is evidenced by the proportion of wastage in this category where fresh vegetables and salad account for almost a quarter of all avoidable food waste by weight. We have looked at the historical context in which date markings have been derived, how they function currently and look at how the current system could be improved. We review the three primary factors that influence the quality of a product – microbiology, visual quality, aroma – and suggest that if more accurate predictions of shelf-life are to be obtained non-destructive methods of testing need to be developed in order to provide the consumer with accurate information about the current state of the product.
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