Philip D. Hollins

Grain quality in the Broadbalk Wheat Experiment and the winter North Atlantic Oscillation

SUMMARY Previous work has shown that the national average quality of the UK wheat crop from 1974 to 1999 was associated with the preceding winter North Atlantic Oscillation (NAO). The association of the winter NAO with the grain quality measure, specific weight, was shown to be mediated by sunshine duration during grain filling and unconditional wet day probability during grain ripening (the probability of a wet day following either a dry or a wet day). The present study tests the hypothesis that the association between specific weight and the winter NAO can be detected in data from 158 years of the Broadbalk Wheat Experiment at Rothamsted in south-east England. Specific weight from the Broadbalk Experiment responded to sunshine duration during grain filling and unconditional wet day probability during grain ripening in a similar way to the national average data. An association with the winter NAO was found in the Broadbalk data from 1956 to 2001, but not in the previous 112 years (1844–1955). This finding is consistent with other work showing significant correlations between the winter NAO and summer climate only in recent decades. It is concluded that the association between wheat quality and the NAO is a recent phenomenon.

Relationships between climate and winter cereal grain quality in Finland and their potential for forecasting

Many studies have demonstrated the effects of climate on cereal yield, but there has been little work carried out examining the relationships between climate and cereal grain quality on a national scale. In this study national mean hectolitre weight for both rye and winter wheat in Finland was modelled using monthly gridded accumulated snow depth, precipitation rate, solar radiation and temperature over the period 1971 to 2001. Variables with significant relationships in correlation analysis both before and after difference detrending were further investigated using forward stepwise regression. For rye, March snow depth, and June and July solar radiation accounted for 66% of the year-to-year variance in hectolitre weight, and for winter wheat January snow depth, June solar radiation and August temperature accounted for 62% of the interannual variance in hectolitre weight. Further analysis of national variety trials and weather station data was used to support proposed biological mechanisms. Finally a cross validation technique was used to test forecast models with those variables available by early July by making predictions of above or below the mean hectolitre weight. Analysis of the contingency tables for these predictions indicated that national hectolitre weight forecasts are feasible for both cereals in advance of harvest.

The impact of supply, demand and grain quality on the UK bread and feed wheat price differential in the UK

The difference between the bread wheat and feed wheat prices in the UK (the premium) is an important influence on behaviour throughout the entire grain chain. The aim of the present study was to quantify the influence of grain quality and other factors on interannual variation in the premium calculated as a proportion of the feed price. A hypothetical model of the UK wheat economy was devised, appropriate annual national data from 1982 to 2000 were collected for each component and multiple regression was used to develop a statistical model for the premium. The statistical model included livestock numbers (calculated as pig equivalents), Hagberg falling number and wheat stocks, which together explained 0·80 of the interannual variation in the premium. A high premium was associated with high livestock numbers, low Hagberg falling number and low wheat stocks. These variables were included in the hypothetical model because: livestock numbers represent demand for feed wheat; Hagberg falling number is a quality criterion for purchase of bread wheat with a low value indicating poor quality and thus a smaller supply of bread wheat; wheat stocks are one of the sources of supply of wheat. It was concluded that of the 16 supply, demand or price variables in the hypothetical model the main variables associated with the premium from 1982 to 2000 were demand for feed wheat, quality of the wheat harvest and carry-over of wheat from the previous harvest.

Identifying Determinants of Residential Property Values in South London

Identifying Determinants of Residential Property Values in South London This paper advances the academic work conducted on identifying some of the determinants of residential property values in different countries. Such determinants might include positive factors such as access to amenities, or negative factors such as high voltage overhead transmission lines (HVOTL). The objective explored here is to extend this research in the UK by considering the particular case of residential property values in South London. A number of determinants is considered, grouped and a model which explains the effect of the determinants on value is produced. The elasticities between property values and the distances from different determinants were also analysed to help highlight relationships between the determinants and residential property values. The results showed a relationship between residential property values and the determinants, and a relationship between the determinants themselves.