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Many factors affect the emergence and development of crop diseases and insect pests. Traditional methods for investigating this subject are often difficult to employ and produce limited data with considerable uncertainty. The purpose of this paper is to predict the annual degree of cotton spider mite infestations by employing grey theory.

The authors established a GM(1,1) model to forecast mite infestation degree based on the analysis of historical data. To improve the prediction accuracy, the authors modified the grey model using Markov chain and BP neural network analyses. The prediction accuracy of the GM(1,1), Grey-Markov chain, and Grey-BP neural network models was 84.31, 94.76, and 96.84 per cent, respectively.

Compared with the single grey forecast model, both the Grey-Markov chain model and the Grey-BP neural network model had higher forecast accuracy, and the accuracy of the latter was highest. The improved grey model can be used to predict the degree of cotton spider mite infestations with high accuracy and overcomes the shortcomings of traditional forecasting methods.

The two new models were used to estimate mite infestation degree in 2015 and 2016. The Grey-Markov chain model yielded respective values of 1.27 and 1.15, whereas the Grey-BP neural network model yielded values 1.4 and 1.68; the actual values were 1.5 and 1.8.

The improved grey model can be used for medium- and long-term predictions of the occurrence of cotton spider mites and overcomes problems caused by data singularity and fluctuation. This research method can provide a reference for the prediction of similar diseases.

Since the issuance in 2009, the digital currency has enjoyed an increasing popularity and has become one of the most important options for global investors. The purpose of this paper is to propose a hybrid model ( KDJ–Markov chain) which integrates the advantages of the stochastic index (KDJ) and grey Markov chain methods and provide a useful decision support tool for investors participating in the digital currency market.

Taking Litecoin's closing price prediction as an example, the closing prices from May 2 to June 20, 2017, are used as the training set, while those from June 21 to August 9, 2017, are used as the test set. In addition, an adaptive KDJ–Markov chain is proposed to enhance the adaptability for dynamic transaction information. And the paper verifies the effectiveness of the KDJ–Markov chain method and adaptive KDJ–Markov chain method.

The results show that the proposed methods can provide a reliable foundation for market analysis and investment decisions. Under the circumstances the accuracy of the training set and the accuracy of the test set are 76% and 78%, respectively.

This study not only solves the problems that KDJ method cannot accurately predict the next day's state and the grey Markov chain method cannot divide the states very well, but it also provides two useful decision support tools for investors to make more scientific and reasonable decisions for digital currency where there are no existing methods to analyze the fluctuation.

A new approach to analyze the fluctuation of digital currency, in which there are no existing methods, is proposed based on the stochastic index (KDJ) and grey Markov chain methods. And both of these two models have high accuracy.

Coming close upon the Report of the Symposium which considered possible toxicological dangers of cosmetics and toilet preparations, held in London last November by the European Committee on Chronic Toxicity Hazards (“Eurotox”), the decision recently announced in the Commons by the Parliamentary Secretary to the Minister of Science of the Government‐aided British Industrial Biological Research Association to undertake research to ascertain if toxic hazards exist from colouring matters used in lipsticks, is a small beginning. This prompts the question of how long before “cosmetics” will be added to “food and drugs” in this country as it was in U.S.A. in the nineteen‐thirties. At present there is practically no statutory control over the constituents used in the manufacture of these commodities, the manufacture and sale of which have increased enormously in recent years.

The pattern of food prosecutions in more recent times has remained relatively unchanged. Most have been taken under Section 2, Food and Drugs Act, 1955, even for foods which have obviously been unfit for human consumption. The Section because of its wider application has distinct procedural advantages. A few local authorities routinely use Section 8 successfully; it probably depends upon a more liberal interpretation and understanding by local justices. The five‐year study of food prosecutions, (BFJ 1971, 73, 39), separated them into a number of well‐defined groups and showed that those for the presence of foreign material were the majority and remained fairly constant throughout the period; mouldy foods increased during the five years and then remained steady as the second largest single group. The foods most commonly affected and the foreign matter commonly present could be seen; neither changed much during the period of the survey.

The brief announcement that the Government had accepted that there should be regulations on open date marking of food, to come into effect in 1975, will come as no surprise. It is a timely reminder of what public pressure can achieve these days; how sustained advocacy and publicity by interested sectors of society—magistrates, local authorities, public health workers, consumer groups—can secure legislative changes which, in this case, run counter to trade opinions and the recommendation originally made by the Food Standards Committee that such a proposal was not practical and the existing law was an adequate protection. This was stated in the FSC Report on Food Labelling of 1964, although there was no indication of the evidence reviewed or that the subject had been considered very deeply; it was, after all, only a small fraction of the problem of food labelling control. It was also stated in this Report that in certain cases, date‐stamping of food could give to purchasers a false sense of security, “not justified by the conditions under which the food has been kept since manufacture”.

The purpose of this paper is to propose a site selection method using grey system theory for a desalination plant in Libya.

In order to tackle incompleteness and imprecision of human’s judgments, grey numbers were used. This work uses a grey-based approach to represent decision makers’ comparison judgments and extent analysis method to select the best site. Therefore, a real case study of a selection problem of a site selection of desalination plant in Libya was used to illustrate the proposed approach.

Site selection in a desalination plant can be one of the most important decisions in planning a desalination project. The decision affects both the project cost and potentially the project schedule. Based on the results of grey model, a clear order of these sites and the degree of preference are obtained. This paper presents a way to improve a site selection by using a grey model, especially in a complex environment like Libya.

To the best knowledge of the authors, there is no literature for site selection using grey system theory in a desalination plant in Libya. This attempt may well enhance and facilitate the decision-making process of the best site in the country involved in this research.

A Crown Court hearing of a charge of applying a false A description under S.2, Trade Descriptions Act, 1968, is given in some detail under Legal Proceedings in this issue of BFJ. It concerns using the word “ham”, ie., the natural leg of a single pig, to various pieces from several pigs, deboned, defatted, “tumbled, massaged and cooked” in a mould shaped to a leg of ham, from which the average purchaser would find it impossible to distinguish. As the defence rightly claimed, this process has been used for at least a couple of decades, and the product forms a sizeable section of the bacon trade. Evidence by prosecution witnesses, experienced shop managers, believed the product to be the genuine “ham”. There is nothing detrimental about the meat, save that it tends to contain an excess of added water, but this applies to many meat products today; or that the manufacturers are setting out to cheat the consumer. What offends is the description given to the product. Manufacture was described in detail—a county trading standards officer inspected the process at the defendant company's Wiltshire factory, witness to the extent of their co‐operation—and was questioned at great length by defending counsel. Specimens of the product were exhibited and the jury were treated to a tasting test—presumably designed to refute prosecution's claim that the meat was of “poor value”. The trial judge said the jury had no doubt been enlightened as to the methods of manufacturing ham. The marketing of the product was also a subject of examination.

In a Northern city, which claims to have more than 12,000 Commonwealth immigrants, mostly of Asian origin—Pakistanis and Indians, an increasing number of whom have been joined by their wives and families, there was instituted in 1965 a routine examination of their children before school entry, later extended to children of immigrant origin already in the schools. This examination extended to haemoglobin estimation, tuberculin‐testing and, equally important, examination of the stools for pathogens and parasitic ova. 419 entrants were examined in the first half of 1965 and 898 pupils. Parental co‐operation must have been excellent, as parents all agreed, without exception, to the special examination, although to some extent, there might have been considered legal authority in the current School Health Service (Medical Inspection) Regulations made under the Education Act, 1944. We are not aware of any report of intestinal pathogens, but helminth infestations were reported (Archer D. M., Bamford F. N., and Lees E., Helminth Infestations in Immigrant Children, 1965, Brit. Med. J., 2, 1517), from which it appears 18·6% carried five types of worm, of which the commonest was hookworm. It would be fair to assume that helminth infestation, indicating as it does, exposure to food infections, water‐borne disease and environment generally, is an index of gastro‐intestinal infection and the presence of pathogens, including the carrier state.

The Commission appointed jointly by the World Health Organization and the Food and Agricultural Organization continues to plod its weary way towards the establishment of Codex standards for all foods, which it is hoped will eventually be adopted by all countries, to end the increasing chaos of present national standards. We have to go back to 1953, when the Sixth World Health Assembly showed signs of a stirring of international conscience at trends in food industry; and particularly expressed “the view that the increasing use of various chemical substances had … , created a new public health problem”. Joint WHO/FAO Conferences which followed initiated inter alia international consultations and the setting up of the Joint FAO/WHO Codex Alimentarius Commission.

In this chapter, drone and vision camera technology have been combined for monitoring the crop product quality. Three vegetable crops such as tomato, cauliflower, and eggplant are considered for quality monitoring; hence, image datasets are collected for those vegetables only. The proposed method classified the vegetables into two classes as rotten and nonrotten products so the images were collected for rotten and nonrotten products. Three different features information such as chromatic features, contour features, and texture features have been extracted from the dataset and further used to train a Gaussian kernel support vector machine algorithm for identifying the product quality. The system utilized multiple features such as chromatic, contour, and texture features in classifier training which enhances the accuracy and robustness of the system. Chromatic features were utilized for detecting the crop while other features such as contour and texture features were utilized for further classifier building to identify the crop product quality. The performance of the system is evaluated based on the true positive rate, false discovery rate, positive predictive value, and accuracy. The proposed system identified good and bad products with a 97.9% of true positive rate, 2.43 % of false discovery rate, 97.73% positive predictive value, and 95.4% of accuracy. The achieved results concluded that the results are lucrative and the proposed system is efficient in agriculture product quality monitoring.