This document provides information about wheat milling and wheat flour production. It discusses the milling process which uses plansifters and purifiers to separate wheat into bran, germ, and endosperm. It describes how roller mills are used to further grind the endosperm into different grades of flour based on extraction rate. The document also covers composition changes during milling, permitted flour treatments, and applications of air-classified wheat flour.
This document discusses the milling process and products of wheat. It begins by describing the different types of wheat used for milling. The traditional and modern milling processes are then outlined, including steps like cleaning, conditioning, breaking, sifting, and purifying. The document also provides a table comparing the nutrient composition of whole grains versus bran, endosperm, and germ. Finally, it lists and describes various primary and secondary wheat products obtained from milling, such as flour, semolina, bran, cracked wheat, bulgur, and vermicelli.
1. Grain quality factors like test weight, foreign material, broken kernels, and moisture content can impact the value of grain for both trade and animal feeding.
2. Test weight alone has little effect on animal performance if animals can meet their energy needs, but impacts value when grain is sold by volume. Foreign material depends on what it is but can reduce storage quality.
3. Both physical and chemical analyses are important for evaluating grain quality factors and potential issues like mycotoxins that impact animal health and performance. Maintaining proper storage conditions is key to preserving grain quality.
This document provides an overview of rice processing technology. It discusses the different parts of a rice grain and the milling process. Rice milling can be done in one, two, or multiple steps to remove the husk and bran. Modern rice mills are highly efficient though capital intensive. Parboiled rice involves soaking, steaming, and drying rice to gelatinize the starch before milling. Byproducts of rice processing like rice bran and husk can be utilized. Strict food safety and employee training programs are needed when processing rice. The global market for parboiled rice is growing due to its nutritional properties. Proper rice milling and processing is important for making rice available and extending its shelf life.
النظام الفعال للرقابة على الأغذية في ليبيا هو أمر ضروري لحماية صحة المستهلك وضمان سلامته.
وهذا النظام أيضاً حاسم في تمكين المجتمع من ضمان سلامة وجودة الأغذية التي تدخل التجارة الدولية وضمان اتفاق الأغذية المستوردة مع الاشتراطات الوطنية.
The document discusses the process of beer production which involves several steps: (1) malting of barley grains, (2) milling of malt, (3) mashing to extract sugars, (4) separating wort, (5) boiling wort, (6) cooling wort, (7) fermenting wort into beer, (8) conditioning beer, (9) filtering beer, and (10) packaging beer. It provides details on the malting process and the role of malt in beer production.
This document provides information about wheat milling and wheat flour production. It discusses the milling process which uses plansifters and purifiers to separate wheat into bran, germ, and endosperm. It describes how roller mills are used to further grind the endosperm into different grades of flour based on extraction rate. The document also covers composition changes during milling, permitted flour treatments, and applications of air-classified wheat flour.
This document discusses the milling process and products of wheat. It begins by describing the different types of wheat used for milling. The traditional and modern milling processes are then outlined, including steps like cleaning, conditioning, breaking, sifting, and purifying. The document also provides a table comparing the nutrient composition of whole grains versus bran, endosperm, and germ. Finally, it lists and describes various primary and secondary wheat products obtained from milling, such as flour, semolina, bran, cracked wheat, bulgur, and vermicelli.
1. Grain quality factors like test weight, foreign material, broken kernels, and moisture content can impact the value of grain for both trade and animal feeding.
2. Test weight alone has little effect on animal performance if animals can meet their energy needs, but impacts value when grain is sold by volume. Foreign material depends on what it is but can reduce storage quality.
3. Both physical and chemical analyses are important for evaluating grain quality factors and potential issues like mycotoxins that impact animal health and performance. Maintaining proper storage conditions is key to preserving grain quality.
This document provides an overview of rice processing technology. It discusses the different parts of a rice grain and the milling process. Rice milling can be done in one, two, or multiple steps to remove the husk and bran. Modern rice mills are highly efficient though capital intensive. Parboiled rice involves soaking, steaming, and drying rice to gelatinize the starch before milling. Byproducts of rice processing like rice bran and husk can be utilized. Strict food safety and employee training programs are needed when processing rice. The global market for parboiled rice is growing due to its nutritional properties. Proper rice milling and processing is important for making rice available and extending its shelf life.
النظام الفعال للرقابة على الأغذية في ليبيا هو أمر ضروري لحماية صحة المستهلك وضمان سلامته.
وهذا النظام أيضاً حاسم في تمكين المجتمع من ضمان سلامة وجودة الأغذية التي تدخل التجارة الدولية وضمان اتفاق الأغذية المستوردة مع الاشتراطات الوطنية.
The document discusses the process of beer production which involves several steps: (1) malting of barley grains, (2) milling of malt, (3) mashing to extract sugars, (4) separating wort, (5) boiling wort, (6) cooling wort, (7) fermenting wort into beer, (8) conditioning beer, (9) filtering beer, and (10) packaging beer. It provides details on the malting process and the role of malt in beer production.
This document discusses experimental design techniques for studying the effects of multiple factors on a response. It provides examples of one-factor-at-a-time experiments and multi-factor experiments. For a study examining the effects of temperature and pH on bacterial growth, a multi-factor design would be necessary to detect any interaction between the two factors. The document also describes 2k factorial designs, coding factors, design matrices, calculating effects estimates, and fitting models to experimental data.
This document discusses principles of experimental design. It covers the aims of experiments including developing new products or processes or improving existing ones. It discusses types of experiments and defines DOE (design of experiments). It outlines the phases of experimental design including treatment design, experiment design, and analysis design. It provides examples of treatment design objectives like screening, quantifying, optimization, and theory. It also discusses concepts like one-variable and two-way factorial experiments, experimental units, replicates, randomization, and analysis of variance.
This document discusses correlation and regression analysis. It defines scatter plots as graphs of independent (X) and dependent (Y) variable pairs that can show positive, negative, or no relationships between variables. The correlation coefficient measures the strength and direction of relationships, ranging from -1 to 1. A value of 0 indicates no linear relationship. Formulas are provided to compute the sample correlation coefficient and conduct a t-test to determine if a correlation is statistically significant. Examples demonstrate these concepts using data on wheat hardness and damage starch.
This document provides an overview of chi-square procedures for testing goodness of fit and independence using categorical data. It defines chi-square tests and presents examples to test if frequency distributions fit specific patterns or if two variables are independent. The examples show calculating expected frequencies, test statistics, degrees of freedom, and making decisions to reject or fail to reject the null hypothesis based on comparing test statistics to critical values at a given significance level.
This document provides an overview of analysis of variance (ANOVA), including:
- ANOVA is used to compare means of three or more populations using an F-test. It assumes normal distributions, independence, and equal variances.
- Between-group and within-group variances are calculated to determine the F-value. If F exceeds the critical value, the null hypothesis of equal means is rejected.
- Two-way ANOVA extends the technique to analyze two independent variables and their interaction effects on a dependent variable. Graphs can show interactions like disordinal, ordinal, or no interaction.
Ch6 Testing the Difference between Means, VariancesFarhan Alfin
The document discusses various statistical tests for comparing means and variances between two populations or groups. It provides formulas and examples for:
1. Testing the difference between two means with large independent samples using the z-test. This assumes normal distributions and known or large sample sizes.
2. Testing differences between two means with small independent samples using a t-test. This allows for unknown and unequal variances between populations.
3. Testing differences between two variances using an F-test, which compares the ratio of the two sample variances to an F distribution.
4. Calculating confidence intervals for the difference between two means with large or small independent samples.
1) Hypothesis testing involves specifying a null hypothesis (H0) and an alternative hypothesis (H1). The null hypothesis states that there is no difference or relationship, while the alternative hypothesis specifies a difference or relationship.
2) A statistical test is used to determine whether to reject the null hypothesis based on sample data. There is a risk of making Type I or Type II errors.
3) The p-value represents the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true.
This document discusses key concepts in statistics for engineers and scientists such as point estimates, properties of good estimators, confidence intervals, and the t-distribution. A point estimate is a single numerical value used to estimate a population parameter from a sample. A good estimator must be unbiased, consistent, and relatively efficient. A confidence interval provides a range of values that is likely to contain the true population parameter based on the sample data and confidence level. The t-distribution is similar to the normal distribution but has greater variance and depends on degrees of freedom. Examples are provided to demonstrate how to calculate confidence intervals for means using the normal and t-distributions.
Ch3 Probability and The Normal Distribution Farhan Alfin
This document provides an introduction to probability and the normal distribution. It defines probability as the chance of an event occurring, and discusses empirical probability determined by observation. It introduces the normal distribution and its key properties including that it is symmetric and bell-shaped. The document also discusses calculating probabilities and areas under the standard normal curve, including between and outside given z-values.
This document provides an overview of key concepts in statistics for engineers and scientists. It discusses parameters and statistics, which are characteristics of populations and samples respectively. It then covers various measures of central tendency (mean, median, mode) and how to calculate them. It also discusses measures of variability such as range, variance, standard deviation, and coefficient of variation. Various distribution shapes are presented. Examples are provided to demonstrate calculating statistics like the mean, median, variance and coefficient of variation. The document aims to describe fundamental statistical concepts and calculations.
This document provides an introduction to statistics. It defines key statistical concepts such as descriptive statistics, inferential statistics, populations, samples, variables, and different types of data. It also discusses methods for organizing and summarizing data, including frequency distributions, histograms, frequency polygons, ogives, time series graphs and pie charts. The goal of statistics is to collect, organize, analyze and draw conclusions from data.
