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Botany & Herbal Manufacturing - Module 1.2

Kingdoms of Life:

Kingdom Monera - Single-cell organisms/Bacteria

Kingdom Protista - Algae

Kingdom Fungi - Fungi

Kingdom Plantae - Plants

Kingdom Animalia - Animals, inc. humans

Taxonomical Classifications:

Kingdom

Phylum/Division

Class

Order

Family

Genus

Species Phylums of Kingdom Plantae:

Hepaticophyta (Liverworts)

Bryophyta (Liverworts, mosses)

Psilophyta (Whiskferns)

Lycophyta (Club mosses)

Equisetophyta (Horsetails)

Pterophyta (Ferns)

Coniferophyta (Conifers)

Gymnosperm (fruitless)

Male and female cones on same plant

Cycadophyta (Cycads)

Gymnosperm

Male and female cones on different plants

Ginkgophyta (Ginkgo)

Gymnosperm

Only one species in this phylum

Ginkgo biloba

Magnoliophyta/Anthophyta (Flowering plants)

Angiosperm (seeds enclosed in fruit)

Botanical Nomenclature:

Generic name (Genus) always has a capital letter

Specific epithet (species) always uncapitalised

Entire latin name is always italicised (underlined if handwritten)

Eg. Mentha piperita (Peppermint).

Herb Regulation in Australia:

TGA (Therapeutic Goods Administration)

GMP (Good Manufacturing Practice)

SUSMP (Standard for the Uniform Scheduling of Medicines and Poisons)

ARTG (Australian Register of Therapeutic Goods)

Suspensions - Advantages:

High absorption rate

No additives or excipients

Relatively cheap

Long shelf life

Lack of alcohol

Suspensions - Disadvantages:

Taste

Dosage measurement can be problematic

Compliance can be low

Few herbs are effectively administered this way

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Botany & Herbal Manufacturing Module 1.1

Botany - The scientific study of the physiology, structure, genetics, ecology, distribution, classification, and economic importance of plants.

Harvesting Techniques:

Check for local pollution, insect damage, yellowed leaves.

Season: Each plant has an optimal picking time. Leaves are best harvested in spring. Late spring to summer is the best time for barks and flowers. Autumn is the best time for roots.

Time of day

Moon phase

Weather: Avoid harvesting on rainy days, particularly when harvesting oily plants.

Modern Wildcrafting:

Stewardship

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Identification

Quality assessment

Preparation

Organoleptic Testing: Using sight, smell, taste, and touch

In order to assess the quality of herbs and plants.

Drying herbs prolongs the life of the herb and reduces up to 90% of bulk. It should take place immediately after harvesting. Woody herbs may be hung but it is not recommended for more delicate herbs with a high moisture content.

Powders - Advantages:

Total contituents of a herb are presented to the digestive tract, rather than only those that dissolve in a solvent.

Powders - Disadvantages:

Reduced shelf life

Can be difficult to swallow

Unpalatable to some

Poor digestion is contraindicated

Pills/Capsules - Advantages

Convenient

Bypass bitterness or other unpleasant tastes

Alternative to tinctures

Can be enteric coated

Ensures accurate delivery

Pills/Capsules - Disadvantages

Constituents may be lost in processing

Not absorbed as readily as liquids

Contain excipients

Fixed amounts reduce flexibility for individual prescribing

Relatively low dose per capsule

Labelling:

Name of the medicine

Dosage and directions

Client name

Amount dispensed

W:V concentration

Expiry date and date dispensed

Warnings or cautions

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EBP Week Nine: Descriptive and Inferential Statistics

Quantitative data vs. Qualitative data:

Quantitative data is expressed in numbers

Qualitative data is expressed in language

Data can be either discrete or continuous. Discrete data can be further categorised as nominal and ordinal data:

Nominal data: Data that can be categorised

Ordinal data: Data that can be categorised and ranked

Continuous data can be further categorised as interval and ratio data:

Interval data: Data that can be categorised and ranked, and has equal, evenly spaced intervals 

Ratio data: Data that can be categorised, ranked, has equal & evenly spaced intervals, and is compared to or has a true zero (eg. weight)

Table 1: Visual representation of types of data.

Range: Difference between the highest and lowest values

Percentiles and interquartile range: Data is split into quarters or more, and range is calculated within each quarter individually

Average deviation about the mean: Calculated by subtracting the mean from each score, then summing the individual deviations, and dividing by n

Variance: Sum of the squared deviations about the mean divided by the number of cases

Standard deviation: Square root of the variance, which reflects the spread or frequency distribution representative of the data

Normal Distribution:

Also called a Gaussian curve, normal distribution applies to continuous data only. When data is distributed along a bell-shaped frequency polygon and symmetrical about a mean, we can transform raw data into z-scores (standard scores) by transforming a measurement based on its distance from the mean in standard deviations. Z-scores represent how many standard deviations a given raw score is above or below a mean.

On a normal curve, the mode, median and mean should all fall in the middle of the curve. When the median, mode and mean fall in places other than the middle, we can say the data is skewed (see figure 1)

Figure 1: Normal curve vs. Skewed curves

Various methods can be used based on the type of data collected to express central tendency and variability.

For nominal data, the mode may be used (The mode may also be used for ordinal and continuous data). 

For ordinal data, the median and interquartile range must be used.

For continuous data that is normally distributed, the mean and standard deviation must be used.

For continuous data that has a skewed distribution, the median and interquartile range must be used (Authors should report the distribution of continuous data)

Inferential statistics are used to investigate whether an association exists between two or more variables (correlation/regression), whether there is a difference between groups (hypothesis testing), and whether conclusions can be drawn about the population from the sample.

Correlation is measured in r values, which range from -1 to +1 (where 0 = no correlation, -1 = perfect negative correlation, and +1 = perfect positive correlation). A high r value indicates a high degree of correlation, but not necessarily causation

Criteria for causation is as follows:

The cause must precede the effect

The cause and effect co-vary

If the cause does not occur, neither does the effect

P values refer to the likelihood that a finding could have occurred by chance. Statistical significance is usually set at p<0.05. The closer to 0 the p value is, the more likely the finding could not have occurred by chance.

The confidence interval (CI) describes the range of scored which includes the true population parameter at a specified level of probability. The confidence interval is usually set at 95%  or 99%

H0 (Null hypothesis) - Any differences in the data between one group and another were due to chance alone (IV had no effect on DV)

HA (Alternate hypothesis) - The results are real (the IV influenced the DV)

Alpha (Level of significance) - The probability level at which the null hypothesis is rejected (Usually set at 0.05, but occasionally set at 0.01)

A type I error occurs when rejecting a null hypothesis which is true (ie. thinking there is an effect when there is none)

A type II error occurs when failing to reject a false null hypothesis (ie. thinking there’s no effect when there is)