Multivariate Analysis, Description, and Ecological Interpretation of Weed Vegetation in the Summer Crop Fields of Anhui Province, China

Multivariate analysis through Two Way Indicator Species Analysis (TWINSPAN) was conducted to study the phytosociological attributes of weeds of some selected crop fields of chickpea, mustard and wheat of Tehsil Isa Khel, District Mianwali, Punjab. Forty one (41) weed species were collected from the study area belonging to twenty one (21) different families. Twenty four weed species found in chickpea, twenty five in mustard and twenty nine in wheat crop fields. Sixteen weed species were common in three crops. Family Poaceae and Astraceae had maximum weed species i.e. 7 and 6 species respectively followed by Euphorbiaceae, Fabaceae, Chenopodiaceae, Papaveraceae, Zygophyllaceae and so on. Asphodelus tenuifolius, Medicago monantha and Carthamus oxycantha are frequently occurring weeds relative to others. Two-Way Indicator Species Analysis (TWINSPAN) was performed on the percentage cover basis which divided the weed species into groups, sub groups, associations and sub associations.

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Use of Pheromone Traps to Monitor Population Fluctuations of Cotton Leafworm Moth and Their Transmission in Winter and Summer Crop Fields

Egyptian Academic Journal of Biological Sciences F Toxicology & Pest Control ◽

10.21608/eajbsf.2021.142439 ◽

2021 ◽

Vol 13 (1) ◽

pp. 53-64

Author(s):

Barrania, Ahmed ◽

Shady Selim

Keyword(s):

Pheromone Traps ◽

Population Fluctuations ◽

Cotton Leafworm ◽

Crop Fields ◽

Summer Crop

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Statistical analysis of classification

Symposium - International Astronomical Union ◽

10.1017/s0074180900053420 ◽

1966 ◽

Vol 24 ◽

pp. 188-189

Author(s):

T. J. Deeming

Keyword(s):

Multivariate Analysis ◽

Statistical Analysis ◽

Classification Scheme ◽

Analytical Procedure ◽

Narrow Band ◽

Scientific Research ◽

Maximum Amount ◽

Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

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