scholarly journals Behaviour of rainfall over lakes around Bombay

MAUSAM ◽  
2022 ◽  
Vol 46 (2) ◽  
pp. 193-198
Author(s):  
SURENDER KUMAR ◽  
S. C. BHAN
Keyword(s):  
Multiple Regression ◽  
Monthly Rainfall ◽  
The Other ◽  
Regression Equations ◽  
Lake Levels

Analysis of monthly rainfall brings out two distinctly different areas of rainfall affinity-one comprising of the lakes situated in Greater Bombay and the other in Thane districts. Rainfall of different sub-periods/months was found to be independent of the rainfall of preceding sub-periods/months. Multiple regression equations between lake levels and monthly rainfall have been computed to predict the anticipated lake levels at the end of different months.    

Correlation of the Levels of Several Constituents of Commercial Orange Juices

1968 ◽  
Vol 51 (6) ◽  
pp. 1199-1203 ◽  
Author(s):  
D E Coffin
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Multiple Regression ◽  
Correlation Coefficients ◽  
Titratable Acidity ◽  
The Other ◽  
Regression Equations

Abstract The amino acid, betaine, polyphenolics, ash, and phosphorus contents, and the titratable acidity of 32 samples of commercial orange juices and reconstituted orange juices were determined. Wide variations in the levels of these constituents were found but there were no significant differences between the juices and the reconstituted juices. Highly significant correlations were established between the levels of the amino acids, betaine, polyphenolics, ash, and phosphorus. The titratable acidity levels failed to show any significant correlation to any of the other constituents. Multiple regression equations were developed to express the interrelationships between some of the components, and correlation coefficients of combined distributions were calculated.

ESTIMATION OF WHOLESALE CUTS AND SEPARABLE LEAN OF CARCASSES FROM HOLSTEIN-FRIESIAN BULLS AND STEERS FED TO A CONSTANT FINISH

1977 ◽  
Vol 57 (4) ◽  
pp. 761-768 ◽  
Author(s):  
B. N. NTUNDE ◽  
W. R. USBORNE ◽  
G. C. ASHTON
Keyword(s):  
Multiple Regression ◽  
The Other ◽  
Carcass Weight ◽  
Backfat Thickness ◽  
Regression Equations ◽  
Estimation Equations ◽  
Holstein Bull ◽  
Holstein Friesian ◽  
Lean It

The left sides of Holstein bull and steer carcasses varying from 173 to 299 kg and finished to an average live backfat thickness of 0.76 cm were used in this study. Simple and multiple regression equations were generated for estimating the trimmed wholesale cuts and separable lean. It was found that weights were more precisely predicted than percentages. Although the longissimus was a more precise predictor than any of the other muscles, all muscle areas were poor contributors in the predictions. Backfat thickness was also a low precision predictor, especially of weights. Hot carcass weight, however, was such a useful predictor of weights that its sole effect was not significantly improved by the inclusion of any or all of the other predictors. It nevertheless gave very low precision in predicting percentages. Some selected estimation equations are recommended provided that the conditions of this study are maintained with regard to body finish and carcass weight. The advantage of using these equations is that hot carcass weight is readily obtainable.

Prediction of bone-in retail cuts and edible meat of crossbred lamb carcasses

1984 ◽  
Vol 24 (126) ◽  
pp. 344 ◽  
Author(s):  
RW Hodge ◽  
N Oddie
Keyword(s):  
Multiple Regression ◽  
Classification System ◽  
Economic Value ◽  
The Other ◽  
Carcass Weight ◽  
Similar Degree ◽  
Regression Equations ◽  
Leg Length ◽  
Percentage Yield ◽  
Retail Cuts

Multiple regression equations describing the percentage yield of bone-in retail cuts and edible meat were developed for lamb carcasses ranging in breed (lambs from Border Leicesterx Merino ewes sired by Suffolk, Southdown, Poll Dorset and Corriedale rams), sex (entire males, wethers and ewes) and carcass weight (12-25 kg). The regression equations first developed contained carcass weight as the sole predictor and these were compared with equations containing carcass weight and two additional predictors: fat depth over the 12th rib and percentage kidney and channel fat. Breed and sex, conformation score, carcass length and leg length were tested with carcass weight in separate analyses. The equations containing carcass weight and measures of fat status accounted for more of the variation in yield of retail cuts and edible meat and had lower residual standard deviations (RSD) than did equations containing the other variables. Fat depth, and percentage kidney and channel fat provided a similar degree of accuracy in predicting the percentage of retail cuts (RSD of 2.96 and 2.87 respectively) or edible meat (3.33 and 3.17 respectively). Inclusion of the quadratic terms had no significant effect on the values for RSD. The variation in fat status of 17 kg carcasses was such that the predicted yields of retail cuts or edible meat ranged from 65 to 71 % and from 49 to 55%, respectively. It was concluded that a lamb classification system need only provide objective information on carcass weight and kidney and channel fat to enable the industry to identify carcasses differing in economic value.

scholarly journals Sustainable Consumer Behavior in Purchasing, Using and Disposing of Clothes

2021 ◽  
Vol 13 (15) ◽  
pp. 8333
Author(s):  
Mirella Soyer ◽  
Koen Dittrich
Keyword(s):  
Consumer Behavior ◽  
The Netherlands ◽  
Multiple Regression ◽  
Significant Role ◽  
Social Motivation ◽  
The Other ◽  
Social Evaluation ◽  
Sustainable Practices ◽  
Usage Phase ◽  
The Core

In this study we investigate how consumers in The Netherlands can be persuaded to adopt sustainable practices when purchasing, using and disposing of clothes. This study investigates the attitude-behavior gap for the sustainable choices for purchase, use and disposing of clothes. For each consumption phase we ran a two-step multiple regression. The findings showed that the importance of the factors vary in the three consumption phases. For purchasing and disposal decisions, the core motivator social motivation predicts sustainable practices best, while it has no role in the usage phase. The factor ability appeared to have a significant role in the disposal phase, but not in the other phases. Finally, the trigger appears to lower the consumers’ ability in the purchasing phase, while it enhances the core motivator social evaluation in the disposal phase.

Estimation de la production de jeunes plantations de pin rouge et de pin gris du sud du Québec

1976 ◽  
Vol 6 (4) ◽  
pp. 478-486 ◽  
Author(s):  
H. A. Bolghari
Keyword(s):  
Multiple Regression ◽  
Jack Pine ◽  
Red Pine ◽  
Pine Plantations ◽  
Regression Equations ◽  
Pine Plantation ◽  
South Shore ◽  
Pine Stands ◽  
Natural Stands ◽  
St Lawrence River

Multiple regression equations have been developed to predict yield from young red pine and jack pine plantations. Data from 446 sample plots representing young red pine and jack pine stands located on the south shore of the St. Lawrence River between Quebec and Montreal were analysed. The red pine plantation yielded more than the jack pine. However, in plantation both species yield more than in natural stands. Taking into account the age and spacing of the sampled plantations, the equation obtained can provide information on yield of red pine and jack pine stands the maximum spacing of which is 3 × 3 m, up to the age of 45 and 35 years respectively. The equations will allow the construction of preliminary yield tables for both species.

FAT THICKNESS MEASURED WITH THREE ULTRASONIC INSTRUMENTS ON LIVE RAM LAMBS AS PREDICTORS OF CUTABILITY

1980 ◽  
Vol 60 (4) ◽  
pp. 857-867 ◽  
Author(s):  
ANDRÉ FORTIN
Keyword(s):  
Multiple Regression ◽  
Live Weight ◽  
Optimal Location ◽  
Regression Equations ◽  
Longissimus Muscle ◽  
Fat Thickness ◽  
Ram Lambs

Fat thickness at four locations over the longissimus muscle was measured ultrasonically on 33 live ram lambs ranging in live weight from 16.0 to 37.0 kg. Simple and multiple regression equations were developed to assess the effectiveness of fat thickness as measured by three different ultrasonic instruments (Krautkrämer USM #2, Scanoprobe Model 731A and Scanogram Model 722) to predict cutability. Weight of trimmed or boneless cuts (shoulder + loin + rack + leg) was predicted with more precision than percentage of cuts. Fat thickness alone or combined with weight at scanning was of no significant value (P > 0.05) in the prediction of percentage of trimmed cuts. Percentage of boneless cuts was predicted more efficiently from weight at scanning alone than from fat thickness alone or combined with weight at scanning. Weight of cuts (trimmed or boneless) was also estimated from the fat measurement (P < 0.01), the weight at scanning (P < 0.01) or a combination of both variables. For the latter, fat thickness did not contribute significantly (P > 0.05). The optimal location of the fat measurement depended on the ultrasonic instrument used. Fat thickness measured with the Krautkrämer was more efficient in its prediction of cutability than fat thickness measured with the Scanoprobe or Scanogram. However, over the range of liveweights studied, the usefulness of fat thickness measured on live ram lambs to predict cutability is questionable.

Paranormal Belief, Experience, and the Keirsey Temperament Sorter

2000 ◽  
Vol 86 (3_part_2) ◽  
pp. 1104-1106
Author(s):  
Jezz Fox ◽  
Carl Williams
Keyword(s):  
College Students ◽  
Multiple Regression ◽  
The Other ◽  
Minor Role ◽  
Regression Analyses ◽  
Keirsey Temperament Sorter ◽  
Paranormal Belief ◽  
Anomalous Experience ◽  
A Minor ◽  
Paranormal Experience

121 college students completed the Anomalous Experience Inventory and the Keirsey Temperament Sorter. Multiple regression analyses provided significant models predicting both Paranormal Experience and Belief; the main predictors were the other subscales of the Anomalous Experience Inventory with the Keirsey variables playing only a minor role.

scholarly journals Comparative Analysis of Different Spatial Interpolation Methods Applied to Monthly Rainfall as Support for Landscape Management

2021 ◽  
Vol 11 (20) ◽  
pp. 9566
Author(s):  
Tommaso Caloiero ◽  
Gaetano Pellicone ◽  
Giuseppe Modica ◽  
Ilaria Guagliardi
Keyword(s):  
New Zealand ◽  
Spatial Interpolation ◽  
Cross Validation ◽  
Landscape Management ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
The Other ◽  
Geostatistical Methods ◽  
The Cross ◽  
Almost All

Landscape management requires spatially interpolated data, whose outcomes are strictly related to models and geostatistical parameters adopted. This paper aimed to implement and compare different spatial interpolation algorithms, both geostatistical and deterministic, of rainfall data in New Zealand. The spatial interpolation techniques used to produce finer-scale monthly rainfall maps were inverse distance weighting (IDW), ordinary kriging (OK), kriging with external drift (KED), and ordinary cokriging (COK). Their performance was assessed by the cross-validation and visual examination of the produced maps. The results of the cross-validation clearly evidenced the usefulness of kriging in the spatial interpolation of rainfall data, with geostatistical methods outperforming IDW. Results from the application of different algorithms provided some insights in terms of strengths and weaknesses and the applicability of the deterministic and geostatistical methods to monthly rainfall. Based on the RMSE values, the KED showed the highest values only in April, whereas COK was the most accurate interpolator for the other 11 months. By contrast, considering the MAE, the KED showed the highest values in April, May, June and July, while the highest values have been detected for the COK in the other months. According to these results, COK has been identified as the best method for interpolating rainfall distribution in New Zealand for almost all months. Moreover, the cross-validation highlights how the COK was the interpolator with the best least bias and scatter in the cross-validation test, with the smallest errors.

EQUATIONS FOR RECIPROCAL CONVERSIONS OF STARCH EQUIVALENT AND TOTAL DIGESTIBLE NUTRIENT VALUES

1962 ◽  
Vol 42 (2) ◽  
pp. 211-214
Author(s):  
J. Kielanowski ◽  
Aleksandra Ziolecka ◽  
Zofia Osińska
Keyword(s):  
Multiple Regression ◽  
Fiber Content ◽  
Crude Fiber ◽  
Regression Equations ◽  
Crude Fiber Content ◽  
Independent Variable ◽  
Total Digestible Nutrient

In order to facilitate reciprocal conversions of Starch Equivalents (SE) and Total Digestible Nutrients (TDN) values of feeds, multiple regression equations were computed for three different groups of feeds (concentrates, green roughages and silages, and dry roughages. These equations are: for concentrates, green roughages and silages, and dry roughages, respectively.[Formula: see text]Where Y = percentage TDN, X1 = percentage SE, and X2 = percentage crude fiber and[Formula: see text]Where Y = percentage SE; X1 = percentage TDN, and X2 = percentage crude fiber.The addition of the crude fiber content as the second independent variable in each equation resulted in a slight but marked gain in accuracy, especially for green and dry roughages, when compared with simple regressions of TDN on SE or vice versa.

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