Regression model relating decortication of oilseed sunflower hybrids with achene characteristics

1993 ◽  
Vol 73 (3) ◽  
pp. 825-828 ◽  
Author(s):  
Walter Dedio
Keyword(s):  
Regression Model ◽  
Key Words ◽  
Multiple Regression ◽  
Oil Content ◽  
Good Prediction ◽  
Regression Equations ◽  
Hull Content ◽  
Wax Content

Multiple regression equations relating decortication with such achene characteristics as oil content, achene weight and density, in three sets of oilseed sunflowers were developed. Hull content and wax content were included in one set of hybrids. Good prediction of decortication could be obtained from the achene characteristics that are routinely determined, i.e., oil content, achene weight and density. Oil content was the most significant factor, followed by achene density. Key words: Decortication, sunflower

Heterosis and prediction of achene oil content in sunflower hybrids from parental lines

1993 ◽  
Vol 73 (3) ◽  
pp. 737-742 ◽  
Author(s):  
Walter Dedio
Keyword(s):  
Key Words ◽  
Helianthus Annuus ◽  
Multiple Regression ◽  
Oil Content ◽  
Regression Equations ◽  
Helianthus Annuus L ◽  
Kernel Oil ◽  
Oil Components ◽  
Parental Lines ◽  
Kernel Content

Oil content of the sunflower achene is determined by its components, namely kernel content and kernel oil content. The object of this study was to determine the heterosis and relative contributions of the parents to the achene oil, kernel oil and kernel content of the hybrid. Multiple regression equations showed that the two parents contribute equally to the achene oil content of the hybrids. Heterosis was observed in the kernel oil content and kernel content as well as the achene oil content. A heterotic effect of 47 g kg−1 over the mid-parent value was observed for achene oil content. For the achene oil components, heterotic effect of 44 g kg−1 was obtained for kernel oil content and 24 g kg−1 higher for kernel content. Key words: Sunflower, achene oil content, kernel oil content, kernel content, Helianthus annuus L., heterosis

scholarly journals Analisis Faktor-Faktor yang Berpengaruh terhadap Tingkat Keberhasilan pada Perusahaan-Perusahaan Dagang di Kotamadya Banjarmasin

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Muhammad Rudiansyah
Keyword(s):  
Regression Model ◽  
Key Words ◽  
Profit Margin ◽  
Dominant Factor ◽  
Analysis Tool ◽  
Regression Equations ◽  
Working Capital

This research is aimed to analize to factors that success of business. The factors analize in the research are; X1 (net selling), X2 (cost expense), X3 (working capital), X4 (gross profit), X5 (profit margin), X6 (total assets), dan X7 (turnover assets). The analysis tool that is used in the research is the multiple linier regression model, regression equations that show the variables X1 , X2 , X3 , X4 , X5 , X6 simultaneously give sinigficant afferst to variable Y. This is show in the test F result calculation (2,897) is higher than the table F (2,17), and its probability value (1.778E-9) is lower the value of alfa ( ? = 0,05) While the dominant factor that affects sucsess of business is the profit margin (X5).Key words; net selling, cost expense, working capita), gross profit, profit margin, total assets, turnover assets.

scholarly journals PENGARUH KEPUASAN KERJA, MOTIVASI, DAN PERSEPSI ATAS DUKUNGAN ORGANISASIONAL TERHADAP KOMITMEN ORGANISASI GURU TAMAN KANAKKANAK DI KECAMATAN SANDEN, KABUPATEN BANTUL, YOGYAKARTA

2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Agustin Eka Nurhayati
Keyword(s):  
Job Satisfaction ◽  
Organizational Commitment ◽  
Regression Model ◽  
Key Words ◽  
Multiple Regression ◽  
Organizational Support ◽  
Perceived Organizational Support ◽  
Multiple Regression Model ◽  
Kindergarten Teachers ◽  
Survey Method

The objective of this study was to explore the influence of job satisfaction, motivation and perceived organizational support on organizational commitment of kindergarten teachers in Sanden, Bantul, Yogyakarta.This research used quantitative approach with survey method in which questionnaire was used to gather the data. The main data of this research were gained from 85 respondents. In this research, multiple regression was used to analyze the data to know the influence of job satisfaction, motivation, and perceived organizational support on organizational commitment. The multiple regression model Y=0,401X1+0,332X2+0,099X3, showed that the job satisfaction influenced positively on organizational commitmentof kindergarten teachers (0,401). Motivation also influenced positively on organizational commitmentof kindergarten teachers (0,332). It was also found that perceived organizational support not influenced positively on organizational commitment (0,099). Key words: job satisfaction, motivation, perceived organizational support, organizational commitment.

scholarly journals Development Of Statistical Techniques For The Forecasting Of Nor’westers And Associated Maximum Gusty Wind And Rainfall Over Bangladesh

1970 ◽  
Vol 35 (2) ◽  
pp. 125-140 ◽  
Author(s):  
Samarendra Karmakar ◽  
Md Mahbub Alam
Keyword(s):  
Wind Speed ◽  
Linear Regression ◽  
Key Words ◽  
Multiple Regression ◽  
Statistical Prediction ◽  
Statistical Techniques ◽  
Regression Equations ◽  
Simple Linear Regression ◽  
Maximum Rainfall ◽  
Linear Multiple Regression

The forecasting techniques for the prediction of nor’westers and associated winds and rainfall have been developed. Four linear multiple regression equations for computation of maximum gusty wind speed associated with nor’westers have been developed. The computed values of maximum gusty wind speed have statistically significant correlation with the actual maximum gusty wind speed. The regression equations have been verified with data of year (2005) and will be useful for the operational meteorologists for the computations of maximum gusty wind speed associated with nor’westers. Simple linear regression equations and linear multiple regression equations have also been developed for the statistical prediction of 24 hrs rainfall over Dhaka, country-averaged 24 hrs rainfall over Bangladesh and 24 hrs maximum rainfall over Bangladesh due to nor’westers. The correlation co-efficient corresponding to these regression equations are statistically significant. These equations have also been verified with the data of year 2005. Key words: Statistical techniques; Forecasting; Nor'westers; BangladeshDOI: http://dx.doi.org/10.3329/jbas.v35i2.9416 JBAS 2011; 35(2): 125-140

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.

Factors Affecting NPAs in Indian Banking Sector

Paradigm ◽  
2021 ◽  
Vol 25 (2) ◽  
pp. 181-193
Author(s):  
Nitya Garg
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Banking Sector ◽  
Relative Weight ◽  
Multiple Regression Model ◽  
Factors Affecting ◽  
Weight Analysis ◽  
Specific Factors ◽  
Relative Weight Analysis ◽  
Bank Specific Factors

Banking sector is the backbone of any economy, so it is necessary to focus on its performance which is largely affected by its non-performing assets (NPAs). In the year 2018–2019, NPA of scheduled banks was Rs 355,076 Crore which is 3.7% of net advances. The purpose of this study is to identify the determinants based on analysis from previous literatures, and majorly macroeconomic and bank specific factors which are affecting NPAs using the relative weight analysis and to frame a model to predict future NPAs using multiple regression model using SPSS. The study also attempts to focus on actions and remedies that banks should make to control future NPAs. Findings of the study will act as a scaffolding for financial analysts and policymakers to prevent the conversion of its performing assets into NPAs and also help in proper management of banks and also in the recovery of economy.

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.

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