scholarly journals PHENOLOGY OF Calotropis procera (Ait.) W.T. Aiton ACCESSIONS BASED ON MORPHOPHYSIOLOGICAL CHARACTERISTICS

2019 ◽  
Vol 32 (2) ◽  
pp. 543-551
Author(s):  
ISAIAS VITORINO BATISTA DE ALMEIDA ◽  
MAÍLSON MONTEIRO DO RÊGO ◽  
FABIANE RABELO DA COSTA BATISTA ◽  
ELIZANILDA RAMALHO DO RÊGO ◽  
RISELANE DE LUCENA ALCÂNTARA BRUNO
Keyword(s):  
Regression Models ◽  
Soil Analysis ◽  
Germplasm Collection ◽  
Northeastern Brazil ◽  
Coefficient Of Determination ◽  
Calotropis Procera ◽  
Soil Fertilization ◽  
Physiological Indexes ◽  
Beginning Of Flowering ◽  
Selection Of

ABSTRACT The objective of this work was to evaluate the phenology of Calotropis procera accessions based on morphophysiological characteristics. Seeds of 70 C. procera accessions were collected between October 2015 and January 2016 in areas where the species naturally occurs in Northeastern Brazil. These accessions make up the current germplasm collection of the National Institute of the Semi-arid (INSA). The experiment was conducted in a greenhouse at INSA, in Campina Grande - PB, from January to September in 2016. The plants were cultivated in plastic pots filled with soil. Fertilization was conducted according to soil analysis recommendations and plants were irrigated at a 3-day interval. Morphophysiological characteristics were recorded 30 days after sowing (DAS) and 30-day intercalated evaluations were conducted up to 240 DAS. In addition, physiological indexes were estimated and leaf fall, flowering, and fruiting were evaluated at 120 DAS. Mean of each characteristic was obtained using the adjustment and the selection of regression models to explain the growth of C. procera based on the coefficient of determination. The vegetative stage of C. procera occurs during the 240 DAS, with continuous fall and production of leaves, while the reproductive stage begins at 153 DAS, continuing until 222 DAS, depending on the accession, making emission of inflorescences constant on plants after the beginning of flowering. The physiological indexes are efficient to estimate the growth of C. procera accessions.

Optimizing age at first use of semen for higher fertilityin Sahiwal breeding bulls

2016 ◽  
Author(s):  
B. C. Naha ◽  
A. K. Chakravarty ◽  
M. A. Mir ◽  
M. Bhakat
Keyword(s):  
Comparative Evaluation ◽  
Regression Models ◽  
Information Criterion ◽  
Conception Rate ◽  
Coefficient Of Determination ◽  
Progeny Testing ◽  
Testing Programme ◽  
Multiple Regression Models ◽  
Improvement Programme ◽  
Selection Of

The objective of the study was to optimise the age at first use (AAFU) of semen in Sahiwal breeding bulls which will help in early selection of bulls under progeny testing programme. The data on AAFU, conception rate based on first A.I. (CRFAI), overall conception rate (OCR) and birth weight (B.WT) of 43 Sahiwal bulls during 1987 to 2013 at NDRI centre pertaining to 8 sets of Sahiwal improvement programme at ICAR-NDRI, Karnal, India were adjusted for significant environmental influences and subsequently analyzed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Comparative evaluation of three developed models (I to III) have showed that Model III, having AAFU and B.WT which fulfill the accuracy of model as revealed by high coefficient of determination, low mean sum of square to due error, low conceptual predictive value and low Bayesian information criterion . The results showed that average predicted CRFAI was highest (49.34%) at less than 5 years and lowest (44.79%) at > 6 years of age at first A.I. /use. Similarly average predicted OCR was highest (48.50%) at less than 5 years and lowest (44.56%) at >6 years of age at first A.I. / use of Sahiwal bulls. In organized herd under progeny testing programme, Sahiwal bulls should be used prior to 5 years which is expected to result in 4.45% better CRFAI and 3.94% better OCR in comparison to Sahiwal bulls used after 6 years of age.

Optimum age at first semen freezing in relation to fertility of Sahiwal breeding bulls

2018 ◽  
Author(s):  
B. C. Naha ◽  
A. K. Chakravarty ◽  
M. A. Mir ◽  
M. Bhakat ◽  
Ramendra Das ◽  
...  
Keyword(s):  
Birth Weight ◽  
Regression Models ◽  
Dairy Herd ◽  
Information Criterion ◽  
Conception Rate ◽  
Coefficient Of Determination ◽  
National Dairy Research Institute ◽  
Multiple Regression Models ◽  
Improvement Programme ◽  
Selection Of

Early selection of bulls having optimum age at first semen freezing play an important role in improving reproductive performance in a dairy herd. Twenty seven years data (1987-2013) on age at first semen freezing (AAFSF), conception rate based on first A.I. (CRFAI) , overall conception rate (OCR) and birth weight (B.WT) of 41 Sahiwal bulls belonging to 8 sets of Sahiwal improvement programme at ICAR-National Dairy Research Institute, Karnal, Haryana, India; were adjusted against environmental effects and subsequently analysed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Among the three developed models (I to III), it was observed that Model III having age at first semen freezing and birth weight fulfil the accuracy of model i.e.; having high coefficient of determination (R2) value (CRFAI = 67% and OCR= 69%), low mean error sum of square (MSSe), low conceptual predictive value (CP value) and low Bayesian information criterion (BIC). The results revealed that optimum age at first semen freezing of Sahiwal bulls should be 2.5 - 3.0 years for 3.10% higher conception rate based on first A.I. (48.86%) and 4.39% higher overall conception rate (48.78%) in comparison to Sahiwal bulls with more than 3.5 years of age (CRFAI :- 45.76% and OCR :- 44.39%).

scholarly journals Genetic diversity and population structure of ridge gourd (Luffa acutangula) accessions in a Thailand collection using SNP markers

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Grimar Abdiel Perez ◽  
Pumipat Tongyoo ◽  
Julapark Chunwongse ◽  
Hans de Jong ◽  
Anucha Wongpraneekul ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Germplasm Collection ◽  
Snp Markers ◽  
Fixation Index ◽  
Breeding Programs ◽  
Total Fixation ◽  
Unrooted Phylogenetic Tree ◽  
Luffa Acutangula ◽  
Selection Of

AbstractThis study explored a germplasm collection consisting of 112 Luffa acutangula (ridge gourd) accessions, mainly from Thailand. A total of 2834 SNPs were used to establish population structure and underlying genetic diversity while exploring the fruit characteristics together with genetic information which would help in the selection of parental lines for a breeding program. The study found that the average polymorphism information content value of 0.288 which indicates a moderate genetic diversity for this L. acutangula germplasm. STRUCTURE analysis (ΔK at K = 6) allowed us to group the accessions into six subpopulations that corresponded well with the unrooted phylogenetic tree and principal coordinate analyses. When plotted, the STRUCTURE bars to the area of collection, we observed an admixed genotype from surrounding accessions and a geneflow confirmed by the value of FST = 0.137. AMOVA based on STRUCTURE clustering showed a low 12.83% variation between subpopulations that correspond well with the negative inbreeding coefficient value (FIS =  − 0.092) and low total fixation index (FIT = 0.057). There were distinguishing fruit shapes and length characteristics in specific accessions for each subpopulation. The genetic diversity and different fruit shapes in the L. acutangula germplasm could benefit the ridge gourd breeding programs to meet the demands and needs of consumers, farmers, and vegetable exporters such as increasing the yield of fruit by the fruit width but not by the fruit length to solve the problem of fruit breakage during exportation.

Optimization of integrated fuzzy decision tree and regression models for selection of oil spill response method in the Arctic

2021 ◽  
Vol 213 ◽  
pp. 106676
Author(s):  
Saeed Mohammadiun ◽  
Guangji Hu ◽  
Abdorreza Alavi Gharahbagh ◽  
Reza Mirshahi ◽  
Jianbing Li ◽  
...  
Keyword(s):  
Decision Tree ◽  
Oil Spill ◽  
Regression Models ◽  
The Arctic ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
Oil Spill Response ◽  
Response Method ◽  
Selection Of

scholarly journals GROWTH DYNAMICS OF SESAME CULTIVARS

2018 ◽  
Vol 31 (4) ◽  
pp. 1062-1068
Author(s):  
Rayanne Maria Paula Ribeiro ◽  
José Ricardo Tavares de Albuquerque ◽  
Manoel Galdino dos Santos ◽  
Aurélio Paes Barros Júnior ◽  
Leilson Costa Grangeiro ◽  
...  
Keyword(s):  
Block Design ◽  
Growth Dynamics ◽  
Plant Performance ◽  
Physiological Processes ◽  
Cropping Season ◽  
Physiological Indexes ◽  
Crop Cycle ◽  
Beginning Of Flowering ◽  
Cropping Seasons ◽  
Physiological Complexity

ABSTRACT Sesame is a plant with high morphological and physiological complexity, with great variability in growth habit. Quantitative growth analysis is an accessible and accurate tool for evaluating plant development and the contribution of different physiological processes to plant performance. In view of this, the purpose of this study was to evaluate the growth of sesame cultivars in two cropping seasons in the conditions of Mossoró-RN. Two experiments were conducted in Horta Didactics of UFERSA. The experimental delineation in each time was a randomized complete block design with four replications. The treatments were arranged in split plots where each experimental plot contained different sesame cultivars, CNPA G2, CNPA G3 and CNPA G4, and the subplots represented seven collection times, 21, 35, 49, 63, 77, 91 and 105 days after sowing (DAS). The growth of the sesame cultivars was slow at the beginning of the crop cycle, intensifying at the beginning of flowering (after 35 DAS). Among the physiological indexes studied, CNPA G4 cultivar was more efficient in relation to growth and varied depending on the cropping season.

scholarly journals Genotypic parameters for egg production in pure breed hens by using random regression model

2017 ◽  
Vol 47 (5) ◽  
Author(s):  
Priscila Becker Ferreira ◽  
Paulo Roberto Nogara Rorato ◽  
Fernanda Cristina Breda ◽  
Vanessa Tomazetti Michelotti ◽  
Alexandre Pires Rosa ◽  
...  
Keyword(s):  
Regression Model ◽  
Regression Models ◽  
Egg Production ◽  
Random Regression ◽  
Broad Sense Heritability ◽  
Residual Matrix ◽  
Random Regression Model ◽  
Residual Covariance ◽  
Genotypic Correlations ◽  
Selection Of

ABSTRACT: This study aimed to test different genotypic and residual covariance matrix structures in random regression models to model the egg production of Barred Plymouth Rock and White Plymouth Rock hens aged between 5 and 12 months. In addition, we estimated broad-sense heritability, and environmental and genotypic correlations. Six random regression models were evaluated, and for each model, 12 genotypic and residual matrix structures were tested. The random regression model with linear intercept and unstructured covariance (UN) for a matrix of random effects and unstructured correlation (UNR) for residual matrix adequately model the egg production curve of hens of the two study breeds. Genotypic correlations ranged from 0.15 (between age of 5 and 12 months) to 0.99 (between age of 10 and 11 months) and increased based on the time elapsed. Egg production heritability between 5- and 12-month-old hens increased with age, varying from 0.15 to 0.51. From the age of 9 months onward, heritability was moderate with estimates of genotypic correlations higher than 90% at the age of 10, 11, and 12 months. Results suggested that selection of hens to improve egg production should commence at the ninth month of age.

scholarly journals A NON-DESTRUCTIVE METHOD FOR ESTIMATING LEAF AREA OF Ceiba glaziovii (Kuntze) K. Schum.

FLORESTA ◽  
2019 ◽  
Vol 50 (1) ◽  
pp. 1063
Author(s):  
João Everthon da Silva Ribeiro ◽  
Francisco Romário Andrade Figueiredo ◽  
Ester Dos Santos Coêlho ◽  
Walter Esfrain Pereira ◽  
Manoel Bandeira de Albuquerque
Keyword(s):  
Leaf Area ◽  
Regression Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Linear Measurements ◽  
Maximum Width ◽  
Bias Index ◽  
Different Shapes ◽  
Non Destructive

The determination of leaf area is of fundamental importance in studies involving ecological and ecophysiological aspects of forest species. The objective of this research was to adjust an equation to determine the leaf area of Ceiba glaziovii as a function of linear measurements of leaves. Six hundred healthy leaf limbs were collected in different matrices, with different shapes and sizes, in the Mata do Pau-Ferro State Park, Areia, Paraíba state, Northeast Brazil. The maximum length (L), maximum width (W), product between length and width (L.W), and leaf area of the leaf limbs were calculated. The regression models used to construct equations were: linear, linear without intercept, quadratic, cubic, power and exponential. The criteria for choosing the best equation were based on the coefficient of determination (R²), Akaike information criterion (AIC), root mean square error (RMSE), Willmott concordance index (d) and BIAS index. All the proposed equations satisfactorily estimate the leaf area of C. glaziovii, due to their high determination coefficients (R² ≥ 0.851). The linear model without intercept, using the product between length and width (L.W), presented the best criteria to estimate the leaf area of the species, using the equation 0.4549*LW.

scholarly journals Prioritization and Selection of High Biomass Energy Producing Plant Species at Boset District, Central Ethiopia: An Ethnobotanical Approach 

2021 ◽  
Author(s):  
Tinsae Bahru Yifru ◽  
Berhane Kidane ◽  
Amsalu Tolessa
Keyword(s):  
Plant Species ◽  
Sustainable Use ◽  
Biomass Energy ◽  
Calotropis Procera ◽  
Sampled Data ◽  
High Biomass ◽  
Structured Interviews ◽  
Acacia Senegal ◽  
Selection Of Species ◽  
Selection Of

Abstract Background: In Ethiopia, about 92.3% of all the biomass energy is consumed by domestic households and the demand is growing from 10-14%. However, there are little/no practical experiences or documented indigenous knowledge on how traditional people identify and select high biomass producing plant species with short rotation periods at Boset District. Therefore, the present study was aimed at: (1) selecting and documenting high biomass energy producing plant species at Boset District; (2) identifying major predictor variables that influence the prioritization and selection of species; and (3) develop a Generalized Linear Model (GLM) to predict the selection of species. Methods: A total of 96 informants comprising 59 men and 37 women between the ages of 18 and 81 were sampled. Data were collected using structured interviews, guided field walk, discussions and field observations. Results: Collected data indicated that 88.5% of the informants involved in firewood collection, while 90% practiced charcoal making. A total of 1533.60 Birr per household on average was earned annually from this activity. A total of 25 firewood and/or charcoal plant species were identified and documented at Boset District. Of these, Acacia senegal, Acacia tortilis and Acacia robusta were the three best prioritized and selected indigenous high biomass producing species. Prosopis juliflora, Parthenium hysterophorus, Azadirachta indica, Calotropis procera, Cryptostegia grandiflora, Lantana camara and Senna occidentalis further grouped under introduced fuelwood species. Prediction of GLM assured sampled Kebeles and source of income generated from fuelwood species positively and significantly (p<0.001) related to selection of species. Higher efficiency to provide energy and heat; little or no smoke or soot; easier to cut and split the wood and easier availability were some of the main selection criteria. Conclusions: This study provides valuable information in selection and documenting of high biomass producing plant species for proper management and sustainable use at Boset District. The three most selected species (A. senegal, A. tortilis and A. robusta) should be further evaluated at laboratory to determine their energy values.

scholarly journals PENGARUH FAKTOR PSIKOLOGIS TERHADAP KEPUTUSAN PEMBELIAN MINYAK GORENG BIMOLI PADA IBU RUMAH TANGGA DI KECAMATAN KURANJI KOTA PADANG

2019 ◽  
Author(s):  
Ongky Fernando ◽  
Aminar Sutra Dewi
Keyword(s):  
Psychological Factors ◽  
Sampling Method ◽  
Coefficient Of Determination ◽  
Purchasing Decisions ◽  
Descriptive Research ◽  
Cooking Oil ◽  
Analysis Technique ◽  
Simple Regression Analysis ◽  
Simple Regression ◽  
Selection Of

Kosumen's behavior towards purchasing decisions is something that marketers must learn to know and understand how consumers make decisions, and the extent to which marketing stimuli can provide stimulus to purchasing decisions. So that can know whether the factors affect consumers in purchasing decisions. The purpose of this study was to determine the effect of psychological factors on the selection of Bimoli cooking oil brand in housewives in Kuranji sub-district, Padang City. The type of this research is descriptive research, many samples used are 250 people by using technique of non-probability sampling method. Data analysis technique used is simple regression analysis, t test and coefficient of determination. This research is done to produce psychological factors have a significant effect on purchasing decision on housewife in Bimoli cooking oil election in District Kuranji Town Padang t arithmetic 5,008&gt; t table 1,984 and significant value 0.000

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