Showing 189 results for Ssi
M. Sabokdast , F. Khyalparast,
Volume 11, Issue 42 (1-2008)
Abstract
This research was conducted in order to determine the relationship between grain yield and yield components, using 30 common bean varieties in a randomized complete block design with four replications at the Agricultural filed faculty of Agriculture,Tehran university In this study 18 traits were assessed on 10 random plants from each plot. The result showed that there were significant differences among varieties in terms of trait under study, indicating the existence of genetic variation among varieties. Also results showed that the grain yield had a positive and significant genotypic correlation with number of seed/pod, pod weight, number of pod/plant, biological yield, days to flowering and maturity. Stepwise regression analysis showed that the maximum variation in grain yield could be attributed to the number pod/plant, number seed/plant, 100 seed weight and pod length. The results of path analysis showed that the highest direct effect, being positive, was related to number seed/plant and the lowest direct effect, which was related to number pod/plant. Factor analysis resulted in three factors that accounted for 78/7% of total variation. The first factor accounted for 38.39% of total variation and was designated as yield and yield component factor. This factor is comprised of pod weight, biological yield, grain yield and number of pod/plant traits.
N. Yaghmaeian Mahabadi, J. Givi,
Volume 11, Issue 42 (1-2008)
Abstract
Gypsum affects many physical, chemical and mineralogical properties which in turn influences management, classification and sutability of the soils. This is the reason why accurate measurement of gypsum in soil is very important. In most of the soil science laboratories, the method of acetone ,in spite of its too much limitation, is being used as a standard method. The purpose of this research was to compare different gypsum determination methods and to find the most suitable one. The study areas include Jafarabad of Borkhar and Sepahanshahr.Soil samples were collected from different horizons of the studied profiles and seven samples with a wide range of gypsum content were selected. Gypsum content of the soil samples were determined by methods of acetone, sodium carbonate, resin, calcium and magnesium difference, diluted extracted sulfate, ammonium carbonate, sodium citrate and hydrochloric acid. To calculate the recovery percentage of the methods, after adding a certain amount of gypsum with known purity percentage to the soil samples, gypsum content was determined again by above mentioned eight methods. To evaluate the suitability of the methods, in addition to the recovery percentage of the methods, coefficient of variability and extent of proximity of the regression line to the 1:1 line were used. The results revealed that among the used methods, the method of sodium carbonate is the most accurate one. Resin method is ranked as the second best method and can be used in non-saline soils as another accurate method for determination of gypsum content. Sodium citrate and hydrochloric acid methods for different amounts of gypsum and ammonium carbonate method for gypsum content up to 30% are third in rank as far as their accuracy is concerned. Acetone, calcium magnesium difference and diluted extracted sulfate methods are not sufficiently accurate, because of low solubility of gypsum in water which is used as an extractant. In general, the most important determinant of accuracy of the methods is extractants of the gypsum among which the sodium carbonate has the highest efficiency.
H. Jalilvand,
Volume 11, Issue 42 (1-2008)
Abstract
This study was down in Forest Park of Noor. In order to determination of tree ring response to climatic variations, 35 cores were taken from dominant natural stand of common ash (Fraxinus excelsior L.). The guide of this study was finding which climatic variables are effective in the ring width growth of ash in current growing year and previous years (one, two and three years before current growing year) by multiple regression models at the North of IR-Iran. Totally, 85 annually, monthly seasons and seasonal growth climatic variations of precipitation, temperature, heat index, evapotranspiration and water balance were analyzed. The best multiple regression models were explained 83 percent of total variance of the growth of common ash. The results show that the growth of common ash was related to the previous year's climatic variations than that of the current year. The most effective role of climatic variations was due to the first and second preceding years (55%). Evapotranspiration of July and September, and precipitation of May in the second and precipitation of March in the third previous years, all were positively affected the growth of this species. This study revealed that ash is interested in warmer condition on early and middle of seasonal growth in present of available humid, and precipitation in the months of early growing season (Ordibehesht-Khordad of two previous years).
A.e. Bonyad, T. Hajyghaderi,
Volume 11, Issue 42 (1-2008)
Abstract
The natural forest and range stands of Zanjan province are located in mountainous areas. Inventorying and mapping of natural forest and range stands in mountainous areas are difficult and costly. Satellite data are suitable for this purpose. The Landsat ETM+ image data of 2002 are used for classification and mapping of natural forest stands in Zanjan province. For the purpose of data reduction and principal components extraction, the principal components analysis (PCA) was used. Just the scores of the first three PCs (PCA1، PCA2 and PCA3 (that accounted for 76.67 percent of the total variance were considered as new images for future analysis. A raster geographic information system (RGIS) database file was prepared and involved 7 ETM+ bands, 3 principle component analysis, 9 factor analysis and 8 vegetation indexes of image data. The correlation coefficients of 27 image layers and optimum index factors (OIF) of selected images were computed and 12 groups were found suitable for natural forest and range stands. Maximum liklelihood classification (MLC) method was used in this study. In order to test the accuracy of map, kappa index of agreement was calculated. The highest KIP belonged to three λ3, λ4, λ5 Landsat image bands with KIP = 0.86. The highest OIF belonged to three PCA3, FA2 and MIR with value of 233.44 and lower OIF belonged to three λ4, λ5, λ7 with value of 83.63. The overall, user’s and producer’s accuracy rates were 88.45, 73.69 and 70.23 percent respectively. The results of the study show that the Landsat ETM+ image data were appropriate for classification and mapping of natural forest and range stands in Zanjan province.
B. Najafi, A.r. Seifi, N.a. Babaeian Jelodar, A.m. Shakib,
Volume 12, Issue 43 (4-2008)
Abstract
Sorrel (Rumex acetosa L.) is a model dioecious plant in genetic and molecular studies for sex determination. In this research, gus reporter gene transformation to leaf disks of this plant via Agrobacterium tumefaciens was evaluated based on transient expression of this gene. Three strains of Agrobacterium( LBA4404, C58 and EHA101) and two kinds of bacterial suspensions (suspension I: Agrobacterium cells were grown in LB medium with PH 7 and suspension II: the cells were resuspended in MS medium containing 100 mM acetosyringone with PH 5.2) were analyzed in a factorial experiment with 3 replications in Complete Randomized Design (CRD). Also, the effects of three different times of pre-culture of explants (0, 2 and 4 days) were examined. Results showed no significant difference among bacterial strains, whereas suspension I and explants without pre-culture had higher efficiency in gene transformation to this plant. Based on the best treatment, stable transformation with different days of cocultivation was carried out and revealed that the 4-day cocultivation is more efficient than the 2-day cocultivation in gene transformation to Sorrel. The histochemical GUS assay and PCR analysis were done on putative transgenic plants. Results showed that some of these plants contain at least one copy of the transferred gene or genes in comparison with control plants .
H. Farhangfar, H. Naeemipour , R. Lotfi,
Volume 12, Issue 43 (4-2008)
Abstract
This study was undertaken to estimate genetic trend and parameters of Holstein cattle in Khorasan province for milk yield using a spline random regression test day animal model. A total of 32854 monthly test day milk records (twice and thrice a day milking) obtained from 3842 Holstein heifers (progeny of 466 sires) distributed in 125 herds and calved from 2001 to 2005 was used to predict breeding value of individual animals. In the model, fixed effects of herd including year-month of recording, milking times, age at calving (linear and quadratic covariables), Holstein gene percentage (linear covariable) as well as random effects of additive genetic and permanent environment were studied. To take account of the shape of the lactation curve at genetic and environmental levels, cubic spline polynomials were also included in the test day model. Bayesian method by applying Gibbs sampling technique (100000 chains applying RRGIBBS software) was utilized to obtain posterior means of predicted breeding value of animals for milk yield at individual month of lactation. The results showed that mean of breeding value for 305-day milk yield was 52.90 kg (p<0.05). Spearman rank correlations between predicted breeding values at different months of lactation decreased as the interval between them increased. The highest and lowest rank correlations were found between months 8 and 9 (0.998) and between months 1 and 10 (0.312), respectively. Predicted breeding value of 305-day milk had the lowest and highest rank correlations with predicted breeding value at months 1 (0.553) and 6 (0.990), respectively. Regression analysis of average predicted breeding value of progenies in their birth year showed that the amount of genetic trend for 305 day milk yield was 17.75 kg per year, statistically no different from zero (p value=0.165).
E. Rahmani, A. Khalili, A. Liaghat,
Volume 12, Issue 44 (7-2008)
Abstract
The growing season climatic parameters, especially rainfall, play the main role to predict the yield production. Therefore, the main objective of this research was to find out some possible relations among meteorology parameters and drought indexes with the yield using classical statistical methods. To achieve the objective, ten meteorological parameters and twelve drought indexes were evaluated in terms of normality and their mutual influences. Then the correlation analysis between the barley yield and the climatic parameters and drought indexes was performed. The results of this study showed that among the drought indexes, Nguyen Index, Transeau Index, Rainfall Anomaly Index and Standardized Precipitation Index (SPI24) are more effective for prediction of barely yield. It was also found that the multivariate regression is better than the univariate regression models. Finally, all the obtained regression models were ranked based on statistical indexes(R,RMSE and MBE). This study showed that the multivariate regression model including wind speed, sunshine, temperature summation more than 10, precipitation and Nguyen index is the best model for prediction yield production in Miane. Average wind speed and Nguyen index were recognized to be the most effective parameters for yield production in the model.
M. Tahmasbi, A. Hemmat, M. Vafaian, M. R. Masaddeghi,
Volume 12, Issue 44 (7-2008)
Abstract
For prevention of soil compaction, knowledge of allowable compression stress limit (compaction strength) in soil is important. Pre-compaction stress ( σpc) was introduced as soil compaction strength and often used as a criterion for evaluation of soil susceptibility to compaction. In this research, pre-compaction stress was measured for a sandy loam soil with plate sinkage (PST) and confined compression (CCT) tests. To prepare soil samples with different initial compactness, two soil water contents (17 and 19%db) and six pre-loading stresses (0, 25, 50, 100, 150 and 200 kPa) were used. The effects of soil water content and pre-loading stress on estimated pre-compaction stress were studied using a factorial experiment in a completely randomized design with three replications. The σpcvalues were significantly influenced by loading combination and soil water content. For PST, pre-load increase and higher soil water content resulted in higher and lower values of σpc , respectively. However, predicted σpc value increased with higher soil water content for CCT. The results also showed that the σpc predicted with PST was accurate, whereas the values obtained with CCT were 4.5 (at 17 %db) and 8.5 (at 19 %db) times higher than the applied pre-loads. Overall, the findings indicated that σpc prediction depends on the compression test, and PST could be a suitable method for soil pre-compaction stress (compaction strength) determination in sustainable soil management, i.e., soil trafficability and tillage. The PST method is also suitable to assess the effect of managing factors on pre-compaction stress.
H. Yosef-Zadeh, M. Tabari, K. Spahbodi, Gh. Jalali,
Volume 12, Issue 44 (7-2008)
Abstract
In order to predict Caucasian maple (Acer velutinum Boiss. ) seedling growth based on nursery Orimel, Eighty six one year old seedlings located at 1550 meters above sea level in Sari, north of Iran were randomly selected. Collar diameter, height, leaf area, photosynthesis area and leaf area/leaf weight ratio were determined. Then multivariate regression models between leaf characteristics and growth characteristic were drawn. The results indicated that number of leaves and photosynthesis area can estimate the height growth of a seedling. Also, mentioned characteristics of leaf can estimate the biomass of stem as a well as growth characteristics. According to the correlation between growth characteristics and leaf characteristics, it would be concluded that the photosynthesis area of leaf can be suitable for early selection of seedling for reforestation. Also, this result shows the importance of increasing the establishment and growth of maple seedlings in plantation areas.
J. Abdollahi, N. Baghestani, M.h. Saveqebi, M.h. Rahimian,
Volume 12, Issue 44 (7-2008)
Abstract
The present study discusses a method used to produce updated information about vegetation cover in arid and semi-arid zones, using RS data and GIS technique. In this method, Landsat ETM+ data in 2002 was collected in an area of about 60000 ha in Nodoushan basin, Yazd, Iran. To collect the necessary ground data, 50 sites of different vegetation types were selected and the percentage of vegetation cover in each one was determined. Also, different vegetation and soil indices were derived and crossed with located sampling points using ILWIS software capabilities. To get the best fitted curve, the relationship between vegetation cover, as a dependent variable, and satellite data bands, vegetation indices and environmental factors, as independent variables were assessed. Therefore, a multiple linear regression model was established for the prediction of vegetation cover percentage in the studied area. Finally, a vegetation cover map with high a precision was produced. As a conclusion, it can be said that mapping of vegetation cover via remote sensing is possible even if its vegetation cover is sparse.
M. Gholamhoseini, M. Aghaalikhani, M.j. Malakouti,
Volume 12, Issue 45 (10-2008)
Abstract
In order to study the effect of various amounts of nitrogen (N) and Iranian natural zeolite on the quantitative and qualitative forage yield of winter canola (Brassica napus L.) in light soil, a field experiment was conducted on research farm of Tarbiat Modares University, Tehran, during 2006-2007. Treatments were arranged in the form of RCBD with 3 replications. The experimental treatments were based on factorial various levels of zeolite (0, 3, 6 and 9 t.ha-1) and nitrogen (90, 180 and 270 kg ha-1) in urea form. Seeds of canola (Brassica napus L. cv. Okapi) were sown on October 2, and fresh forage was harvested at the time of silique formation (170 DAP). Results showed that the effect of N and zeolite on forage quantitative attributes including biomass, leaf and stem dry weight and leaf area index were statistically significant. In addition, forage qualitative traits including crude protein percentage and calcium percentage in plant mass were significantly affected by N and zeolite. Increasing application of N fertilizer caused increase in N leaching, and with increasing zeolite application, N leaching reduced. The interaction of two factors for all parameters was not significant. The most increasing effects on forage yield and quality were gained using 270 kg N ha-1 in combination with 9 t. Zeolite ha-1. More detailed studies are strongly recommended to investigate the effects of integrated application of chemical fertilizer and natural zeolite.
B Dolati, Sh Oustan, A Samadi,
Volume 12, Issue 46 (1-2009)
Abstract
Successive cropping of potassium-demanding crops like sunflower leads to depletion of soil potassium (K). This study was conducted to investigate the different forms of K and quantity–intensity (Q/I) relationship for sunflower growing soils in Khoy region, West Azarbaijan province. Twenty composite soil samples were collected from different soil series. Different forms of K, including solution K (Kso), exchangeable K (Kex) and non-exchangeable K (Knex) were determined. The results showed that Kso values varied from 0.061 to 0.54 (mmol L-1), with an average of 0.28 (mmol L-1), Kav values ranged from 55 to 699 (mg kg-1), 265 mg Kg-1 on average, and Kex values ranged from 54 to 694 (mg Kg-1) with an average of 261 (mg kg-1). Furthermore, Knex values varied from 160 to 612 (mg kg-1), 261 (mg kg-1) on average. Available K (NH4OAc- extraction) was less than 250 mg Kg-1 in half of the soils indicating the depletion of potassium from these soils. The Q/I curves were predominantly located in the adsorption regions. The Q/I curves were linear and lacked the curvature part relating to loss and gain of potassium present in the specific sites. The PBCK values varied from 11 to 108 (cmolc kg-1)/ (mol L-1) 0.5 and an average of 38 (cmolc kg-1)/(mol L-1)0.5. There was a linear significant relationship between PBCK and CEC (r2=0.82***). The AReK values ranged from 0.0014 to 0.027 (mol L-1) 0.5 and 0.0076 (mol L-1)0.5 on average. There was a significant relationship between the values of AReK and those of the soil solution K (r=0.68**). The Ko values varied from 0.0050 to 0.49 cmolc kg-1and an average of 0.21cmolc kg-1. Additionally, there was a high significant relationship between the values of Ko and ARoK (r= 0.95***) in the soils under study.
M Mirzaee, S Ruy, Gh Ghazavi, C Bogner,
Volume 12, Issue 46 (1-2009)
Abstract
At present, soil surface characteristics (SSC) are recognised as key parameters controlling infiltration rates, runoff generation and erosion. Microtopography of surface among SSC is the main one. The work presented in this paper is based on a set of digital elevation models (DEMs) supplied by two different methods: Laser roughness-meter and photogrammetry method. We used two maquettes. The used maquettes correspond to varying roughness (rough and soft roughness). These methods were compared using different statistical parameters of SSC such as heights and slopes histograms. In addition, we studied estimation of Random Roughness (RR) coefficient and Maximum Depression Storage (MDS). RR is considered as an indicator of microtopography and it is one of the main parameters influencing erosion and runoff-infiltration processes. The obtained RR by photogrammetry method showed, on average, 10 percent difference from laser method for soft maquette and 5 percent for the rough maquette. The range of this difference for the MDS varies from 2 to 34 percent, i.e., maximum 0.17 millimetres. In this study, photogrammetric method gives the DEMs with a lower slope for the rough maquette (on average 40.5 versus 46 for the laser method) and higher slope for the soft maquette (about 23.5 versus 20.7 for the laser method). The results showed the DEMs provided by photogrammetric method is able to perform accurate estimation for RR and provides good estimation for the MDS. Therefore, it can be useful in erosion and hydraulic studies.
M Noruzi, A Jalalian, Sh Ayoubi, H Khademi,
Volume 12, Issue 46 (1-2009)
Abstract
Crop yield, soil properties and erosion are strongly affected by terrain parameters. Therefore, knowledge about the effects of terrain parameters on strategic crops such as wheat production will help us with sustainable management of landscape. This study was conducted in 900ha, of Ardal district, Charmahal and Bakhtiari Province to develop regression models on wheat yield components vs. terrain parameters. Wheat yield and its components were measured in 100 points. Points were distributed randomly in stratified geomorphic surfaces. Yield components were measured by harvesting of 1 m2 plots. Terrain parameters were calculated by a 3×3 m spacing from digital elevation model. The result of descriptive statistics showed that all variables followed a normal distribution. The highest and lowest coefficient of variance (CV) was related to grain yield (0.36) and thousand seeds weight (0.13), respectively. Multiple regression models were established between yield components and terrain parameters attributes. The predictive models were validated using validation data set (20% of all data). The regression analysis revealed that wetness index and curvature were the most important attributes which explained about 45-78% of total yield components variability within the study area. The overall results indicated that topographic attributes may control a significant variability of rain-fed wheat yield. The result of validation analysis confirmed the above-stated conclusion with low RMSE and ME measures.
N Barahimi, M Afyuni, M Karami, Y Rezaee Nejad,
Volume 12, Issue 46 (1-2009)
Abstract
Compost and sewage sludge contain high concentration of plant nutrients and, thus, have been used extensively as an inexpensive fertilizer. The objective of this study was to evaluate cumulative and residual effects of compost, sewage sludge and cow manure on nitrogen, phosphorus and potassium in soil and wheat. The experiment included compost, sewage sludge and cow manure, each applied at 3 rates (25, 50 and 100 Mg ha-1), a chemical fertilizer (250 kg ha-1 amonium phosphate + urea) and a control plot with 3 replications. The experimental design consisted in completely randomized blocks with treatments arranged in split plots. To study the cumulative and residual effects of the organic amendments, application was repeated on four fifths of each plot in the second year. Wheat was grown in the plots. The results showed that one application (residual effect) of organic amendments had not significant effect on total N in soil and wheat leaves and stem, but it led to significant increase of available phosphorus and potassium in soil and wheat leaves and stem. Cumulative effects of organic amendments significantly (P≤ 0.05) increased the total N (in 50 and 100 Mg ha-1 Cow manure and 100 Mg ha-1 Compost treatments), available P in all organic treatments and K (in all Compost and Cow manure treatments) in soil. Also, cumulative effects of organic amendments significantly (P≤ 0.05) increased the N (in 100 Mg ha-1 sewage sludge), P (in 100 Mg ha-1 compost) and K (in all organic treatments with the exception of 25 Mg ha-1 Compost) concentrations in leaves and stem.
A Amini, M Shahsavan, A Zeinal Hamedani,
Volume 12, Issue 46 (1-2009)
Abstract
Women as extension help-agents could play an important role in rural extension programs. This study was aimed at evaluating the success of women as extension help-agents, and factors affecting their success in Isfahan province, Iran. The data was randomly collected from 156 extension help-agents, using Cochran formula. The validity and reliability of constructed questioners were checked, using Cronbach Alfa and K.M.O. criteria. The results showed that 6.5 percent of the agents gained a success score of more than or equal to the average score, 50.3 percent equal to the average score, and 43.2 percent gained less than the average success score. The Effective factors are categorized as the degree of their familiarity with the problems of the population, the degree of their involvement in extension-educational programs, and factors such as their access to rural libraries, financial and occupational background and contribution to community and team work. According to the regression analysis results, participation activities of the villagers, financial status of the help-agents and educational programs provide most influential factors for successful extension programs.
M.m Majidi, A Mirlohi,
Volume 12, Issue 46 (1-2009)
Abstract
This experiment was conducted to investigate the genetic diversity, identify traits explaining yield variation, recognize relationships between traits and classify accessions in a Iranian and forign germplasem of tall fescue. Forty six Iranian and foreign tall fescue accessions were surveyed for Phenological, morphological and agronomical characters in a randomized complete block design with three replications in field for 2 years. Significant differences were observed for all of the characters, indicating broad variation in this germplasm. Iranian accessions had a better performance for most of the traits in both years indicating their high potential for developing commercial varieties in breeding programs. Basis on stepwise regression analysis, crown width justified the majority of hay yield variation, followed by establishment rate, percentage of dry matter, height and number of stem. Hence, these characters could be used for selecting high yielding cultivars. Factor analysis revealed 4 factors which explained more than 80 percent of the total variation and confirmed the results of regression analysis. Using UPGMA method, cluster analysis revealed five groups. Accessions with similar country of origin or same ecological conditions were grouped in same cluster. Regarding the morphological characters the best accessions were identified to be used in the further breeding projects.
K Rabiei, M Khodambashi, A Rezaei,
Volume 12, Issue 46 (1-2009)
Abstract
Factor and principal component analyses are widely used in different sciences especially in agricultural science. To determine the factors that create variation between potato cultivars, in normal (non-stress) and water deficit (stress) conditions, two experiments were conducted in the form of randomized complete block design with three replications in summer 2002. Stepwise regression analysis showed that in normal conditions, stem length, number of stems/plant and leaflet width contributed significantly to yield. In stress condition, other than stem length and number of leaves/main stem, leaflet length also entered the model. As is evident, stem length had a detrimental effect on tuber yield in both stress and non-stress conditions. So, this trait could be used as an important criterion for the selection of high yielding genotypes. Principal component analysis revealed that number of stem, leaf length and leaf width were important traits creating variability between potato cultivars, especially number of stem that had high coefficients in the first principal for both environments. Factor analysis distinguished two factors in normal environment named leaf surface and structural attitude factors, and also two factors in stress environment called photosynthetic surface and structural attitude. Therefore, these factors should be intervened and attended to in breeding programs.
A Masoumi, A Shahriari,
Volume 13, Issue 47 (4-2009)
Abstract
To reduce storage space and transportation cost for alfalfa and straw bales, recompressing of the bales is recommended. In order to design different units and elements of double compressing device, some physical and rheological properties of desired products were determined. A factorial experiment with a randomized complete block design with three replications was used during the tests. Confined compression tests for three levels of axial strain (25, 35 and 45% of initial length) on alfalfa and straw bales were performed. In this study, the influence of the materials and strain on pressure, modulus of elasticity and required energy were investigated. The results showed that the effect of materials type and strain levels on the determined parameters were highly significant (P<0.01). The highest value of the measured parameter was obtained for straw bales at 45% strain. The Fabroad’s model (expressing the relationship between pressure and density) and two other models, namely, Sitki and Osbof which were used to describe the relationship between modulus of elasticity and density were fitted to the measured values, and then constants were determined for each model individually. The coefficients of friction for alfalfa and straw bales on steel and galvanized surfaces at three levels of perpendicular loads were determined. Effect of bales and surface types on frictional coefficient were not significant (P< 0.05), however, the effect of perpendicular load was highly significant (P<0.01). Tensile strength of hemp and nylon ropes, which are usually used to knot compressed bales, was measured. The results indicated that hemp ropes had more strength than nylon.
F Ghafori, M Eskandari, H Mohamadi,
Volume 13, Issue 47 (4-2009)
Abstract
Variance components and genetic parameters of body weight of Mehraban sheep were estimated by univariate and random regression models. This was done by using body weight records of 2746 Mehraban lambs related to flocks under supervision of the Agriculture Organization of the Hamadan province, collected between 1990 and 2005. In both methods, variance components estimates were obtained by restricted maximum likelihood (REML) using DFUNI and DXMRR programs, respectively, via DFREML 3.1 software package. Results showed that variance components obtained from RR models (except for residual variance) in some ages were higher than those obtained from univariate models. Direct heritability (h2) estimates from univariate and RR models were approximately equal to weaning age but, overall, RR estimates were higher than those obtained from univariate analyses. Maternal heritability estimates (m2) from RR models were higher than univariate models’ estimates, and showed a different pattern of variation with age. Correlations between predicted breeding values from univariate and RR models for birth weight and weaning weight were 0.72 and 0.70, respectively. Results showed that estimates of variance components and genetic parameters by RR models were affected by data structure and in case of the need for genetic parameters, especially those related to body weight late in lambs’ life, estimates of univariate analyses should be preferred.
