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Open Access
Development of a suitable model for ascertaining the growth and egg production in quails
(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1991) John Thomas, M; KAU; George, K C
An investigation was carried out into the growth and egg production aspect of Japanese quails at the Kerala Agricultural University Poultry Farm, Mannuthy on 1st February, 1989 with the following objectives. 1. to find a suitable relationship between age and body weight. 2. to investigate the" trend of egg production in quails through suitable mathematical models. ,3. to study the impact of climate parameters (temperature, ; , humidity) on egg production in quails. The birds were reared under uniform feed formula and ^identical management practices (recommended by Kerala Agricul tural University Package of Practices). The investigation mainly depended on' data consisting of weekly body weights of -ii^-dividual birds, daily egg production of birds (beginning from age at sexual maturity) and daily climatological para meters (temperature and humidity) from beginning till the end of experiment of 30th September, 1989. Mathematical models such as linear, quadratic, exponential, .Von-Bertalanffy, modified exponential, logistic and Gompertz were fitted for the purpose using body weights of ) individual birds as well as average body weights over twelve weeks and the fitted models were compared using coefficient of 2 determination (r ) and standard error of estimate(s). Mathematical models such as linear, exponentialf parabolic exponential, inverse polynomial. Gamma function. Gamma-type functic^n, quadratic function, quadratic function in logari'thmic scale, quadratic-cum-log, emperical and linear hyperbolic functions were fitted for the development of suitable models for ascertaining egg production using total weekly, fortnightly egg production, hen housed and hen day egg production and fitted models were compared using Furnival index, r^ and s. Multiple linear regression equation was fitted using average weekly egg production per bird as dependent variable and weekly temperature and humidity as explanatory variable to study the impact of climatological parameters on egg production in quails. The investigation has the following, salient features. (i) The hatching weight of Japanese quails were 7.1369 g. (ii) The females weighed more than the males during the entire period of experiment and the body weights have shown an increasing trend. At the end of 12th week the average body weights of males and females were 157.6552 g and 179.2500 g respectively. (iii) Rao's method justified that initial body weights • had no significant effect on growth rate. • (iv) Gompertz curve = a exp [-b exp(-kt)'] was most , suitable for , ascertaining growth in quails on individual basis as well as on the basis of • average body weights over twelve weeks. (v) Average age at sexual maturity (females) was found to be approximately 10 weeks and on an average the eggs weighed 12.20 g. (vi) Quadratic function in logarithmic scale ; = a f b(logJ^) + c(log^)^ was most suitable , for ascertaining egg production in quails (weekly, , fortnightly, hen housed and hen day production • basis). (vii) Climatic parameters had significant impact on egg production in quails.
Open Access
Study of genetic correlations under full -SIB mating system (Two loci case)
(Department of Statistics, College of veterinary and animal sciences Mannuthy, Thrissur, 1985) Khin Moe Moe; KAU; George, K C
A purely theoretical investigation entitled ,JA Study of Genetic Correlations under Fu ll-s ib Mating System (two lo c i case)*1 was carried out with the following objectives, i ) to derive the joint distribution (correlation table) and to find the correlation between fu ll -s ib pairs under fu l l -s ib mating system in the case of two lo c i when there i s no linkage as well as when there i s complete linkage. l i ) to derive the joint distribution (correlation table) and to find the correlation between parent-offspring pair© under fu l l -s ib mating system in the case of two loci when there is no linkage as well as when there is complete linkage, i i i ) to derive the joint distribution (correlation table) and to find the correlation between fu l l -s ib pairs under paront-offspring mating system in the case of two lo c i when there is no linkage as well as when there is complete linkage, iv) to derive the joint distribution (correlation table) and to find the correlation between parent-offspring pairs under parent-offspring mating system in the case of two lo c i when there is no linkage as well as when there is complete linkage. 2 Th© joint distributions of fu ll -s ib pairs and parent- ©Ffspring pairs undor fu ll-s ib gating system wore derived with the help of generation matrix technique and th© correlations wore worked out therefrom, assuming additive genie e ffec ts and using the product-momeni correlation coefficient formula. The correlations were worked out for tho f i r s t ten generations of fu ll -s ib mating in both cases of no linkage and complete linkage, & comparative study of fu ll -s ib correlations and parent-offspring correlationsf conducted both numerically and graphically, revealed that £i) evonthough fu ll -s ib correlation was greater than parent-offspring correlation in in i t ia l generation (random mating) when there was complete linkage, the la tte r increased more rapidly than the former from in it ia l generation to f ir s t generation and ( i i ) from the second generation onwards, the rate of increase in both o f correlations were nearly the same upto tenth generation. I t was interesting to note that the parent-offspring correlations wore of comparatively higher order than th© fu ll-s ib correlations in both cases of complete linkage and no linkage. Similarly, th© joint distributions (correlation tables) for fu ll-s ib pairs and parent-offspring pairs under parentoffspring mating system were derived employing generation matrix approach and the correlations for the f i r s t ten 3 generations of parent—offspring mating in both cases of no linkage and complete linkage were worked out therefrom. A comparative study of those correlations was carried out both numerically and graphically. It was found that the trend in both correlation curves remain the same, but the value of parent-offspring correlation was always greater than that of full-sib correlation in case of no linkage as well as in caso of complete linkage. In comparison of all these correlations, it was found that the correlations increased as the number of generation increased and ultimately reached the limit unity when the number of generations increased indefinitely large. It was also observed that the magnitude of correlation in case of complete linkage was more than that of correlation In case of no linkage even under the same system of mating*
Open Access
Nonlinear models for major crops of Kerala
(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 2007) Joshy, C G; KAU; Krishnan, S
Nonlinear modelling techniques are the most suited tools for describing any time series phenomenon. Among the various nonlinear models in vogue monomolecular, logistic, gompertz and mixed-influence models find a prominent place. With this idea the agricultural scenario of Kerala was measured through the three important descriptors namely area, production and productivity of the major crops viz; coconut, rubber, paddy, pepper, tapioca, cashew and banana for all the districts and the state as such. Monomolecular model was the most apt model in most of the cases. The data sets were further explored based on the carrying capacity achieved by 2002-03 coupled with intrinsic growth rate. When none of the nonlinear models were found satisfactory either simple linear regression model or quadratic model was tried to explore the nature of trend. Coconut production was found to have reached its near maximum in all the districts where it was a major crop but the productivity figures gave a warning note for increasing the productivity. Rubber was found to be one of the most gifted crops, which was not devoid of proper attention. Even with this stature, production of rubber can be improved through uniform management practices. Usually nonlinear and quadratic models aptly describe a time series data on crop production. It is astonishing that simple linear regression model aptly described the paddy production in the state. The regressive value of the regression coefficients indicated that paddy production in the state is facing extinction.Paddy production in the state has at least to be protected. The lack of fit of most of the nonlinear models and even quadratic models to the data of pepper production indicate the various devastating hazards that the crop faced with. These contrasting features bring out the fact that pepper cultivation be not allowed to be toyed with. The area specific crops like cashew, cardamom, coffee and banana be made nonspecific through innovative technologies. A concerted effort with valid stresses specific to each crop will make the agricultural scenario bright.
Open Access
Interaction effect under ammi model
(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 2006) Eldho, Varghese; KAU; Krishnan, S
The study of interaction is one of the major objectives of most of agricultural experiments. Conceptually this is done based on regression technique. Among the interactions studied, two factor interaction derives its importance as it is the simplest of the interactions. The joint regression technique is employed to study the G x E interaction. The regression techniques are having the assumption of additivity of effects. When there is departure from these assumption the joint regression technique fails. Additive Main effects and Multiplicative Interaction studies have helped a lot at this juncture. Raju (2002) derived a more comprehensive measure of interaction based on AMMI model. This was achieved using the spectral decomposition of the relevant interaction matrix which enabled the study of interaction with the same precision as that of studying the main effects. Biplots formulations of interaction effects based on the PCA vector scores are the most simplest and explicit representation of interaction. The study of interaction based on spectral decomposition has been illustrated using the secondary data on the biometric, chemical and qualitative characters from the projects “Development of a bimodal phasic management system to improve both quantity and quality in Kacholam (Kaempferia galanga)” and “Development of a bimodal phasic management system to improve both quantity and quality in Njavara (Oriza Sativa)”. The DMRT tests for each level of the factors viz., calcium and source were carried out for the parameters viz., percentage content of phosphorus in rhizome, percentage content of potassium in rhizome and North – South foliage spread. In all these characters no specific interaction effect could be sorted out. These interactions when studied based on the factor analytical technique revealed that source II and second level of calcium had the highest positive interaction as regards the percentage content of phosphorus; source III and third level of calcium for percentage content of potassium and source II and third level of calcium for North – South foliage spread. When the order of the interaction matrix was high as in the case of the second experiment, DMRT tests failed to highlight the appropriate interactive effect in the characters viz., grain yield, percentage content of nitrogen in grain, percentage content of phosphorus in grain, percentage content of phosphorus in straw and percentage content of potassium in straw. The study based on the factor analytical technique revealed that the treatments T15, T8, T3, T1 and T4 respectively had the highest interactive effect with Payyanur for the above said characters where as for Badagara they were T3, T14, T4, T5 and T8 .
Open Access
Spatial and temporal variations in the development of agriculture in Kerala
(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 2002) Allahad, Mishra; KAU; Ajitha, T K
Agricultural scenario of Kerala is unique as compared to other states of India. The present study entitled "Spatial and temporal variations in the development of agriculture in Kerala" was undertaken mainly with an objective of constructing composite indices to quantify the development of agriculture based on suitable indicator variables for each district or region of Kerala. The significance of the districtwise and temporal disparities in agricultural development have been studied. The agricultural growth with respect to acreage and gross production of major crops • is also estimated using different growth curves. The time series data from 1970-71 to 1997-98 collected from State Planning Board and Directorate of Economics and Statistics, Government of Kerala, Trivandrum were used for the study. As all the districts were not present before 1985-86 state was divided into several regions. Districts wise analysis was carried out from 1985-86 to 1997-98, whereas region wise analysis was carried out from 1970-71 to 1997-98. For measuring the diversification level of districts or regions five indices viz., Herfindahl Index, Entropy Index, Modified Entropy Index, Composite Entropy Index and Ogive Index were computed. All the quantitative indices were constructed by using the total cropped area of seven major crops of Kerala. It was found that in most of the periods the diversification in cropping pattern was mainly towards plantation crops. The most diversified district was Kollam, where the cropping pattern had equal importance to all the major crops. Based on the real situation, out of the five measures of diversification Composite Entropy Index was found to be better suited. It was also noticed that as time progressed the diversification level among the districts or regions decreased. The Compound growth rates of both production and acreage were computed and it was found that rubber recorded the highest C.G.R. The food crops viz., rice and tapioca showed negative C.G.R whereas cash crops viz., coconut and pepper showed positive C.G.R for both production and acreage. Productivity index were constructed for each district taking into consideration the variety of crops and their relative importance in a particular district. The results revealed that different districts behaved differently with respect to the rate of growth of productivity. Development is a multidimensional process, so instead of analysing a single variable, composite index or development index for different districts or regions were computed by using several indicators, which contributed to the development of agriculture. In the present study three methods were used to compute the development index based on seven indicators. In the first approach i.e. Taxonomic approach during 1985-86, 1990-91 and 1995-96 Emakulam occupied the first place in agriculture development. However, Wayanad and Kasargode were the two least agriculturally developed districts during the above said periods. It was also observed that there was hardly any change in the level of development of agriculture over different periods of study. In Taxonomic approach each variable was considered to have equal contribution towards the development of agriculture. However, it is unlikely to happen so. With this fact, the Taxonomic approach was modified in Modified Taxonomic approach by giving separate weightage to the indicators based on the score given by experts. In the present study separate weightage did not have any significant impact on the classification of districts or regions on their agricultural development status. Obviously the selected variables might be highly correlated. Characteristics in biological experiment are highly correlated. In the present study Principal Component analysis was used to overcome this problem. The first component of both district wise and region wise analysis contributed around 99.5 per cent of total variation. Therefore, without loosing any information supplied by the seven variables, the first component score was taken as the composite index of development. Hence in the present context Principal Component analysis could be considered as the best method, as no approximation is involved. It could be considered as a more comprehensive method. The Potential targets for the under developed districts or regions are also estimated to assess the position of those districts or regions compared to the model • districts or regions. Accordingly suitable development programmes can be launched or special care can be taken to allocate resources optimally on per capita basis to reduce spatial disparities in development.
Open Access
Study of Genetic Diversity in Desert and Culinary Types of Banana Varieties
(Department of Statistics,College of Veterinary,Mannuthy, 1981) Mercey, K A; KAU; George, K C
The data taken from the Bana Research Station, Kannara for 30 culinary varieties for 13 morphological characters and 56 dessert varieties for 12 morphological characters were the base material for this study. Genetic divergences in the varieties were studied using D2-statistic and canonical analysis. The varieties were grouped into clusters by using Tooher’s minimum generalized distance concept. The same clustering pattern was obtained through canonical analysis. In the case of culinary varieties 12 clusters were formed consisting 11 varieties in the first cluster 5 each in second and third and the others were single variety clusters. Whereas the dessert varieties were grouped into 7 clusters 13 varieties in the first cluster 17 in the second cluster, 20 in the third, 2 each in the fourth and fifth and the last two were single variety clusters. The intra and inter cluster distance were diagrammatically represented in a two dimensional space. The scatter diagram showing the mean values of the canonical variates in order to have an idea of the appropriateness of the clustering pattern were also formed in both the type of varieties. In the case of culinary varieties the character bunch weight and in the case of dessert varieties the character finger length was contributing maximum towards divergence. The character girth was contributing minimum towards divergence in both the cases.
Open Access
Optimum size of plots In coconut using multivariete techniques
(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1997) Kumari Liji, R S; KAU; Gopinathan Unnithan, V K
This investigation was taken up to determine optimum size of experimental units for coconut using multivariate approach. Observations on yield, female flower production, percentage of buttons set and number of functional leaves from 184 coconut palms for two consecutive years were utilised. These palms belonged to two separate experiments in two locations. All known systematic effects were eliminated from the observations. The trees were arranged in the ascending order of the number of functional leaves of first year of observations. Experimental units of sizes ranging from single tree to ten trees were formed by combining trees adjacent in the list of ordered trees. Blocks of five plots, seven plots and ten plots were also formed by combining adjacent plots. Coefficient of variation in univariate case and determinant of relative dispersion matrix in multivariate case were the measures of variation used. Optimum size of experimental units was determined in univariate case for yield and female flower production in first and second years. Optimum size of plots was determined in multivariate case for the following character combinations. 1) Yield for first and second year 2) Female flower production for first and second years 3) Yield and female flower production for first and second year 4) Yield, female flower production and percentage of buttons set for the first year 5) Yield female flower production and percentage of bottons set for the second year Optimum size of plot was determined by three different criteria viz., (i) that which requires minimal experimental material for a specified precision (ii) that having maximum efficiency and (iii) that which maximises the curvature of the relationship between measure of variation and plot size. Plot size that required minimum number of trees for 5 per cent error was two tree plots except in the univariate case of yield in first year and multivariate case of without blocking for characters sets (4) and (5) for which single tree plots were optimum. In all univariate determinations single tree plots had maximum efficiency. Two tree plots had maximum efficiency in multivariate approach except for characters sets (4) and (5) in the case of no blocking. Four tree plot was optimum by the method of maximum curvature except for characters sets (3), (4) and (5) is multivariate case for which three tree plots were optimum. Though Fair Field Smith's law was a good fit to the relationship between the measure of variation and plot size, Y = a +b/√x+ c/x gave better fit in most of the cases. Two tree plots were recommended for experiments it) established coconut gardens.
Open Access
Forcasting of lemongrass (Cymbopogon flexuosus Nees ex.Steud Wats) yield based on weather
(Department of Agricultural Statistics, College of Horticulture,Vellanikkara, 2001) Sajitha Vijayan, M; KAU; Soudamini, P
The grass and oil yield obtained from comparative yield trials conducted at Aromatic and Medicinal Plants Research Station from 1965-1989 and the weather observations corresponding to the same period have been analysed in order to evaluate the effect of different climatic factors on lomongrass yield and to develop suitable prediction models for the pre-harvest forecasting of grass yield with sufficient degree of precision. The variety viz., OD-19 (Sugandhi) was considered and the crop was raised as rainfed for the entire period of investigation. The meteorological variables included in the study were number of rainy days, total rainfall (mm), maximum temperature (0C), minimum temperature (0C) and relative humidity (%). Coefficients of correlation of weather variables and their logarithms with grass and oil yield for the growing period of the crop (six weeks or three fortnights) were worked out. Two stage regression models for each week of the growing period were developed to predict grass and oil yield using observations on weather variables up to the week of forecast as the explanatory variables. Predictability of model obtained for earlier week of crop growth were over 70% for first, second, fourth and fifth harvests. Fortnightly prediction models were also developed making use of weather variables and their logarithms. In addition to these, logarithms of weather variables were also used as explanatory variables to predict logarithm of grass and oil yields. In the case of fortnightly weather variables composite regression model proposed by Agrawal et al.(1980) was also developed.
Open Access
Changing scenario of Kerala agriculture- an overview
(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 2009) Unnikrishnan, T; KAU; Ajitha T K
The present investigations on “Changing scenario of Kerala agriculture – an overview” was carried out in the Department of Agricultural Statistics, College of Horticulture, Vellanikkara during 2006 – ’09. The secondary data on area, production, productivity and price of major crops of Kerala viz; coconut, rubber, paddy(season wise), pepper, cashew, arecanut, coffee, tapioca and banana collected from the Directorate of Economics and Statistics for the period from 1952-53 to 2006-07 were used for the analysis. The main objectives of the study included assessment of trend and growth rates of area, production, productivity and price, testing of the cointegrated movement of price and respective area of each crop, identification of the best ARIMA(Auto Regressive Integrated Moving Average) model for prediction of area, production, productivity and price and comparison of predictability of forecasting models developed by different techniques. Modified P-Gan’s method helped to understand whether the growth rate in crop production was mainly due to area or productivity. The series of prices and areas of respective crops could be co-integrated and the regression models evolved through this technique resulted in moderately high values of predictability. ARIMA models were superior to other models developed achieving a maximum value of R2 = 99.8% for the prediction of area of rubber with a very low value of MAFPE = 1.23%. Excellent parsimonious forecasting equations could be generated using the ARIMA technique for all the crops studied. The general findings of the study showed that there was a shift in area from food crops to non-food crops. The production of major food crops, rice and tapioca reached at negative growth rates due to the declining trend of their areas. But production rate of banana has increased due to increase in both area and yield. Among cash crops, both area and productivity growths influenced the production rates. The major cash crops coconut, arecanut and pepper showed positive growth rates. Compared to food crops, cash crops in general showed better growth trends in production. Negative growth rate in the production of cashewnut was due to the decline in area. Among plantation crops, rubber and coffee attained a high production growth rate due to the combined growth of area and productivity. The highest production growth rate and area growth rate were recorded by rubber among all the crops studied.

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