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In case of random effects models for balanced designs, the analysis is simple and no problem is encountered in testing the variance components since the sums of squares are independent, sums of squares are chi-square variates, ratio of variance components follow standard F-distribution and hence exact testing is possible. When a random effects model is considered in unbalanced designs, analysis of variance technique rarely produce exact tests for testing the hypothesis. Under the conventional normality assumptions, except for the error component, the analysis of variance fails to decompose the total sums of squares into independently distributed sums of squares. Also, sums of squares are neither chi-square variates nor multiple of chi-square variate. The sums of squares are not independent either. Another standardized measure that quantifies the difference between means and relationship between independent and the dependent variable is effect-size measure. Two generally used statistics for computing effect-size are eta and omega squared statistics. But, these statistics do not yield correct estimate of effect-size that are comparable across different designs [Bakeman (2005)]. In that scenario, generalized eta and omega statistics given by Olejnik and Algina (2003) can be used. There was a conversation on two-way factorial ANOVA with mixed effects and interactions [Nelder (1977, 1982, 1994, 2008)]. The major assessments about the two-way factorial ANOVA model is no substantial rationale for the imposed constraints on random interactions and a lack of clear interpretation of its variance components, especially for the main random effects in respect of the response [Nelder (1977), Wolfinger and Stroup (2000), Lencina et al. (2007)]. As a result, the usual model is more widely used nowadays. The unbalanced mixed ANOVA models are often analyzed under the linear mixed models (LMM) framework using the restricted maximum likelihood (REML) or generalized least squares approaches [Littell (2002), Stroup (2013), Jiang (2017)]. Kaur and Garg (2020) attempted for Computer aided construction of rectangular PBIB designs. Gupta and Sharma (2020) constructed a set of balanced incomplete block designs (BIBD) against the loss of two blocks where loss of some observations lie in between at most two common treatments. Gupta (2021) worked on nested partially balanced incomplete block designs and its analysis. Singh et al. (2021) presented mixture designs generated using orthogonal arrays. In this study, the one way random effects model for unbalanced nested design in which we have given the model, hypothesis to be tested, sums of squares and testing procedure for the hypothesis along with analysis of variance table. In the next section, we have explained model, hypothesis testing, sums of squares, hypothesis testing procedure and analysis of variance table for two way unbalanced nested design. Since in two way unbalanced case the means squares are generally not independent and are not distributed as chi-square variates, exact testing is not available for the main class variance component. We have obtained the expected size of approximate tests and the actual size for both conventional and approximate tests. Then with the help of a simulated data we found out the numerical for actual size of the conventional test and the actual and expected size of the approximate tests for some assumed values of the variance components.Under unbalanced design, testing of variance ratios are generally neither independent nor distributed as chi- square variates and does not follow standard F-distribution. In this case, exact testing of variance ratios is not available in the literature. Procedure for unbalanced data (generally not independent and are not distributed as chi-square variates) has been developed for testing the variance components in one way and two way unbalanced nested designs.Not Availabl

Mineral composition and their genetic variability analysis in eggplant (Solanum melongena L.) germplasm

Eggplant, Solanum melongena  L. is one of the most popular and major vegetable crops grown inSouth Asia and other parts of the world. It is an important source of plant-derived nutrients like minerals, available throughout the year and popular among the poor. Thirty two morphologically diverse eggplant germplasm accessions were analyzed for macro- and micro-minerals. Significant differences in the mineral content among the germplasm accessions were detected. Potassium and magnesium ranged from 177.19 to 274.48 mg and 6.25 to 18.34 mg/100 g fresh weight (FW), respectively. Copper, iron and zinc ranged from 0.024 to 0.178, 0.170 to 0.846 and 0.073 to 0.233 mg/100 g FW, respectively. Phenotypic co-efficient of variation and genotypic co-efficient of variation were high for the minerals studied except potassium. High broad sense heritability (84.44-97.07%) indicated the presence of additive gene effects. Significant positive correlation were found between zinc with potassium (r=0.397), magnesium (r=0.439) and copper (r=0.409). Overall, two germplasm accessions IC090785 and IC383102 have been identified as rich sources for all minerals studied, which could be utilized further in breeding programme for developing mineral-rich varieties of eggplant

Forecasting of growth rates of wheat yield of Uttar Pradesh through non-linear growth models

Wheat production in India is about 70 million tonnes per year which counts for approximately 12 per cent of world’s production. Being the second largest in population, it is also the second largest in wheat consumption after China, with a huge and growing wheat demand. Major wheat growing states in India are Uttar Pradesh, Punjab, Haryana, Rajasthan, Madhya Pradesh, Gujarat and Bihar. All of north is replenished with wheat cultivation. Uttar Pradesh, the largest wheat growing region of the country, produces around 28 million tonnes of wheat and Bihar produces around 5 million tonnes. The usual parametric approach for growth rate analysis is to assume multiplicative error in the underlying nonlinear geometric model and then fit the linearized model by ‘method of least squares'. This paper deals with a critical study of wheat yield of Uttar Pradesh with a non-linear approach. The available data of rice during different years is taken into consideration and different statistical models are fitted for that. The time series data on annual yield of wheat in UP from 1970-2010 were collected from various sources. Growth rates are computed through non-linear models, viz. Logistic, Gompertz and Monomolecular models. Different nonlinear procedures such as Gauss-Newton Method, Steepest-Descent Method, Levenberg-Merquadt Technique and Do Not Use Derivative (DUD) Method were used in this study to estimate the nonlinear growth rates. The results showed that logistic model performed better followed by Gompertz and monomolecular

Hydrogen Sulfide and Silicon Together Alleviate Chromium (VI) Toxicity by Modulating Morpho-Physiological and Key Antioxidant Defense Systems in Chickpea (Cicer arietinum L.) Varieties

Extensive use of chromium (Cr) in anthropogenic activities leads to Cr toxicity in plants causing serious threat to the environment. Cr toxicity impairs plant growth, development, and metabolism. In the present study, we explored the effect of NaHS [a hydrogen sulfide; (H2S), donor] and silicon (Si), alone or in combination, on two chickpea (Cicer arietinum) varieties (Pusa 2085 and Pusa Green 112), in pot conditions under Cr stress. Cr stress increased accumulation of Cr reduction of the plasma membrane (PM) H+-ATPase activity and decreased in photosynthetic pigments, essential minerals, relative water contents (RWC), and enzymatic and non-enzymatic antioxidants in both the varieties. Exogenous application of NaHS and Si on plants exposed to Cr stress mitigated the effect of Cr and enhanced the physiological and biochemical parameters by reducing Cr accumulation and oxidative stress in roots and leaves. The interactive effects of NaHS and Si showed a highly significant and positive correlation with PM H+-ATPase activity, photosynthetic pigments, essential minerals, RWC, proline content, and enzymatic antioxidant activities (catalase, peroxidase, ascorbate peroxidase, dehydroascorbate reductase, superoxide dismutase, and monodehydroascorbate reductase). A similar trend was observed for non-enzymatic antioxidant activities (ascorbic acid, glutathione, oxidized glutathione, and dehydroascorbic acid level) in leaves while oxidative damage in roots and leaves showed a negative correlation. Exogenous application of NaHS + Si could enhance Cr stress tolerance in chickpea and field studies are warranted for assessing crop yield under Cr-affected area

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Not AvailableABSTRACT The treatment combinations of the ordinary full factorial need not be the best for fitting the relationship. Therefore, it is necessary to search for a suitable set of treatment combinations by using which a stipulated relation can be fitted. The special class of designed experiments for fitting the response surfaces is called response surface design. Response surface designs have wide applications in agricultural, biological and industrial experiments. Similar to factorial experiments, experimental units in response surface design may exhibit trend over space or time. Among response surface designs, Box-Behnken design has been studied and linear trend-free design has been obtained. The developed algorithm helps the experimenters who are conducting quantitative factors using response surface designs. There may be a trend in the experimental material and hence we need trend-free design. It provides a complete solution in the sense that it is capable of generating the trend free Box-Behnken design. Trend-free designs are quite useful for such experimental situations. But the construction for such design is not easily available. It is, therefore, required to give easy method of construction, possibly computer aided for the construction of these designs. Thus algorithms have been developed to generate complete factorial experiments each at two levels with any number of factors k ( ³ 4) that are linear trend-free for main effects using the criterion of component-wise product.Not Availabl

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Not AvailableGrowth of animal is a repeated measurements data and observations taken on body weight at different time points are correlated to each other. A multivariate technique called profile analysis has been discussed to analyse the growth data (body weight) of animal. This technique is simplified and the data obtained from Jabalpur and Tirupati research stations under AICRP on pigs have been analysed. It was found that the null hypothesis of no interaction of groups with time points and that there is no difference in growth between groups is accepted at 5% level of significance. But the hypothesis of no difference in growth over different time points is rejected for both the research stations. It was observed that the period of 24--32 weeks of age is the period when the growth of pigs is accelerated fast for Jabalpur research station and 12-16 weeks, 20-24 weeks and 28-32 weeks of age are the periods when the growth is accelerated fast for Tirupati research station. These are the periods that need more attention for having the better growth of pigs. Further, 2 traditional (univariate) methods of analysis of repeated measures data have been described and the merits of profile analysis over these methods have also been discussed.Not Availabl

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Not AvailableThe treatment combinations of the ordinary full factorial need not be the best for fitting the relationship. Therefore, it is necessary to search for a suitable set of treatment combinations by using which a stipulated relation can be fitted. The special class of designed experiments for fitting the response surfaces is called response surface design. Response surface designs have wide applications in agricultural, biological and industrial experiments. Similar to factorial experiments, experimental units in response surface design may exhibit trend over space or time. Among response surface designs, Box-Behnken design has been studied and linear trend-free design has been obtained. The developed algorithm helps the experimenters who are conducting quantitative factors using response surface designs. There may be a trend in the experimental material and hence we need trend-free design. It provides a complete solution in the sense that it is capable of generating the trend free Box-Behnken design. Trend-free designs are quite useful for such experimental situations. But the construction for such design is not easily available. It is, therefore, required to give easy method of construction, possibly computer aided for the construction of these designs. Thus algorithms have been developed to generate complete factorial experiments each at two levels with any number of factors k (≥4) that are linear trend-free for main effects using the criterion of component-wise product.Not Availabl

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Not AvailableCreation and maintenance of a computerized information system that not only manages agricultural field experiments data efficiently but also provides its statistical analysis is essential for researchers, planners and farmers. Generally data created by the researchers is collected, processed and stored in different physical locations and is poorly disseminated. Data is usually retained at the level of each physical entity for organizational use. An adequate analysis of agricultural field experiments and interpretation of results over time and space seems to be lacking to effectively use it for agricultural policy planning and other purposes. An attempt has been made by creating a computerised Agricultural Field Experiments Information System (AFEIS) at ICAR-Indian Agricultural Statistics Research Institute (IASRI). This system has been aimed at addressing this urgent need by establishing a single, centralized data storage and retrieval system for agricultural field experimental data generated in the country. Development of this system will help the agricultural research workers, planners as well as the farmers to a great extant in this direction.Not Availabl

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Not AvailablePregnancy involves interactions of numerous growth factors, proteins and hormones exerting their biological functions in cellular growth, migration, differentiation and signal transduction. FGF2, STAT5A and UTMP are important mediators of intra-cellular signals transduction and transcription functions during pregnancy. Mutations in these genes will eventually disrupt their biological functions leading to embryonic death. The present study was designed to analyze in silico the SNPs in buffalo FGF2, STAT5A and UTMP genes by homology modeling. In the present study genomic DNA was isolated from the blood of 75 adult female buffaloes which was subsequently used for the amplification of FGF2, STAT5A and UTMP gene specific regions. PCR products of 167 bp, 429 bp and 279 bp were obtained for specific FGF2, STAT5A and UTMP gene regions, respectively. Sequenced PCR products showed 96–97% similarity with bovine sequences on BLAST analysis for all the 3 gene segments. Sequence analysis showed 9, 3 and 9 distinct nucleotide differences in the regions of FGF2, STAT5A, UTMP genes, respectively. Furthermore, based on the nucleotide difference 3 variants for FGF2 and UTMP genes were deduced in comparison with the bovine sequence. Promotor region analysis of FGF2 and homology modeling of STAT5A and UTMP gene revealed modification in the protein structure arising due to the presence of nucleotide changes. In the present study single nucleotide polymorphism were deduced in FGF2, STAT5A and UTMP gene region of buffalo and homology modeling of the studied gene portions were carried out.Not Availabl

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Not AvailableLettuce is considered as a high value vegetable due to its richness in phytonutrients. Nowadays, it is produced all the year round and consumed fresh so that all the ingredients stay intact. Estimation of different elements in different types of lettuce is essential in developing nutritionally rich, good quality varieties for cultivation. Sixty two genotypes comprising both heading and non-heading types were analyzed for six mineral content such as Calcium, Sulphur, Zinc, Copper, Manganese and Iron. The genotypes studied belonged to six lettuce types, namely Latin (three), Stem (five), Crisphead (thirteen) Butterhead (Eight), Leaf (twenty three) and Cos (ten). Overall, latin types were rich in sulphur, while crisphead types were rich in calcium and copper and butterhead in zinc, manganese and iron. The stem types, however, were found to be lesser in most of the minerals compared to other types. The Pennlake Crisphead lettuce genotype had highest calcium content (390.07 ppm), New chicken stem type had highest sulphur content (7.80 ppm), L-S-2 leaf type had highest zinc content (29.91 ppm), Balmoral crisphead type had highest copper content (10.98 ppm), Great takes Katrain crisphead type had highest magnesium content (44.94 ppm) followed by Sheetal crisphead type (44.11 ppm) and All source butterhead type had highest iron content (605.52 ppm). The comprehensive analysis helped by providing detailed information about the composition of minerals of different types as well as genotypes. The information so obtained will go a long way in developing mineral content dense lettuce varieties.Not Availabl