Extending Shelf Life and Maintaining Quality of Tomato Fruit by Calcium Chloride, Hydrogen Peroxide, Chitosan, and Ozonated Water

Tomatoes are perishable fruit that makes them deteriorate rapidly during the post-harvest chain. Therefore, the effect of calcium chloride (CaCl2), chitosan, hydrogen peroxide (H2O2), and ozonated water on the storage abil\ity and quality of tomato fruit (Solanumlycopersicum L. cv. 448) stored at 10 °C for 28 d was studied. Weight loss, firmness, fruit color, total soluble solids (TSS), titratable acidity, total carotenoids, and ascorbic acid content (AsA) of treated tomato fruit were recorded. Our results revealed that all tested treatments significantly extended the shelf-life and maintained quality of tomato fruit compared to the control. Chitosan and CaCl2 were the most effective treatments in maintaining quality attributes. Furthermore, a correlation study suggested that AsA and total carotenoids played a vital role in conserving tomato fruit quality during storage. PC1 had strong positive loading for pH, appearance, firmness, AsA, TSS, carotene, fruit color (L* & b*) and a strong negative loading for lycopene content, color (a), weight loss, and color index. PC2 had high positive loading for total acidity and total sugar content.

Spatial variability in Karoo dolerites

<p>AD Kotze and RJ Roberts</p><p>Department of Geology, University of Pretoria, Hatfield, Pretoria, South Africa; [email protected]</p><p>The Karoo Large Igneous Province (KLIP) in South Africa consists of both a spatially limited extrusive basalt suite (Drakensberg Group) and a spatially extensive dolerite suite, both generally considered to be remarkable homogenous and of a “low-Ti” character (Luttinen, 2018). The homogeneity of the rocks requires that statistical analysis is necessary to look for spatial and geochemical trends in the data, which may yield clues to the mantle processes producing the 60 000 km<sup>2</sup> expanse of basaltic magma. In this project, data derived from several locations are used as proxies to check for lateral variability in the Karoo dolerites. A principal component analysis (PCA) on trace element data using a covariance matrix was performed, and comparisons based on variables that are 1) common to the Karoo dolerites and Lesotho basalts and, 2) responsible for the most amount of variation to the data set are made. Trace element modelling is then used to test different mantle melting scenarios possibly responsible for the variation seen in the dolerites.</p><p>Principal component analyses revealed several trace elements are responsible for most of the variability in the dolerites. Cr and Ni has the strongest positive loading on Component 1 whereas Cr and Ba has the strongest positive loading on Component 2. Ba has a strong negative loading on Component 1. Cu, Sr, V and Zr do impart an appreciable amount of variation to the data, but all four variables have weak negative loadings on both components. Interestingly, the activity of Cu and V seems to be the inverse of that of Cr and Ni.</p><p>Due to the nature of a PCA, this work is afforded an opportunity to place the geochemistry of the Karoo dolerites within a larger geodynamic context without bias. From the observed variation, the activity of Ba and Cr is interpreted as an assimilation-oxidation process, whereas the Ni signature reflects the mantle origin of the magmas. Further modelling of these processes will allow the testing of suggested mechanisms for the formation of the KLIP, especially whether the magmatism is plume-related or related to the foundering of crustal blocks.</p><p>Luttinen, A., 2018. Bilateral geochemical asymmetry in the Karoo large igneous province. Scientific Reports, 8(5223).</p>

Assessment of Genetic Divergence in Long Day Onion (Allium cepa L.) through Principal Component and Single Linkage Cluster Analysis

To assess the nature and magnitude of genetic diversity in long day onion germplasm by using the principal component analysis and single linkage cluster analysis an experiment was carried out with 34 onion genotypes. High coefficient of variation with wide range in traits indicated an appreciable variability in germplasm. Genotypes were classified into seven principal components having Eigen value > 1, cumulatively accounted for 83.87% of total variability. Principal Component - I contributed for 24.73% of total variation for followed by principal component-II (15.27%). PC-I had high positive loading for bulb weight (0.401), marketable yield (0.338), total bulb yield (0.401) and PC-II had high positive loading for plant height (0.412), PC-III for high T.S.S. (0.276) PC -IV for A grade bulbs (0.436), PC-V for polar diameter of bulbs (0.514), PC-IV negatively loaded with purple blotch (-0.461) and PC-VII for narrow neck thickness (-0 .515). Plotting PC-I aganist PC-II differenciated CITH-O-13, CITH-O-4, CITH-O-22, CITH-O-19, CITH-O-9, CITH-O-6 and CITH-O2 as most divergent genotype.On the basis of single linkage cluster means cluster-I was most importent for average bulb weight, minimum bolters, high marketble bulb percentage high marketable and total bulb yield whereas cluster -II was important for maximum nuber of leaves/plant and minimum neck thicknes. Highest inter-cluster distance was observed between cluter II and Cluster-I(873.5% ).Most divergent genotypes with high inter cluter distance could be the most appropriate parents for crop impovement in onion.

Spatio-temporal variations of water quality and phytoplankton diversity of the different rivers flowing within Sundarban mangrove wetland ecosystem of Bangladesh

The water of different rivers passing in the Sundarban Mangrove Forests (SMF) of Bangladesh was analyzed to know the spatio-temporal variations in the water quality and phytoplankton diversity of the river. The pH of the waters of all the rivers examined showed a narrow range of variation (6.60-7.8 in 2015 and 6.3 to 7.5 in 2016) indicating the buffering capacity of different rivers. The values of pH showed a slightly decreasing tendency indicating the acidification of river waters which might be due to increase of global CO2 concentration in the atmosphere. The temperature of water, conductivity, salinity, DO (ppm), DO (% sat), K, Na, was found to vary from 27.6 to 30.8° C, 8.00 to 32.30 mS/cm, 5.50 to 23.00 ‰, 3.5 to 6.35 ppm, 46.60 to 82.00 %, 125.00 to 630.00 mg/l, 600 to 4300 ppm, respectively in April 2015; and ranged from 28.8 to 31.0° C, 9.48 to 31.60 mS/cm 5.00 to 24.00 ‰, 0.11 to 5.33 ppm, 1.2 to 95.2 % saturation, 110 to 670 ppm, 4683.5 to 13465.10 ppm, respectively in March 2016. The values of Ca, Mg and Fe were 210 to 500 ppm, 320.0 mg/l to 892.0 mg/l and 0.25 to 0.050 mg/l, respectively in 2015. The amount of DO was very low during 2016 especially in the locations 1, 2, 3 which might be due to cloudy condition during sampling time. Principal component analyses (PCA) of different variables of the year 2015 showed that PC-1 had positive loading of water temperature, air temperature, humidity, pH, conductivity, Salinity, Na, K, Fe, Mg, Zn whereas PC-1 of different variables during 2016 showed positive loading of only water temperature and pH. Maximum number of phytoplankton taxa was recorded from Sela river (Tambulbunia) where 34 taxa (with the unknown ones) were recorded followed by Passur river (near Mongla Ferry Ghat). Coscinodiscus is found to be the dominant genus. Maximum Shannon-Weaver index of diversity was found in Homra Khal (value was 6.825) and minimum was found in Sela river (where the oil tanker sank and value was 0.0). Only one species of phytoplankton was found in this place. Maximum species richness (d) was observed in Passur river at Mongla ferry ghat with a value of 14.81 whereas, maximum evenness (e) was found in location 16 (Homra khal with a value of 5.437). J. Biodivers. Conserv. Bioresour. Manag. 2019, 5(1): 61-76

Hydrochemical Characterisation and Groundwater Suitability for Drinking and Irrigation uses in Semiarid Region of Nashik, Maharashtra, India

Hydrochemical investigation was undertaken in the Kadava river basin to ascertain the groundwater quality and its suitability for drinking and irrigation purposes. In this context, forty (40) representative groundwater samples were collected from different dug/bore wells based on their importance in drinking and analyzed. Physicochemical parameters like pH, EC and TDS; cations viz., Ca, Mg, Na and K; and anions include CO3, HCO3, SO4, NO3, F, Cl were determined to authenticate the groundwater suitability for drinking. According to BIS, pH (15%), TDS (27.5%), TH (27.5%), Mg (45%), Na (15%), Cl (2.5%), NO3 (52.5%) and F (2.5%) samples exceed the permissible limit (PL); hence, unfit for drinking. The positive loading of TDS and TH is influenced by the content of Mg, Na, Cl and SO4 ions. The increased concentration of Na over Ca corresponds to the ion exchange process. The irrigation indices like SAR, Na (%), RSC, MAR, KR and SSP were considered to evaluate groundwater aptness for irrigation. According to SAR and RSC classification all groundwater samples are suitable for irrigation. MAR ratio suggests 97.5% samples are unfit for irrigation. The study advocates that, those aquifers which are awkward then particular remedial measures required prior to their beneficial use.

Assessment by Multivariate Analysis of Groundwater between Low and High Tides Interactions in East Coast of Terengganu

World sea level rise has an effect in the rise on high and low tides levels in coastal areas of Terengganu. Because of that, as many as 13 groundwater represented of well that located close to Terengganu coastline were sampled and analyzed. Samplings were conducted for the wet and dry seasons and also for the high and low tides at the same sampling wells to identify the variation of groundwater quality temporally. A Global Positioning System (GPS) was used to locate the exact coordinates of each sampling well. Nineteen physico-chemical parameters were analyzed from groundwater samples. Principal Component Analysis (PCA) was adopted to observe the contrast of the compositional pattern among the variables and to recognize the factors that influence the parameters as an input to define water intrusion. Hierarchical Agglomerative Clustering Analysis (HACA) is performed on data to group the sampling wells into a few clusters. The results show that from nineteen parameters only five has strong positive loading; EC (0.99), TDS (0.99), chloride (0.99), sulphate (0.92) and salinity (0.99) during high and low tides. The difference are BOD and DO have strong positive loading during low tide while turbidity and TSS were strong positive loading during high tide.

Breakfast patterns and their association with body mass index in Brazilian adults

The objective was to investigate the relationships between body mass index (BMI), skipping breakfast, and breakfast patterns in Brazilian adults. We analyzed data of 21,003 individuals aged between 20 to 59 from the Brazilian National Dietary Survey 2008-2009. Breakfast was defined as the eating occasion between 5 and 10a.m. with the highest usual food consumption (exceeding 50Kcal/209.2kJ). Dietary patterns were derived by the factor analysis of 18 food groups (usual intake). Controlling for confounders linear regressions of BMI were used to verify the associations considering the survey design. Skipping breakfast was not associated with BMI. Three breakfast patterns were observed (48% variability): Brazilian Northern (positive loading for meats, preparations with corn, eggs, tubers/roots/potatoes, dairy products, savory snacks/crackers, fruit juices/fruit drinks/soy-based drinks); Western (positive for fruit juices/fruit drinks/soy-based drinks, sandwiches/pizza, baked/deep-fried snacks, chocolate/desserts, cakes/cookies) and Brazilian Southeastern (cold cut meat, milk, cheese, coffee/tea, bread). The Brazilian Southeastern pattern was inversely associated with BMI, while the Brazilian Northern pattern was directly associated with it. Therefore, the results suggest a role for breakfast quality in the association with BMI. Thus, a Brazilian Southeastern breakfast usual intake may be inversely associated with BMI.

EVALUATION AND MODELLING OF GROUND WATER QUALITY DATA OF ALLAHABAD CITY BY ENVIRONMETRIC METHODS

Water is an essential resource for all the organisms, plants and animals including the human beings. It is the backbone for agricultural and industrial sectors and all the small business units. Increase in human population and economic activities have tremendously increased the demand for large-scale suppliers of fresh water for various competing end users.The quality evaluation of water is represented in terms of physical, chemical and Biological parameters. A particular problem in the case of water quality monitoring is the complexity associated with analyzing the large number of measured variables. The data sets contain rich information about the behavior of the water resources. Multivariate statistical approaches allow deriving hidden information from the data sets about the possible influences of the environment on water quality. Classification, modeling and interpretation of monitored data are the most important steps in the assessment of water quality. The application of different multivariate statistical techniques, such as cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA) help to identify important components or factors accounting for most of the variances of a system. In the present study water samples were analyzed for various physicochemical analyses by different methods following the standards of APHA, BIS and WHO and were subjected to further statistical analysis viz. the cluster analysis to understand the similarity and differences among the various sampling stations. Three clusters were found. Cluster 1 was marked with 3 sampling locations 1, 3 & 5; Cluster-2 was marked with sampling location-2 and cluster-3 was marked with sampling location-4. Principal component analysis/factor analysis is a pattern reorganization technique which is used to assess the correlation between the observations in terms of different factors which are not observable. Observations correlated either positively or negatively, are likely to be affected by the same factors while the observations which are not correlated are influenced by different factors. In our study three factors explained 99.827% of variances. F1 marked 51.619% of total variances, high positive strong loading with TSS, TS, Temp, TDS, phosphate and moderate with electrical conductivity with loading values of 0.986, 0.970, 0.792, 0.744, 0.695, 0.701, respectively. Factor 2 marked 27.236% of the total variance with moderate positive loading with total alkalinity & temp. with loading values 0.723 & 0.606 respectively. It also explained the moderate negative loading with conductivity, TDS, and chloride with loading values -0.698, -0.690, -0.582. Factor F 3 marked 20.972 % of the variances with positive loading with PH, chloride, and phosphate with strong loading of pH 0.872 and moderate positive loading with chloride and phosphate with loading values 0.721, and 0.569 respectively.