Effect of abiotic factors on the distribution of earthworms in different land use patterns

AbstractThe distribution of earthworms is usually diverse and their numbers fluctuate in relation to the different abiotic factors and land use patterns of the soil. The aim of the present study is to determine the biodiversity, distribution and relative abundance of earthworms under different land use pattern and its relation to abiotic factors (physico-chemical properties) of the soil. Earthworms were collected from different sites on the basis of various environment niches like agriculture fields, gardens, nurseries, along the river and road side etc. by hand sorting method. Physico-chemical analysis of the soil was also done to know the important factors affecting earthworm biodiversity and distribution. Total five species of earthworms belonging to the families Megascolecidae and Octochaetidae were identified: Metaphire posthuma, Lampito mauritti, Amynthas morissi, Eutyphoeus waltoni and Eutyphoeus incommodus. M. posthuma was the most abundant species and found in all the collection sites while other four species were abundantly found in gardens and nurseries. Shannon–Wiener diversity index, Margalef species richness and Pielou’s evenness was ranged from 0.11 to 0.37, 0 to 0.6 and 0 to 0.53 respectively. Principal component analysis also proved that the abiotic factors like pH, moisture, soil texture and OC has strong positive effect on the distribution of earthworm. Earthworm biodiversity and distribution have been found to be positively correlated with type of vegetation and moisture content at the different collection sites and also varied according to soil habitat, soil tillage and land used pattern

Environmental Influence of Soil toward Effective Vermicomposting

Vermicomposting is a process by which the organic waste is converted into manure with the help of earthworms. Growth rate, onset of maturity (clitellum development), rate of reproduction (cocoon production) and population buildup of earthworm during vermicomposting have been depend upon the conditions like temperature, moisture and physico-chemical properties of the feed mixtures. Eisenia fetida was superior to other epigeic species and tolerate wide range of temperature, moisture and pH. Endogeic species produced lesser cocoon than epigeic species and cocoon production decreased at low temperature. Maintenance of temperature and moisture content is the critical step for vermicomposting. Growth and maturation of earthworms was best at 20–25°C temperature with 80–85% moisture content. Increase temperature upto 30°C accelerated growth rate of earthworms and lessened the time to sexual maturity. Earthworms can survive in the soil contaminated with heavy metals by accumulating heavy metals in their tissues

Soil properties changes earthworm diversity indices in different agro-ecosystem

Abstract Background Earthworm communities are generally very sensitive to physico-chemical properties of the soil in different agro-ecosystem i.e. cultivated or non-cultivated which directly or indirectly influence the earthworm survival. The difference in physico-chemical properties of soil at different sites contributed to the formation of population patches for earthworm species. Understanding the physico-chemical properties of soil at a particular site could facilitate the prediction of earthworm species at that site. The objective of the present study was to investigate the diversity, abundance, and distribution of earthworms in cultivated and non-cultivated agroecosystems and their physico-chemical properties affecting the earthworm diversity and abundance. Results Total 10 species of earthworms i.e. Amynthas alexandri, Amynthas morrisi, Eutyphoeus incommodus, Eutyphoeus waltoni, Metaphire birmanica, Metaphire houlleti, Metaphire posthuma, Octochaetona beatrix, Perionyx excavatus, and Polypheretima elongata, were reported. Out of all the reported species, Metaphire posthuma was found to be the most abundant earthworm species in both cultivated and non-cultivated agroecosystems with the occurrence at 56.81% sites. The Shannon-Wiener index (H), Margalef species richness index (DMg) and Pielou species evenness (E) was ranged from 0 to 0.86, 0 to 0.64 and 0.78 to 1 respectively. The principal component analysis resulted in four principal components i.e. PC1, PC2, PC3 and PC4 which contributing variance (%) of 22.96, 19.37, 14.23 and 10.10 respectively. The principal component analysis also showed that physico-chemical parameters of soil such as EC, pH, TDS, texture, OC, moisture, etc. play a critical role in earthworm distribution. Conclusion The conventional farming system has a negative effect on the earthworm diversity in the soil while the physico-chemical properties of soil also have a determinant effect on the same. Earthworms abundance in the present study have significant direct relation with soil properties at a particular site and vice versa. The diversity indices also change due to the conventional farming system which directly affects the earthworm abundance

Machine Learning-based Occupancy Estimation Using Multivariate Sensor Nodes

In buildings, a large chunk of energy is spent on heating, ventilation and air conditioning systems. One way to optimize their usage is to make them demand-driven depending on human occupancy. This paper focuses on accurately estimating the number of occupants in a room by leveraging multiple heterogeneous sensor nodes and machine learning models. For this purpose, low-cost and non-intrusive sensors such as CO 2 , temperature, illumination, sound and motion were used. The sensor nodes were deployed in a room in a star configuration and measurements were recorded for a period of four days. A regression based method is proposed for calculating the slope of CO 2 , a new feature derived from real-time CO 2 values. Supervised learning algorithms such as linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), support vector machine (SVM) and random forest (RF) were used on several different combinations of feature sets. Moreover, multiple performance metrics such as accuracy, F1 score and confusion matrix were used to evaluate the performance of our models. Experimental results demonstrate a maximum accuracy of 98.4% and a high F1 score of 0.953 for estimating the number of occupants in the room. Principal component analysis (PCA) was also applied to evaluate the performance of a dataset with reduced dimensionality

Assessment of Self-Esteem and Quality of Life in Patients with Complete Unilateral Cleft Lip and Palate Undergoing Orthodontic Treatment

Objective: To assess the self-esteem and quality of life (QOL) in patients with complete unilateral cleft lip and palate (UCLP) who were undergoing orthodontic treatment. Materials and Methods: This cross-sectional study was conducted on a total sample of 300 individuals consisted of 150 patients with UCLP (Group I) and 150 normal controls (Group II) with an age range of 10–25 years, who were undergoing comprehensive orthodontic treatment from December 2016 to December 2018. The Self Esteem and QOL were assessed using the Rosenberg Self Esteem scale (RSE) and Modified Paediatric QOL Inventory Scale (M-PQOL), respectively, in Group I and II. Results: The comparison of overall mean scores of responses to RSE questionnaires showed nonsignificant differences for all the responses and was significant only for RSE 6 and RSE 8 in the age group of 10–15 years and 21–25 years, respectively, and nonsignificant for all other questions in all the age groups. The comparison of overall mean scores of M-PQOL for the total sample showed nonsignificant differences in Group I and II for physical functioning, emotional functioning, and school functioning domain, and were highly significant differences (P ≤ 0.001) in the social functioning domain and M-PQOL 12 and M-PQOL 21. Conclusions: This study demands a definite need of a psychologist/psychiatrist among the cleft care team to counsel the patients with cleft during orthodontic treatment for motivating them to gain self-respect and acceptance in the society as certain aspects, particularly social functioning domain made them feel different from normal children because of the functional and aesthetic problems

Modulation of atrazine-induced chromosomal aberrations and cyclin-dependent kinases by aqueous extract of Roylea cinerea (D.Don) Baillon leaves in Allium cepa

Abstract Roylea cinerea (D.Don) Baillon an indigenous medicinal plant of Lamiaceae family used for the treatment of several diseases. In the present study, its aqueous (leaves) extract was tested for genoprotective action against atrazine-induced chromosomal aberrations in the root tip cells of Allium cepa. Atrazine is a herbicide of triazine class commonly used to inhibit the growth of broad leaf and grassy weeds. In order to find the concentration of atrazine that exhibits maximum toxicity, its different concentrations (1, 5 and 10 µg/mL) were tested. It was observed that 10 µg/mL concentration was more toxic as it reduced the mitotic index and also increased the chromosomal aberrations. Among all the tested concentrations of aqueous (leaves) extracts (0.25. 0.5, 1.0, 1.5 and 3.0 µg/mL), the3.0 µg/mL concentration in both modes of experiments i.e. pre and post showed a significant reduction in chromosomal aberrations induced by atrazine. To understand the mechanism of protection by plant extract on atrazine-induced chromosomal abnormalities the RT-qPCR studies were conducted to observe the expression of marker genes Cyclin-dependent kinases (CDKs) (CDKA:1, CDKB2:1 and CDKD1:1. For this, the RNA was extracted from root tips treated with extract along with atrazine by TRIzol®. It was observed that aqueous extract of Roylea cinerea (D.Don) Baillon leaves upregulated the CDKs gene expression in both the modes i.e. pre and post treatments. A critical analysis of results indicated that aqueous extract ameliorated the chromosomal aberrations caused by atrazine which may be be due to the increased expression level of CDKs genes

Ecological risk assessment of metals in roadside agricultural soils: A modified approach

<p>The threat of metal contamination of roadside agricultural soils poses severe ecological risks throughout the globe due to dual contamination by intensive agriculture and traffic-related activities. Therefore, the present study was conducted to assess ecological risks posed by metals (Cd, Co, Cr, Cu, Fe, Mn, Pb, and Zn) in intensively cultivated roadside agricultural soils of Punjab, India. The results of the contamination assessment factors <i>i.e.</i> Contamination Factor (CF) and Enrichment Factor (EF) indicated that the studied soils were moderately to highly contaminated with metals. It was observed that the Modified Risk Index (MRI), which is based upon EF, indicated the ecological risks of metals more efficiently than the traditional Ecological Risk Index (RI), which is based upon CF in the present study. The MRI values indicated that the metals posed considerable to high risk in 67.86% samples as compared to only 7.14% samples based upon RI values. Thus, MRI can be considered as a more efficient risk indicator in comparison to RI. Spatial distribution maps of MRI indicated to higher metal contamination in inner urban parts of study area due to higher traffic and industrial activities.</p