Bending rigidity of thermally bonded nonwoven structures

Bending rigidity is one of the most important parameters affecting the fabric drape characteristics. In this research work, classic Freeston and Platt model, describing the bending behaviour of nonwovens specifically for thermally bonded, has been modified by accounting for number of bonds replacing the number of fibres in a unit cell. These bonds are responsible for constraining the relative fiber motion in the nonwoven structure. The anisotropic characteristics of thermally bonded nonwovens are revealed by analysing the bending properties in various test directions. In general, there is a good agreement between the bending rigidity values obtained from modified Freeston and Platt model and experimental work. However, the classic Freeston and Platt model has overestimated the bending rigidity of thermally bonded nonwoven structures. Furthermore, the effect of main fiber parameters including volume fraction, modulus and orientation characteristics has been investigated on the bending rigidity of thermally bonded nonwovens.     

Influence of planting date on growth, artemisinin yield, seed and oil yield of Artemisia annua L. under temperate climatic conditions

Artemisia annua L. is an annual aromatic antibacterial herb, with effective antimalarial properties due to the presence of artemisinin. The intention of the present study was to establish plant survival, growth attributes, yield attributes and artemisinin yield of A. annua cv CIM - Arogya with different transplanting months in two cropping seasons (March 2005-February 2006 and March 2006-February 2007) under temperate climatic conditions of Himalaya, India. Artemisinin yield in the dried leaves was found maximum amongst the plants that were transplanted in March (24.39 kg ha⁻¹) and minimum in those transplanted in November (3.39 kg ha⁻¹).     

A study on the effect of cadmium on the antioxidative defense system and alteration in different functional groups in castor bean and Indian mustard

The present study was planned to delineate the role of antioxidants and different functional groups of Ricinus communis and Brassica juncea in the tolerance mechanisms toward cadmium (Cd) for phytoremediation. Application of Cd caused a reduction in dry biomass of 53.84% and 26.58% in root and 45.33% and 33.84% in shoots of B. juncea and R. communis, respectively. Antioxidant enzymes, namely superoxide dismutase, catalase, ascorbate peroxidase, guaiacol peroxidase, glutathione reductase and glutathione-S-transferase, and metabolites (proline) increased in both the species due to Cd exposure. The metal caused substantial changes in the functional groups present in the roots and leaves of the plants. A number of new peaks appeared in the Cd-treated plants, which indicate the production of the compounds responsible for the metal tolerance of these plants. R. communis has been found to possess a good antioxidant defense system against Cd stress and may be used for the phytoremediation of metal-contaminated soils in place of edible crops, which enhance the risk of contaminating the food chain. It has been observed that R. communis accumulated 213.39 and 335.68 mg Cd in roots and shoots, respectively, whereas B. juncea accumulated 28.19 and 310.15 mg Cd in the roots and shoots, respectively.     

Micropropagation of mature Terminalia catappa (Indian Almond), a medicinally important forest tree

We report an efficient in vitro propagation method for Terminalia catappa using nodal segments of a 15-year-old mature tree. The nodal segments were cultured on MS medium supplemented with 6-benzyladenine (BA; 0.5–3.0 mg l⁻¹) or Kinetin (Kn; 0.5–3.0 mg l⁻¹) for bud breaking and multiple shoot induction. About 85% of the explant responded (2.8 ± 0.41 shoots per node with 2.7 ± 0.14 cm length) within 15 days of inoculation in Murashige and Skoog medium fortified with 2.0 mg l⁻¹ of BA. Further shoot multiplication was achieved by repeated transfer of mother explants and subculturing of in vitro-produced shoots on medium supplemented with various concentrations of BA (0.25–1.5 mg l⁻¹) or Kn (0.25–1.5 mg l⁻¹) or on their combinations. Optimal number of shoots and shoot length were recorded on MS medium supplemented with 0.25 mg l⁻¹ of BA and 0.25 mg l⁻¹ of Kn. The multiplied shoots were used for ex vitro rooting after treatment for 4 min with indole-3-butyric acid (IBA; 50–500 mg l⁻¹) or α-naphthalene acetic acid (NAA; 50–500 mg l⁻¹). About 80% of the shoots treated with 200 mg l⁻¹ of IBA produced ex vitro roots with an average of 2.8 roots per shoot. Nearly 75% of these plantlets could be acclimatized within 5 weeks and successfully established in the field. This is the first report on micropropagation of T. catappa, which can be applied for further genetic transformation assays and pharmaceutical purposes.     

Effect of bypass fat supplementation on productive performance and blood biochemical profile in lactating Murrah (Bubalus bubalis) buffaloes

The study investigated the effect of dietary supplementation of bypass fat on productive performance and blood biochemical profile of lactating Murrah buffaloes (Bubalus bubalis). Fifteen multiparous buffaloes (2-4 lactation) of early to mid lactation were divided in three homogenous groups T(1) (control), T(2), and T(3) of five each. The animals in T(1) were fed with a basal diet consisting of a concentrate mixture, green sorghum, and wheat straw as per requirements, while the animals in group T(2) and T(3) were fed with same ration supplemented with 0.7 % (100?g/day) and 1.4 % (200?g/day) bypass fat (on dry matter intake (DMI) basis), respectively. The feed intake, milk yield, and milk composition were not influenced by supplemental bypass fat. However, fat-corrected milk (6.5 %) yield was higher (P?相似文献   

Microbial decomposition of soil organic matter is mediated by quality and quantity of crop residues: mechanisms and thresholds

Crop residue quality and quantity have contrasting effects on soil organic matter (SOM) decomposition, but the mechanisms explaining such priming effect (PE) are still elusive. To reveal the role of residue quality and quantity in SOM priming, we applied two rates (5.4–10.8 g kg^?1) of ¹³C-labeled wheat residues (separately: leaves, stems, roots) to soil and incubated for 120 days. To distinguish PE mechanisms, labeled C was traced in CO₂ efflux and in microbial biomass and enzyme activities (involved in C, N, and P cycles) were measured during the incubation period. Regardless of residue type, PE intensity declined with increasing C additions. Roots were least mineralized but caused up to 60% higher PE compared to leaves or stems. During intensive residue mineralization (first 2–3 weeks), the low or negative PE resulted from pool substitution. Thereafter (15–60 days), a large decline in microbial biomass along with increased enzyme activity suggested that microbial necromass served as SOM primer. Finally, incorporation of SOM-derived C into remaining microbial biomass corresponded to increased enzyme activity, which is indicative of SOM cometabolism. Both PE and enzyme activities were primarily correlated with residue-metabolizing soil microorganisms. A unifying model demonstrated that PE was a function of residue mineralization, with thresholds for strong PE increase of up to 20% root, 44% stem, and 51% leaf mineralization. Thus, root mineralization has the lowest threshold for a strong PE increase. Our study emphasizes the role of residue-feeding microorganisms as active players in the PE, which are mediated by quality and quantity of crop residue additions.     

Estimating carbon sequestration potential of existing agroforestry systems in India

India launched National Agroforestry Policy on 10th February, 2014 which has the potential to substantially reduce poverty in rural India and revive wood based industry, besides integrating food production with environmental services. The policy is not only crucial to India’s ambitious goal of achieving 33 per cent forest and tree cover but also to mitigate GHG emissions from agriculture sector. Dynamic CO2FIX-v3.1 model has been used to estimate the carbon sequestration potential (CSP) of existing agroforestry systems (AFS) for simulation period of 30 years in twenty six districts from ten selected states of India. The observed number of trees on farmers’ field in these districts varied from 1.81 to 204 per hectare with an average value of 19.44 trees per hectare. The biomass in the tree component varied from 0.58 to 48.50 Mg DM ha^?1, whereas, the total biomass (tree and crop) ranged from 4.96 to 58.96 Mg DM ha^?1. The soil organic carbon ranged from 4.28 to 24.13 Mg C ha^?1. The average estimated carbon sequestration potential of the AFS, representing varying edapho-climatic conditions, on farmers field at country level was 0.21 Mg C ha^?1yr^?1. At national level, existing AFS are estimated to mitigate 109.34 million tons CO₂ annually, which may offsets one-third (33 %) of the total GHG emissions from agriculture sector.     

Applying machine learning on sensor data for irrigation recommendations: revealing the agronomist’s tacit knowledge

Jojoba Israel is a world-leading producer of Jojoba products, whose orchards are covered with sensors that collect soil moisture data for monitoring plant needs at real-time. Based on these data, the company’s agronomist defines a weekly irrigation plan. In addition, data on weather, irrigation, and yield are recorded from other sources (e.g. meteorological station and irrigation-plan records). However, so far, there has been no attempt to use the entire set of collected data to reveal insights and interesting relationships between different variables, such as soil, weather, irrigation characteristics, and resulting yield. By integrating and utilizing data from different sources, our research aims at using the collected data not only for monitoring and controlling the crop, but also for predicting irrigation recommendations. In particular, a dataset was constructed by integrating data collected over almost two years from 22 soil-sensors spread in four major plots (which are divided into 28 subplots and eight irrigation groups), from a meteorological station, and from actual irrigation records. Different regression and classification algorithms were applied on this dataset to develop models that were able to predict the weekly irrigation plan as recommended by the agronomist. The models were developed using eight different subsets of variables to determine which variables consistently contributed to prediction accuracy. By comparing the resulting models, it was shown that the best regression model was Gradient Boosted Regression Trees, with 93% accuracy, and the best classification model was the Boosted Tree Classifier, with 95% accuracy (on the test-set). Data that were not contributing to the model prediction success rate were identified as well. The resulting model can significantly facilitate the agronomist’s irrigation planning process. In addition, the potential of applying machine learning on the company data for yield and disease prediction is discussed.     

Fusarium equiseti is associated with the wilt and dieback of Aquilaria malaccensis in Northeast India

Aquilaria malaccensis, categorized by IUCN as globally vulnerable, is in high demand in the Middle East and Asian markets for its unique resinous agarwood. In August 2015, symptoms of dieback were observed on A. malaccensis trees planted in the Medicinal and Aromatic Plant Garden, Panbari, Golaghat of the Assam Forest Department. The entire crowns of 70 trees showed complete leaf loss and severe dieback. Rotting at the collar region and of roots was also observed. Isolation from the infected roots consistently yielded Fusarium equiseti identified following standard laboratory procedures and analysis of the internal transcribed spacer (ITS) sequence of the ribosomal DNA. Symptoms of wilt, dieback and root rot were observed on 5‐month‐old Aquilaria seedlings 25 days after inoculation with the isolated fungus. This paper is the first report of F. equiseti causing wilt and dieback of A. malaccensis.