Synthetic colorants such as metanil yellow, lead chromate, Acid orange 7, Sudan red; rhizomes of related Curcuma sp. besides spent turmeric, starch, chalk and yellow soapstone are the main adulterants in traded turmeric while synthetic curcumin is an adulterant of natural curcumin. Both branded products as well as the produce from the unorganized sector are found adulterated. The adulterants, added either to increase the bulk, improve the colour and appearance or enhance the profit margin, often result in corroding the biological efficacy of the commodity and eroding the public impression besides posing health risks to the consumers. Various physical, chemical and PCR based methods are available to detect the adulterants in traded turmeric. While chemical methods are suited to detect the synthetic adulterants and spent turmeric, DNA based methods are the best options for detecting the biological adulterants (except spent turmeric) in the commodity. Along with adopting a supply chain system and quality linked pricing in turmeric trade, commercial adulteration diagnostic kits, if they can be developed and deployed, will be a very convenient way to ensure the quality of the traded produce.

Statistical tools such as analysis of variance, correlation, path coefficient analysis, Scott-Knott test and principal component analysis were used in the present study to characterize black pepper verities/hybrids for spike and berry traits. ANOVA indicated that fifteen traits under study were statistically significant. Traits like fresh pericarp weight and dry pericarp weight showed high positive correlation (>0.95) with spike weight. Path coefficient analysis revealed that berry weight and seed size are contributing directly to spike weight. Scott-Knott test identified Panniyur-1 and Nedumchola as the most contrasting genotypes for most number of traits studied. Based on Principal Component Analysis (PCA), first three principal components had an eigen value above unity and explained 88 per cent of cumulative variation. Principal component PC-1 accounted for maximum variation of about 42.4 percent which discriminated the genotypes based on fresh berry weight, dry seed weight and fresh pericarp weight. These traits serve as the selection criteria for improvement of yield in black pepper.

Black pepper is a very important spice and medicinal crop of India. The country produces about 62,000 metric tonnes of black pepper annually, of which 10–12% is exported. Kerala with an area of 82,761 ha under the crop is a leading producer of the spice in India. It is grown under varied agro-ecologies in the state ranging from sea-level to High Ranges. The crop, a climber, is cultivated either as a monocrop trailed on different multipurpose support trees (called “standards”, e.g. Ailanthus triphysa, Erythrina indica, Garuga pinnata, Gliricidia sepium etc.) or in the homesteads along with assorted trees like Areca catechu, Cocos nucifera, Artocarpus heterophyllus, Mangifera indica and the like. Trailing a sciophytic (shade-loving) climber on woody perennial support trees makes it a unique agronomic system and an excellent example of agroforestry. Attractive prices, albeit fluctuations, long shelf-life of the produce, and the ability to provide a range of ecosystem services including supporting and regulatory services (e.g. carbon sequestration and soil fertility enrichment), make black pepper production an attractive land use option in Kerala. This paper reviews the literature on agroecology of the crop with particular reference to Kerala.

The effect of hurtful toxins in the air on human wellbeing is an immense territory of exploration, forestalling or Controlling, and furthermore checking the poison is one of the important problems in daily life. Air pollution is caused by smoke from manufacturing industry, vehicles etc. Due to this more side effects and diseases are caused to human beings. This paper predicts the air pollution using IoT with machine learning algorithms with high accuracy. These sensors measure the air quality and store the sensed data in a cloud. The machine learning analysis the data which is send by the IoT devices. The accuracy is very high when compared with the existing algorithms. KeywordsAir pollution, NodeMCU, Air Quality Index, Data preprocessing, Regressive Model.

Diabetes is a type of metabolic disease identified by unstable blood glucose level due to the defect in the human body and the body does not make insulin. Diabetes is created due to the defect in the metabolism of converting glucose to energy in the blood. Type 1 diabetes is caused due to lack of generation of insulin in human blood and Type 2 diabetes is caused due to resistance to insulin action, which leads to several other diseases like foot ulcer and severe wounds in the human foot or other parts of the body. The main aim of the research study presented here is to diagnose Type 2 diabetes. While the traditional method of identifying diabetes does not provide effective results, more reliable and research on this perspective has gained potential importance. Based on the analysis noted down from the heat changes in the human foot, we present a study to diagnose diabetes is done in the human body is done using TEG sensors. Imbalanced glucose level affects the performance of the nerves system, which leads to slower response for temperature change in the foot surface. The study in this paper uses Thermo Electric Generator (TEG) sensor to analyse the temperature changes in the foot, which could represent the level of diabetes caused in the patient body. The signals extracted from the TEG sensor were collected and processed using signal analysis algorithm using MATLAB software. The results obtained were more promising and compared with several other existing schemes. The result was analysed using physicians who have agreed on the inference obtained using the study.

In recent year, cloud computing provides consistent, customized and quality service to the cloud user for securing the data in cloud storage. Currently, numerous business organization generate enormous volume of insightful information for instance, employee personal data, economic related information and data related to hospital records. Subsequently, digital information related to multinational were increased. so, they avoid storing their information locally and they planned to outsource their data to cloud environment. On the other hand, the significant worry to the data owner is to deliver security and truthfulness their outsourced data. Our proposed system takes this issue as a challenging task and provide security to the out sourced data in cloud environment by using Remote Data auditing (RDA) Technique. In earlier days most auditing techniques only focused on static data and not supported for dynamic data. In this paper, we proposed a professional RDA technique using Data Privacy Preserving Protocol for cloud storage system. Our system also designs system model which support the dynamic data operation in the cloud environment. The experimental result shows that proposed model for auditing protocol is safe and extremely efficient as compare to existing auditing techniques.

DNA barcoding in plants involves the selection and sequencing of DNA regions as a tool for species identification. Here we have attempted to discriminate Piper nigrum L., black pepper of commerce, from its related adulterant species viz., Piper attenuatum Buch-Ham, Piper galeatum (Miq.) C. DC. using rbcL, psbA-trnH, rpoC1, and matK as barcode loci. No single barcoding locus could discriminate all the three species of Piper. However rbcL and rpoC1 could differentiate P. attenuatum from P. nigrum and Piper galeatum while psbA-trnH differentiated P. galeatum from P. nigrum and P. attenuatum. Two locus barcode approach proved better when compared to single locus in discriminating Piper species. The coding that. gene with non coding psbA-trnH spacer was preferred than the coding rpoC1 + psbA-trnH combination in the present study.

A reliable and efficient protocol for isolation and amplification of genomic DNA from dried mace of Myristica fragrans, was developed. The yield of genomic DNA was 231.4 mu g and 306.8 mu g g(-1), respectively for the samples procured from the farm and market. The absorbance ratio at A260/A280 was greater than 1.8 indicating the good quality of DNA. Complete restriction digestion and PCR amplification of genomic DNA further confirmed the quality of isolated DNA.

Myristica fragrans mace, an economically important traded spice is being adulterated with mace of M. malabarica, a closely related species. Identification of the genuine mace from its adulterant is difficult owing to the loss of diagnostic morphological characters on drying and storage. Four DNA barcoding loci viz., rbcL, matK, psbA-trnH and Internal Transcribed Spacer (ITS) are compared to analyse Myristica malabarica adulteration in traded Myristica fragrans mace samples. The potential of psbA-trnH as the best barcode over other loci in authentication of M. fragrans mace was established by its amplification and sequencing success, high interspecific variation and presence of polymorphic sites. Sixty polymorphic sites and 9 indel regions in psbA-trnH locus specific to M. malabarica are found in three out of the five market samples studied, thereby confirming the adulteration of traded M. fragrans mace with M. malabarica. (C) 2016 Elsevier Ltd. All rights reserved.

A unique nutmeg accession having normal fruit, but with rudimentary, sterile seed and finely packed mace having a human brain like appearance was collected from a farmer’s garden from the secondary center of domestication of the crop and characterized. Seed (female) sterility in a dioecious or emerging monoecious plant like nutmeg is hitherto not recorded and is a novelty. This unique accession is conserved at the germplasm conservatory of tree spices at the ICAR-Indian Institute of Spices Research, Kozhikode, Kerala.

Seventy one cinnamon accessions studed for variability and association revealed high coefficient of variation for dry and fresh bark yield, bark oleoresin, leaf oil, bark oil, leaf size index and percentage recovery of bark. Association analysis revealed significant correlation of fresh weight of bark and leaf oil with dry hark yield. Bark oil was negatively associated with leaf oil.

IISR Varada (Acc, 64) developed at the Indian Institute of Spices Research, Calicut and recomm~lld.ed for release by the All India Coordinated Research Projet on Spices, is a good quality, high yielding, ginger (Zingiber officinale) variety developed through germplasm selection, Maturing in 200 days, the variety has an average yield of 22,66 tlha (fresh), low fibre and dry recovery of 20,7 per cent. The dry ginger of this variety is less prone to storage insect damage,

In order to elucidate a gene regulation model for biosynthesis of the major pharmaceutical compound curcumin in turmeric (Curcuma longa), a precise knowledge of sequence diversity and expression patterns of key genes of the pathway is necessary. Polyketide synthases (PKS) being the key enzymes involved in the pathway, attempts were made to mine the major PKS from the transcriptome of the Curcuma rhizome. Comparative expression of candidate genes vis a vis curcumin content across accessions, various developmental stages, environmental conditions and management practices was analyzed. The full length cDNA of a novel PKS, showing higher transcript abundance and significant correlation with curcumin content was amplified and bioinformatic analysis was carried out. The present study could mine 63 transcripts of PKS from Curcuma transcriptome and among them, a novel transcript (ClPKS11) showed 69 fold higher expression in a high curcumin variety. The expression of ClPKS11 correlated with curcumin content under different experimental conditions. It contained an open reading frame of 1176bp, encoding a polypeptide of 391 amino acids with a predicted molecular mass of 42.9kDa. CLPKS11 showed maximum identity of 72% with CURS3 (curcumin synthase 3) and exhibited amino acid differences in the substrate binding pocket, cyclization pocket and geometry shapers surrounding the active site. Molecular docking studies indicated a high substrate affinity for CLPKS11. Intrinsic levels of ClPKS11 may be used as a marker for screening for curcumin, as it shows divergent expressions in high and low curcumin genotypes that are detectable even at the very early developmental stage. The present study also laid the foundation for over expression of ClPKS11 in turmeric to investigate its physiological role in curcumin biosynthesis.

An accession of nutmeg IC-537218 derived from an open pollinated seedling progeny of a high yielding tree from Burliar, Nilgiris, Tamil Nadu, was evaluated under a farmer participatory mode at three locations in two states, Kerala and Tamil Nadu, for yield characters, for 13 years and this accession was found superior for mace and nutmeg yield over the existing variety, IISR Vishwashree, in all the yield parameters studied. The tree is a pure female which flowers profusly and bears oblong shaped yellow fruits. The aril is thick and covers the entire seed and is dark red in colour. The nut is bold and brownish black in colour. The mace and nut of the new variety is rich in sabinene.

The kanamycin sensitivity for callus growth was studied in vitro in a cultivar of black pepper ( Piper nigrum ) using cotyledons as explants to investigate the suitability of kanamycin resistance as a selectable marker for Agrobacterium mediated transformation. Callus formation was completely inhibited at 50 ug ml-1 and above concentrations of kanamycin suggesting that 50 ug ml-1 is the minimum concentration needed to select the transformed tissues.