537 resultados para Cashew kernels
Resumo:
The changes occuring to cashew kernels during storage at two humidity levels - 80% to 20% with respect to organoleptic characteristics, protein content, carbohydrate content, oil content, iodine and peroxide values were studied. From the present study it is concluded that organoleptic characteristics of cashew kernels deteriorates with increase in humidity. Decrease in protein and carbohydrate content of stored cashew kernel is dependent on humidity. Humidity increased oxidative rancidification.
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Cashew kernels have high nutritive value. Upon exposure to air kernels turn rancid and their nutritive value decreases. From this study it is concluded that chemical treatment using antioxidants reduced oxidative rancidity but failed to prevent deterioration in organoleptic characteristics and decrease in protein and carbohydrate content of stored kernels.
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Since the world demand for cashew kernels has been rising steadily for several years in the past, conferring significant price increase the processing of cashew remains a highly profitable lndustry. India being the earliest and largest supplier of cashew kernels in the world market it is our prestigious obligations to reestablish her pristine monopoly. Further the added importance ot the indutry in the Socio economic context of the State of Kerala makes various measures impervative in order to bring back to the industry its pristine glory at the late sixties to give a face lift and to stabilize the industry. This present study adopts a comprehensive frame work of analysis compassing the major issues involved in the cultivation, distribution, import, processing and marketing of cashew undcr the private and public sector, migration of the industry and the financial requirements of the industry.
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Cashew is an important commodity traded across the continents and the world cashew industry is the livelihood of more than three million people worldwide, the majority of whom are womenfolk from the socially and economically backward community of the developing nations. Cashew tree was originally planted to prevent soil erosion and it was during the beginning of the 19th century that cashew kernels attained the status of a food item. Further, the cashew kernels attained the status of an international commodity with India exporting its first consignment of cashew kernels to U.S.A. in 1920. India was the first country to hit the world market with cashew as a commodity and it was she who pioneered cashew processing as an industry. For decades together India was enjoying a monopoly in the world cashew industry in the fields of raw nut production (cultivation), processing and the market share in the international trade. The liberalisation of international trade has brought in a big transition in the world of cashew. India started to benefit from the trade policy, that improved her supply positions of raw nuts from other producing countries, accelerated her growth in processing of raw nuts and exports of cashew kernels. On the other side, her domestic consumption started growing up that by the beginning of the new century, she emerged out as the world’s largest consumer of cashew kernels as well.
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In semisupervised learning (SSL), a predictive model is learn from a collection of labeled data and a typically much larger collection of unlabeled data. These paper presented a framework called multi-view point cloud regularization (MVPCR), which unifies and generalizes several semisupervised kernel methods that are based on data-dependent regularization in reproducing kernel Hilbert spaces (RKHSs). Special cases of MVPCR include coregularized least squares (CoRLS), manifold regularization (MR), and graph-based SSL. An accompanying theorem shows how to reduce any MVPCR problem to standard supervised learning with a new multi-view kernel.
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Dose kernels may be used to calculate dose distributions in radiotherapy (as described by Ahnesjo et al., 1999). Their calculation requires use of Monte Carlo methods, usually by forcing interactions to occur at a point. The Geant4 Monte Carlo toolkit provides a capability to force interactions to occur in a particular volume. We have modified this capability and created a Geant4 application to calculate dose kernels in cartesian, cylindrical, and spherical scoring systems. The simulation considers monoenergetic photons incident at the origin of a 3 m x 3 x 9 3 m water volume. Photons interact via compton, photo-electric, pair production, and rayleigh scattering. By default, Geant4 models photon interactions by sampling a physical interaction length (PIL) for each process. The process returning the smallest PIL is then considered to occur. In order to force the interaction to occur within a given length, L_FIL, we scale each PIL according to the formula: PIL_forced = L_FIL 9 (1 - exp(-PIL/PILo)) where PILo is a constant. This ensures that the process occurs within L_FIL, whilst correctly modelling the relative probability of each process. Dose kernels were produced for an incident photon energy of 0.1, 1.0, and 10.0 MeV. In order to benchmark the code, dose kernels were also calculated using the EGSnrc Edknrc user code. Identical scoring systems were used; namely, the collapsed cone approach of the Edknrc code. Relative dose difference images were then produced. Preliminary results demonstrate the ability of the Geant4 application to reproduce the shape of the dose kernels; median relative dose differences of 12.6, 5.75, and 12.6 % were found for an incident photon energy of 0.1, 1.0, and 10.0 MeV respectively.
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Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.
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A direct method of solution is presented for singular integral equations of the first kind, involving the combination of a logarithmic and a Cauchy type singularity. Two typical cages are considered, in one of which the range of integration is a Single finite interval and, in the other, the range of integration is a union of disjoint finite intervals. More such general equations associated with a finite number (greater than two) of finite, disjoint, intervals can also be handled by the technique employed here.
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Spectral data were collected of intact and ground kernels using 3 instruments (using Si-PbS, Si, and InGaAs detectors), operating over different areas of the spectrum (between 400 and 2500 nm) and employing transmittance, interactance, and reflectance sample presentation strategies. Kernels were assessed on the basis of oil and water content, and with respect to the defect categories of insect damage, rancidity, discoloration, mould growth, germination, and decomposition. Predictive model performance statistics for oil content models were acceptable on all instruments (R2 > 0.98; RMSECV < 2.5%, which is similar to reference analysis error), although that for the instrument employing reflectance optics was inferior to models developed for the instruments employing transmission optics. The spectral positions for calibration coefficients were consistent with absorbance due to the third overtones of CH2 stretching. Calibration models for moisture content in ground samples were acceptable on all instruments (R2 > 0.97; RMSECV < 0.2%), whereas calibration models for intact kernels were relatively poor. Calibration coefficients were more highly weighted around 1360, 740 and 840 nm, consistent with absorbance due to overtones of O-H stretching and combination. Intact kernels with brown centres or rancidity could be discriminated from each other and from sound kernels using principal component analysis. Part kernels affected by insect damage, discoloration, mould growth, germination, and decomposition could be discriminated from sound kernels. However, discrimination among these defect categories was not distinct and could not be validated on an independent set. It is concluded that there is good potential for a low cost Si photodiode array instrument to be employed to identify some quality defects of intact macadamia kernels and to quantify oil and moisture content of kernels in the process laboratory and for oil content in-line. Further work is required to examine the robustness of predictive models across different populations, including growing districts, cultivars and times of harvest.
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Maize is a highly important crop to many countries around the world, through the sale of the maize crop to domestic processors and subsequent production of maize products and also provides a staple food to subsistance farms in undeveloped countries. In many countries, there have been long-term research efforts to develop a suitable hardness method that could assist the maize industry in improving efficiency in processing as well as possibly providing a quality specification for maize growers, which could attract a premium. This paper focuses specifically on hardness and reviews a number of methodologies as well as important biochemical aspects of maize that contribute to maize hardness used internationally. Numerous foods are produced from maize, and hardness has been described as having an impact on food quality. However, the basis of hardness and measurement of hardness are very general and would apply to any use of maize from any country. From the published literature, it would appear that one of the simpler methods used to measure hardness is a grinding step followed by a sieving step, using multiple sieve sizes. This would allow the range in hardness within a sample as well as average particle size and/or coarse/fine ratio to be calculated. Any of these parameters could easily be used as reference values for the development of near-infrared (NIR) spectroscopy calibrations. The development of precise NIR calibrations will provide an excellent tool for breeders, handlers, and processors to deliver specific cultivars in the case of growers and bulk loads in the case of handlers, thereby ensuring the most efficient use of maize by domestic and international processors. This paper also considers previous research describing the biochemical aspects of maize that have been related to maize hardness. Both starch and protein affect hardness, with most research focusing on the storage proteins (zeins). Both the content and composition of the zein fractions affect hardness. Genotypes and growing environment influence the final protein and starch content and. to a lesser extent, composition. However, hardness is a highly heritable trait and, hence, when a desirable level of hardness is finally agreed upon, the breeders will quickly be able to produce material with the hardness levels required by the industry.
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Each Agrilink kit has been designed to be both comprehensive and practical. As the kits are arranged to answer questions of increasing complexity, they are useful references for both new and experienced producers of specific crops. Agrilink integrates the technology of horticultural production with the management of horticultural enterprises. REPRINT INFORMATION - PLEASE READ! For updated information please call 13 25 23 or visit the website www.deedi.qld.gov.au (Select: Queensland Industries – Agriculture link) This publication has been reprinted as a digital book without any changes to the content published in 1999. We advise readers to take particular note of the areas most likely to be out-of-date and so requiring further research: see detailed information on first page of the kit. Even with these limitations we believe this information kit provides important and valuable information for intending and existing growers. This publication was last revised in 1999. The information is not current and the accuracy of the information cannot be guaranteed by the State of Queensland. This information has been made available to assist users to identify issues involved in the production of cashews. This information is not to be used or relied upon by users for any purpose which may expose the user or any other person to loss or damage. Users should conduct their own inquiries and rely on their own independent professional advice. While every care has been taken in preparing this publication, the State of Queensland accepts no responsibility for decisions or actions taken as a result of any data, information, statement or advice, expressed or implied, contained in this publication.
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Interest in cashew production in Australia has been stimulated by domestic and export market opportunities and suitability of large areas of tropical Australia. Economic models indicate that cashew production is profitable at 2.8 t ha-1 nut-in-shell (NIS). Balanced plant nutrition is essential to achieve economic yields in Australia, with nitrogen (N) of particular importance because of its capacity to modify growth, affect nut yield and cause environmental degradation through soil acidification and off-site contamination. The study on a commercial cashew plantation at Dimbulah, Australia, investigated the effect of N rate and timing on cashew growth, nut production, N leaching and soil chemical properties over five growth cycles (1995-1999). Nitrogen was applied during the main periods of vegetative (December-April) and reproductive (June-October) growth. Commercial NIS yields (up to 4.4 t ha-1 from individual trees) that exceeded the economic threshold of 2.8 t ha-1 were achieved. The yield response was mainly determined by canopy size as mean nut weight, panicle density and nuts per panicle were largely unaffected by N treatments. Nitrogen application confined to the main period of vegetative growth (December-April) produced a seasonal growth pattern that corresponded most consistently with highest NIS yield. This N timing also reduced late season flowering and undesirable post-November nut drop. Higher yields were not produced at N rates greater than 17 g m-2 of canopy surface area (equating to 210 kg N ha-1 for mature size trees). High yields were attained when N concentrations in Mveg leaves in May-June were about 2%, but this assessment occurs at a time when it is not feasible to correct N deficiency. The Mflor leaf of the preceding November, used in conjunction with the Mveg leaf, was proposed as a diagnostic tool to guide N rate decisions. Leaching of nitrate-N and acidification of the soil profile was recorded to 0.9 m. This is an environmental and sustainability hazard, and demonstrates that improved methods of N management are required.
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BACKGROUND Kernel brown centres in macadamia are a defect causing internal discolouration of kernels. This study investigates the effect on the incidence of brown centres in raw kernel after maintaining high moisture content in macadamia nuts-in-shell stored at temperatures of 30°C, 35°C, 40°C and 45°C. RESULTS Brown centres of raw kernel increased with nuts-in-shell storage time and temperature when high moisture content was maintained by sealing in polyethylene bags. Almost all kernels developed the defect when kept at high moisture content for 5 days at 45°C, and 44% developed brown centres after only 2 days of storage at high moisture content at 45°C. This contrasted with only 0.76% when stored for 2 days at 45°C but allowed to dry in open-mesh bags. At storage temperatures below 45°C, there were fewer brown centres, but there were still significant differences between those stored at high moisture content and those allowed to dry (P < 0.05). CONCLUSION Maintenance of high moisture content during macadamia nuts-in-shell storage increases the incidence of brown centres in raw kernels and the defect increases with time and temperature. On-farm nuts-in-shell drying and storage practices should rapidly remove moisture to reduce losses. Ideally, nuts-in-shell should not be stored at high moisture content on-farm at temperatures over 30°C. © 2013 Society of Chemical Industry