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Record W2201432439

Cashew Research in India: Achievements and Strategies

2014· article· en· W2201432439 on OpenAlexaboutno aff
Pushpendra Saroj, T. R. Rupa

Bibliographic record

VenueProgressive Horticulture · 2014
Typearticle
Languageen
FieldMedicine
TopicGinkgo biloba and Cashew Applications
Canadian institutionsnot available
Fundersnot available
KeywordsLakhAnacardiumTamilGeographyProductivitySocioeconomicsNon-invasive ventilationAgroforestryAgricultureBiologyEconomic growthHorticultureArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The cashew tree (Anacardium occidentale L.), though native of Brazil, has acclimatized well in India. Cashew was introduced to India by Portuguese travellers during 16th Century for afforestation and soil conservation purpose. In India, cashew is grown along the coastal regions mainly in Maharashtra, Goa, Karnataka and Kerala in the West Coast and Tamil Nadu, Andhra Pradesh, Odisha and West Bengal in the east coast. With the establishment of All India Co-ordinated Research Project on Cashew, Its cultivation has also been extended in non-traditional areas such as Bastar region of Chhattisgarh and Kolar (Plains) region of Karnataka, Gujarat, Jharkhand and in NEH region. India is the first country in the world to exploit the international trade of cashew kernels in the early part of 20th Century. India exports 1.312 lakh tonnes of cashew kernels per annum to over 65 countries and is a leading trader for over a century. The major countries that import Indian cashew are United States of America, Netherlands, United Kingdom, United Arab Emirates, Japan, France, Saudi Arabia, Spain, Russia, Germany, Canada and Greece. Globally, India's share in the cashew area and production is 20 per cent and 16 per cent, respectively. During the year 2012–13, total production of cashew in the country was 7.28 lakh tonnes from 9.82 lakh ha of land with a productivity of 772 kg/ha. The productivity is almost standstill over the few years. This needs introspection to identify the gaps and sharpen our approaches to meet the needs of future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.295

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.386
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2014
Admission routes1
Has abstractyes

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