MétaCan
Menu
Back to cohort
Record W2155438700 · doi:10.6000/1927-5129.2013.09.09

Quality Attributes of Immature Fruit of Different Mango Varieties

2013· article· en· W2155438700 on OpenAlexvenueno aff
M. H. Leghari, Saghir Ahmed Sheikh, Noor-un-Nisa Memon, Aijaz Hussain Soomro, Aijaz Ali Khooharo

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPotassiumChemistryZincSodiumPulp (tooth)MagnesiumManganeseCalciumHorticultureNutrientMoistureVitamin CFood scienceBiology

Abstract

fetched live from OpenAlex

The study was carried out to evaluate quality attributes of immature fruits of four commercially grown varieties of mango namely Sindhri, Chaunsa, Langra and Desi. The immature mango fruits were collected from basin of mango tree in the end of April followed by washing, surface drying and extraction of fruit pulp. The extracted fruit pulp was assessed for pH, TSS, moisture and ash percentage, acidity, vitamin C, fat, protein and sugars. Besides, minerals including sodium, calcium, potassium, magnesium, zinc, iron, copper, chromium, and manganese were also determined. On the basis of varietal comparison Sindhri had more moisture (88.60%), ash and fat (0.60%) each, total sugars (6.99%) and reducing sugars (2.78%) as compared to rest of the varieties. However TSS (9.35%), protein (0.71%), and non reducing sugars (4.86%) were recorded the highest in Langra variety. Only the Chaunsa variety had maximum pH of 3.01 and vitamin-C (27.16 mg 100g-1). Regarding mineral elements, Desi was found potential in terms of sodium (453.93 mg kg-1), calcium (403.79 mg kg-1), Zinc (3.47 mg kg-1) and iron (5.95 mg kg-1). The zinc and iron was at par with the results obtained from Langra. However, potassium (904.58 mg kg-1) and copper (2.58 mg kg-1) were observed the highest in Langra, magnesium (78.09 mg kg-1) in Chaunsa and manganese (2.43 mg kg-1) in Sindhri.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.255

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 head0.040
GPT teacher head0.249
Teacher spread0.209 · 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 designBench or experimental
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

Citations8
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Basic & Applied SciencesSame topicPlant Physiology and Cultivation StudiesFrench-language works237,207