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Record W2749271318 · doi:10.5539/jas.v9n9p182

The Effect of Irrigation Intervals on the Growth and Yield of Quinoa Crop and Its Components

2017· article· en· W2749271318 on OpenAlex
Abdullah M. Algosaibi, Ayman E. Badran, Abdulrahman M. Almadini, Mohammed M. El-Garawany

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsChenopodium quinoaIrrigationRandomized block designAgronomyCropStrawMathematicsWater contentSoil waterHorticultureBiology

Abstract

fetched live from OpenAlex

This experiment was conducted to study the effect of irrigation intervals on growth, yield and its components and some of the chemical characteristics of the soil after the harvest of quinoa (Chenopodium quinoa willd) plant. Three treatments were used as follow: T1 (twice irrigation every week, which is the common in the region), T2 (once irrigation every week) and T3 (twice irrigation every two weeks) using in a randomized complete block design with four replicates. The crop coefficient (Kc) value differed according to the stage of growth where the results showed that the T2 treatment gave the highest mean in all the studied traits followed by the T3 treatment in all traits except the number of seed/m2. The results also confirmed that the increase in water reduced the agronomic traits such as harvest index, number of seeds and yield of seeds and straw/m2. Also it showed that the pH values in soils were not significantly affected by irrigation, while Ec significantly affected. Correlation coefficient was negative with the most traits and low with the number of grain (0.34) under overall studied treatments which confirms that quinoa is a plant that needs limited amounts of irrigation water. On the other hand there was positive strong correlation between the harvest index and grain yield (0.92). The results showed that moisture stress treatments increased the concentration of the ionic, NH4-N and NO3-N significantly compared to soils which do not have moisture stress (T1, T2). We assume that the development based on Kc during growth-stages helps in irrigation management and provides precise water applications for quinoa plant. These results indicate that the water requirements of quinoa plant are limited and that quinoa plant growth is not affected by the lack of irrigation water on the crop and its qualities.

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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.558
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.230
Teacher spread0.206 · 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