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Record W4408707428 · doi:10.1061/jidedh.ireng-10465

Discussion of “Maximizing Irrigated Maize Productivity: Evaluating the Impact of Deficit Irrigation and Nitrogen Rates on Growth, Yield, and Water-Use Efficiency in Southwest Ethiopia”

2025· article· en· W4408707428 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Irrigation and Drainage Engineering · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsUniversity of Manitoba
FundersNew Mexico State University
KeywordsYield (engineering)IrrigationProductivityAgronomyDeficit irrigationEnvironmental scienceNitrogenMathematicsEconomicsBiologyIrrigation managementChemistry

Abstract

fetched live from OpenAlex

The discussers would like to express their appreciation to the authors of the original paper for conducting research on the effects of deficit irrigation and nitrogen rates on maize yield and water-use efficiency, with a focus on identifying the best economic benefits for farmers.The discussers have noted some key areas that require attention to improve the irrigation and nitrogen management in a corn production system.While important information can be derived from the original paper, the discussers would like to comment on the methodology used by the authors, specifically on the reference crop evapotranspiration estimation, crop coefficients, irrigation scheduling approach, and net irrigation estimates.The adoption of the Food and Agriculture Organization (FAO) Penman-Monteith equation to estimate the reference crop evapotranspiration (ETo) requires the key climatic variables such as the maximum and minimum temperatures, the maximum and minimum relative humidity, wind speed, and solar radiation.In case of missing parameters, some adjustments are proposed and detailed in Allen et al. (1998).The authors of the original paper collected sunshine duration instead of solar radiation and no transformation of the sunshine hours into solar radiation was presented in the original paper.The discussers are wondering how the FAO Penman-Monteith equation was used to estimate the ETo without the solar radiation data.The authors should have mentioned the precise ETo they used for the ETo estimation.The authors indicated using crop coefficients in combination with ETo to estimate maize actual evapotranspiration (ETc).Throughout the original paper, no maize crop coefficient was reported.Maize crop coefficients are reported as 0.70 for initial stage, 1.20 for midseason, and 0.60-0.35for late-season development stage (Allen et al. 1998).Further, Allen et al. (1998) provided key information for adjusting the midseason crop coefficients when the relative humidity differs from 45% and the wind speed is larger or smaller than 2 m=s, using the average midseason plant height to compensate for differences in aerodynamic roughness and leaf area.Similarly, end-season Kc could also be adjusted.Moreover, many

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 score0.889
Threshold uncertainty score0.133

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 studies0.0000.000
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 head0.024
GPT teacher head0.267
Teacher spread0.243 · 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