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Record W2761886967 · doi:10.2134/agronj2017.04.0208

Wheat Yield Affected by Soil Temperature and Water under Mulching in Dryland

2017· article· en· W2761886967 on OpenAlexaff
Gang He, Zhaohui Wang, Xiaolong Ma, Hongxia He, Hanbing Cao, Sen Wang, Jian Dai, Laichao Luo, Ming Huang, S. S. Malhi

Bibliographic record

VenueAgronomy Journal · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsUniversity of Alberta
FundersSpecial Fund for Agro-scientific Research in the Public InterestChina Agricultural Research SystemNational Natural Science Foundation of China
KeywordsSowingAgronomyMulchEnvironmental scienceSoil waterDryland farmingPlastic filmEvapotranspirationGrowing seasonWater-use efficiencyPlastic mulchIrrigationAgricultureSoil scienceBiologyChemistry

Abstract

fetched live from OpenAlex

Core Ideas Plastic mulch increased soil temperature and water, thus increased wheat yield. High soil temperature by plastic mulch and planting legume reduced wheat yield. Incorporation of legume increased soil temperature of next wheat growing season. Planting legume increased soil water use in summer and decreased evapotranspiration in wheat season. In the Loess Plateau of northwestern China, soil water shortage is the main factor constraining dryland wheat ( Triticum aestivum L.) production. Soil mulching is considered an effective practice to improve wheat yield due to increased soil water storage, but the information related to integrated understanding of soil temperature and water is scarce. We conducted a location‐fixed field experiment with two soil mulching (plastic mulch and planting legume) treatments to confirm the effects of soil temperature and water on wheat yield under different precipitation levels. In 2014–2015 with higher than average precipitation, plastic mulch increased soil water storage by 13% at sowing and average soil temperature by 0.4°C, which in turn increased yield by 13%, compared to the control. In 2012–2013 with extremely lower than average precipitation, the high daily maximum soil temperature during wheat reproductive period decreased grain number per spike and grain weight by 16 and 4%, respectively, thus reduced yield by 16%. For planting legume, the lower soil water storage at sowing and high daily maximum soil temperature during the wheat reproductive period decreased the number of spikes per hectare and grain weight by 29 and 4%, respectively, resulting in a 37% decrease in yield in 2012–2013. In other years with relatively higher precipitation, the proper soil temperature and extra N input under planting legume alleviated the negative impact of yield decline. Overall, planting legume did not show any benefit for wheat yield, while plastic mulch provided an opportunity for increasing wheat yield in dryland.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.214
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), 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

Citations40
Published2017
Admission routes1
Has abstractyes

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