MétaCan
Menu
Back to cohort
Record W4403509065 · doi:10.1016/j.agwat.2024.109105

Plastic mulching enhances maize yield and water productivity by improving root characteristics, green leaf area, and photosynthesis for different cultivars in dryland regions

2024· article· en· W4403509065 on OpenAlexaff
Lihong Wu, Lina Wu, Xi Zhang, Dianyuan Ding, Hao Feng, Kadambot H. M. Siddique, De Li Liu, Bin Wang

Bibliographic record

VenueAgricultural Water Management · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCultivarAgronomyMulchPhotosynthesisYield (engineering)ProductivityEnvironmental scienceWater-use efficiencyWater useBiologyMathematicsBotanyIrrigationMaterials science

Abstract

fetched live from OpenAlex

Uneven precipitation during the growing season and frequent seasonal droughts on the Loess Plateau in Northwest China adversely affect crop production and water use efficiency. While plastic mulching (PM) has been used to alleviate water stress, few studies have examined the traits maize cultivars need to adapt to the altered water environment under PM and achieve high yields. A two-year field experiment was conducted to assess the root characteristics and aboveground growth traits of three widely used high-yielding maize cultivars—Zhengdan 958 (ZD), Huanong 138 (HN), Heboshi 122 (HBS)—under no mulching (NM) and PM conditions. Among the three cultivars, HBS had the highest root system indices—root length density (RLD), root surface area density (RSD), and root biomass—in the topsoil (0–40 cm), followed by ZD and HN under both NM and PM conditions. Under NM, HBS_NM treatment exhibited strong water absorption, improving photosynthesis and yield, making it suitable for drought conditions. Under PM, topsoil moisture increased significantly, with root system indices increasing by 22.5–36.1 % for RLD, 30.2–36.1 % for RSD, and 25.2–36.5 % for root biomass across the cultivars compared to NM. While ZD_PM did not have the highest root system indices under PM, it exhibited higher green leaf area index (4.5–7.5 %), chlorophyll content (2.8–8.6 %), and photosynthetic rate (6.0–14.5 %), resulting in the highest aboveground biomass and yield among the treatments. These findings suggest ZD is better adapted to the enhanced soil moisture under PM. Future research should focus on breeding genotypes that thrive under PM conditions, emphasizing traits such as larger leaf areas and higher photosynthetic rates to boost crop productivity in rainfed areas. • HBS cultivar has the largest root system and yield under uncovered conditions. • Plastic mulching (PM) increased soil moisture and promotes root growth. • ZD cultivar shows the highest yield and water productivity under PM conditions. • ZD cultivar has the highest green leaf area and photosynthetic capacity under PM.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

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 head0.013
GPT teacher head0.197
Teacher spread0.184 · 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 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

Citations27
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAgricultural Water ManagementSame topicIrrigation Practices and Water ManagementFrench-language works237,207