Evidence map›Paper›PMID 38594637›Full record

ArticleBMC plant biology2024

Vineyard microclimate alterations induced by black inter-row mulch through transcriptome reshaped the flavoromics of cabernet sauvignon grapes.

Meng-Bo Tian, Yu Wang, Xiao-Tong Gao, Hao-Cheng Lu, Qi Zhang, Xiao Han, Hui-Qing Li, Ning Shi, Chang-Qing Duan, Jun Wang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC plant biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Meng-Bo Tian *Center for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, China.
Yu Wang *Key Laboratory of Jianghuai Agricultural Product Fine Processing and Resource Utilization, Ministry of Agriculture and Rural Affairs, Anhui Engineering Research Center for High Value Utilization of Characteristic Agricultural Products, College of Tea & Food Science and Technology, Anhui Agricultural University, Hefei, 230036, China.
Xiao-Tong GaoCenter for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, China.
Hao-Cheng LuCenter for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, China.
Qi ZhangKey Laboratory of Jianghuai Agricultural Product Fine Processing and Resource Utilization, Ministry of Agriculture and Rural Affairs, Anhui Engineering Research Center for High Value Utilization of Characteristic Agricultural Products, College of Tea & Food Science and Technology, Anhui Agricultural University, Hefei, 230036, China.
Xiao HanCenter for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, China.
Hui-Qing LiCenter for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, China.
Ning ShiCenter for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, China.
Chang-Qing DuanCenter for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, China.
Jun WangCenter for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, China. jun_wang@cau.edu.cn.
China Agricultural University · CNMinistry of Agriculture and Rural Affairs · CNAnhui Agricultural University · CN

Funding

China Agriculture Research System of MOF and MARA CARS-29Major Science and Technology Special Projects of Xinjiang Uygur Autonomous Region during the "14th Five-year Plan" 2022A02002-1
6 · The paper itself

Abstract

backgroundWeed control is essential for agricultural floor management in vineyards and the inter-row mulching is an eco-friendly practice to inhibit weed growth via filtering out photosynthetically active radiation. Besides weed suppression, inter-row mulching can influence grapevine growth and the accumulation of metabolites in grape berries. However, the complex interaction of multiple factors in the field challenges the understanding of molecular mechanisms on the regulated metabolites. In the current study, black geotextile inter-row mulch (M) was applied for two vintages (2016-2017) from anthesis to harvest. Metabolomics and transcriptomics analysis were conducted in two vintages, aiming to provide insights into metabolic and molecular responses of Cabernet Sauvignon grapes to M in a semi-arid climate.

resultsUpregulation of genes related to photosynthesis and heat shock proteins confirmed that M weakened the total light exposure and grapes suffered heat stress, resulting in lower sugar-acid ratio at harvest. Key genes responsible for enhancements in phenylalanine, glutamine, ornithine, arginine, and C

conclusionThis study provides a valuable overview of metabolic and transcriptomic responses of M grapes in semi-arid climates, which could facilitate understanding the complex regulatory network of metabolites in response to microclimate changes.

Indexed as

VitisWineAnthocyaninsFarmsFruitMicroclimateTranscriptomeAnthocyaninsMicroclimatePrimary metabolitesSecondary metabolitesTranscription pathwayVineyard management

Identifiers

PMID38594637
PMCPMC11003005
OpenAlexW4394615501

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.