Green Extraction of Lotus Leaf (

Jing Sun, Mengqi Qin, Luyang Chen, Xin Li, Xinyan Wu, Gang Ye, Jianjun Deng, Haixia Yang

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Jing SunCollege of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.

Mengqi QinCollege of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.

Luyang ChenCollege of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.

Xin LiCollege of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.ORCID 0009-0002-4024-2269

Xinyan WuCollege of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.

Gang YeCollege of Veterinary Medicine, Sichuan Agricultural University, Chengdu 611130, China.

Jianjun DengState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.ORCID 0000-0002-3057-6997

Haixia YangCollege of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.ORCID 0000-0002-4410-9257

Funding

CNS-NSF-Nutrilite Research Fund for Plant Functional Substances CNS-NCL2024-312National Natural Science Foundation of China 32422069State Key Laboratory of Vegetable Biobreeding SKLVB202503the 2115 Talent Development Program of China Agricultural University none

6 · The paper itself

Abstract

Deep eutectic solvents (DESs) have attracted considerable attention in recent years because of their cost-effectiveness, safety, and sustainability. In this study, we developed 19 DESs for the extraction of antioxidant polyphenolic compounds from lotus leaves, utilizing ultrasound-assisted extraction (UAE). Among the DESs examined, choline chloride (ChCl) and lactic acid (ChCl: lactic acid) exhibited the highest extraction efficiency. The optimal conditions were established as follows: molar ratio of 1:2.6, solid-to-liquid ratio of 1:20 g/mL, water content of 8%, and ultrasound time of 65 min, which proved to be more efficient than conventional extraction methods such as water and ethanol. Under the optimal conditions, the total phenolic content (TPC) was 187.23 ± 14.67 mg GAE/g DW, and the extracts exhibited high antioxidant activity (DPPH IC

Indexed as

antioxidant activitydeep eutectic solventsextraction mechanismtotal phenolic content

Identifiers

PMID41375983

DOI10.3390/foods14234045

PMCPMC12691861

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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.