Evidence map›Paper›PMID 38987328›Full record

ArticleScientific reports2024

Wild rodents seed choice is relevant for sustainable agriculture.

Yang Peng, Zhenbang Hu, Wen Dong, Xiaodong Wu, Chunyan Liu, Rongsheng Zhu, Jinhui Wang, Mingliang Yang, Zhaoming Qi, Ying Zhao and 7 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

17 authors.

Yang Peng *National Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Zhenbang Hu *National Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Wen Dong *National Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Xiaodong Wu *National Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Chunyan LiuNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Rongsheng ZhuNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Jinhui WangNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Mingliang YangNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Zhaoming QiNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Ying ZhaoNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Jianan ZouNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Xiaoxia WuNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Yingdong BiInstitute of Crop Cultivation and Tillage, Heilongjiang Academy of Agricultural Sciences, Harbin, 150028, Heilongjiang,, China.
Limin HuNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China.
Pascal RatetUniversité Paris-Saclay, CNRS, INRAE, Univ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91190, Gif sur Yvette, France. pascal.ratet@universite-paris-saclay.fr.
Qingshan ChenNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China. qshchen@126.com.
Dawei XinNational Key Laboratory of Smart Farm Technologies and Systems, Key Laboratory of Soybean Biology in Chinese Ministry of Education, College of Agriculture, Northeast Agricultural University, Harbin, 150030, People's Republic of China. xdawei@163.com.

Funding

High Oil and Yield Germplasm Development and Breeding Utilization (CZKYF2021-2-C009)National Key Research and Development Program of China 2021YFF1001206National Natural Science Foundation of China 31771882National Natural Science Foundation of China 31801389National Natural Science Foundation of China 32072014National Natural Science Foundation of China Grant numbers: 32070274National Natural Science Foundation of China U20A2027
6 · The paper itself

Abstract

Mitigating pre-harvest sprouting (PHS) and post-harvest food loss (PHFL) is essential for enhancing food securrity. To reduce food loss, the use of plant derived specialized metabolites can represent a good approach to develop a more eco-friendly agriculture. Here, we have discovered that soybean seeds hidden underground during winter by Tscherskia triton and Apodemus agrarius during winter possess a higher concentration of volatile organic compounds (VOCs) compared to those remaining exposed in fields. This selection by rodents suggests that among the identified volatiles, 3-FurAldehyde (Fur) and (E)-2-Heptenal (eHep) effectively inhibit the growth of plant pathogens such as Aspergillus flavus, Alternaria alternata, Fusarium solani and Pseudomonas syringae. Additionally, compounds such as Camphene (Cam), 3-FurAldehyde, and (E)-2-Heptenal, suppress the germination of seeds in crops including soybean, rice, maize, and wheat. Importantly, some of these VOCs also prevent rice seeds from pre-harvest sprouting. Consequently, our findings offer straightforward and practical approaches to seed protection and the reduction of PHS and PHFL, indicating potential new pathways for breeding, and reducing both PHS and pesticide usage in agriculture.

Indexed as

AgricultureGlycine maxSeedsVolatile Organic CompoundsAnimalsCrops, AgriculturalGerminationRodentiaVolatile Organic Compounds

Identifiers

PMID38987328
PMCPMC11237120

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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.