Sep 2026· Frontiers in Plant Science· 0 citations· 25 references
Plant Growth Enhancement Techniques
Abstract
This study presents the development and evaluation of a novel, natural plant oil-based biostimulant called PlantGuard, formulated from a blend of essential oil components and emulsifiers designed to enhance crop performance under field and controlled-environment hydroponics conditions. The biostimulant was applied to horticultural vegetables and crops such as tomato (
Solanum lycopersicum
) and shallot
(Allium cepa
var.
aggregatum)
, as well as rice (
Oryza sativa
) across multiple trial sites in Indonesia over two growing seasons. Treated plots demonstrated statistically significant improvements in flowering synchrony, fruit set, biomass accumulation, and overall yield, with increases ranging from 15% to 32% compared to untreated controls. We also studied the effect of PlantGuard on tomatoes and kale (
Brassica oleracea
var.
sabellica)
, grown under hydroponic conditions and recorded an almost 3-fold increase in total yield. To characterize biological responses associated with PlantGuard, a comprehensive molecular analysis was conducted comprising RNA sequencing, quantitative proteomics, and untargeted metabolomics. RNA-sequencing profiling revealed differential expression of genes associated with photosynthesis, nutrient transport, hormonal signaling, including jasmonic acid- and auxin-related responses, and defense processes. Proteomic analyses confirmed the enhanced expression of stress-related proteins, antioxidant enzymes, and metabolic regulators. Metabolomic fingerprinting identified elevated levels of phenylpropanoids, flavonoids, and lipid-derived signaling molecules associated with abiotic stress mitigation and plant growth promotion. Collectively, these multi-omics findings validate the functional activity of PlantGuard at the molecular level and support its application as a sustainable input for enhancing crop and vegetable productivity by increasing plant growth and resilience in diverse agricultural systems.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· SSE@SIGSOFT FSE· 56 citations· ⚡4
This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.