Multifaceted mechanisms regulating Brassica oleracea growth under shading gradients in an agrivoltaic system: Integrated responses of the soil-plant system and transcriptomic analysis

Authors

  • zhuo Chen Guizhou Academy of Agricultural Sciences Horticultural Research Institute (Guizhou Province Horticulture Engineering Technology Research Center), Guiyang 550025, China
  • Xiaocui Liu Guizhou Academy of Agricultural Sciences Horticultural Research Institute (Guizhou Province Horticulture Engineering Technology Research Center), Guiyang 550025, China
  • Tiantian Ban Guizhou Academy of Agricultural Sciences Horticultural Research Institute (Guizhou Province Horticulture Engineering Technology Research Center), Guiyang 550025, China
  • Chao Ma Guizhou Academy of Agricultural Sciences Horticultural Research Institute (Guizhou Province Horticulture Engineering Technology Research Center), Guiyang 550025, China

Keywords:

agrivoltaic system, shading gradient, Brassica oleracea, soil physicochemical properties, crop physiology, transcriptomics

Abstract

Agrivoltaic systems represent a sustainable land-use paradigm capable of synergistically generating electricity and producing agricultural crops on the same piece of land. However, the mechanisms by which photovoltaic shading affects crop growth are not fully understood. This study investigated these mechanisms using Brassica oleracea as a model plant at an agrivoltaic base in Guizhou Province, China. Treatments included high shading (HP, 70%-80%), low shading (LP, 20%-30%), and no shading (NP). This study systematically examined the regulatory effects of these shading gradients on soil physicochemical properties, plant growth physiology, and transcriptomic expression. Results indicated that the NP treatment yielded the highest B. oleracea biomass, while the LP treatment significantly enhanced the content of quality components such as sugars and starch while maintaining a relatively high yield. The HP treatment promoted the accumulation of structural substances (cellulose, lignin) and maintained higher soil nutrient levels. Transcriptome analysis revealed that shading significantly altered pathways involved in photosynthesis, starch and sucrose metabolism, and plant hormone signal transduction. Several key responsive genes were identified, including Bo4g182560 (a chlorophyll a/b-binding protein) and Bo3g039200 (involved in jasmonic acid biosynthesis). Furthermore, different shading environments induced distinct antioxidant strategies: the NP zone relied on peroxidase (POD) activity to manage oxidative pressure associated with full sunlight exposure, whereas the HP zone maintained redox homeostasis by enhancing catalase (CAT) activity. By integrating multi-omics data spanning soil, plant, and molecular levels, this study partially elucidates the adaptive regulatory network of B. oleracea in the agrivoltaic system, specifically involving photosynthesis, starch and sucrose metabolism, plant hormone signal transduction, and distinct antioxidant strategies, providing a theoretical basis and genetic resources for system optimization and precise crop configuration.      

Key words: agrivoltaic system; shading gradient; Brassica oleracea; soil physicochemical properties; crop physiology; transcriptomics

DOI: 10.25165/j.ijabe.20261904.10486

Citation: Chen Z, Liu X C, Ban T T, Ma C. Multifaceted mechanisms regulating Brassica oleracea growth under shadinggradients in an agrivoltaic system: Integrated responses of the soil-plant system and transcriptomic analysis. Int J Agric & BiolEng, 2026; 19(4): 152–164.

References

[1] Tesfaye B, Lengoiboni M, Zevenbergen J, Simane B. A holistic analysis of food security situation of households engaged in land certification and sustainable land management programs: South Wello, Ethiopia. Foods, 2023; 12(18): 3341.

[2] Fernandez M I, Go Y I, Wong D M L, Früh W G. Review of challenges and key enablers in energy systems towards net zero target: Renewables, storage, buildings, & grid technologies. Heliyon, 2024; 10(23): e40691.

[3] Wang Y J, Wang R, Tanaka K, Ciais P, Penuelas J, Balkanski Y, et al. Global spatiotemporal optimization of photovoltaic and wind power to achieve the Paris Agreement targets. Nat Commun, 2025; 16(1): 2127.

[4] Coşgun A E, Endiz M S, Demir H, Özcan M. Agrivoltaic systems for sustainable energy and agriculture integration in Turkey. Heliyon, 2024; 10(11): e32300.

[5] Goetzberger A, Zastrow A. Kartoffeln unter dem Kollektor. Sonnenenergie, 1981; 3(3): 19–22.

[6] Tan Y, Liu J, Li W D, Yin J H, Chen H, Peng Y T, et al. Agrivoltaics development progresses: From the perspective of photovoltaic impact on crops, soil ecology and climate. Environ Res, 2025; 266: 120540.

[7] Cuppari R I, Branscomb A, Graham M, Negash F, Smith A K, Proctor K, et al. Agrivoltaics: Synergies and trade-offs in achieving the sustainable development goals at the global and local scale. App.Energy, 2024; 362: 122970.

[8] Mäkinen A, Ishihara H, Poque S, Sipari N, Himanen K, Varjus I, et al. Photosynthetic adjustments maintain lettuce growth under dynamically changing lighting in controlled indoor farming setups. Physiol Plant, 2025; 177(4): e70405.

[9] Hickey T, Uchanski M, Bousselot J. Vegetable crop growth under photovoltaic (PV) modules of varying transparencies. Heliyon, 2024; 10(16): e36058.

[10] Ukwu U N, Muller O, Meier-Grüll M, Uguru M I. Agrivoltaics shading enhanced the microclimate, photosynthesis, growth and yields of vigna radiata genotypes in tropical Nigeria. Sci Rep, 2025; 15(1): 1190.

[11] Disciglio G, Stasi A, Tarantino A, Frabboni L. Microclimate modification, evapotranspiration, growth and essential oil yield of six medicinal plants cultivated beneath a dynamic agrivoltaic system in Southern Italy. Plants, 2025; 14(15): 2428.

[12] Zheng J, Meng S D, Zhang X Y, Zhao H L, Ning X L, Chen F C, et al. Increasing the comprehensive economic benefits of farmland with Even-lighting Agrivoltaic Systems. PLoS ONE, 2021; 16(7): e0254482.

[13] Siggers J A, Sturchio M A, Gordon L, Mead S, Smith M D, Knapp A K. Environmental heterogeneity imposed by photovoltaic array alters grassland soil microbial communities. Glob Chang Biol, 2025; 31(7): e70376.

[14] Li X R, Yu Q Q, Yao Z X, Li S, Ma L C, Su K L, et al. The combination of physiological and transcriptomic approaches reveals new insights into the molecular mechanisms of leymus chinensis growth under different shading intensities. Int J Mol Sci, 2025; 26(6): 2730.

[15] Jing X J, Chen P R, Jin X J, Lei J, Wang L J, Chai S S, et al. Physiological, photosynthetic, and transcriptomics insights into the influence of shading on leafy sweet potato. Genes, 2023; 14(12): 2112.

[16] Markin L, Bobrik L. Geometric method for estimating shading degree of objects in solar industry. In: Proceedings of the 31st International Conference on Computer Graphics and Vision (GraphiCon 2021). 2021; pp.645–655. doi: 10.20948/graphicon-2021-3027-645-655.

[17] Bremner J M. Nitrogen—total. In: Sparks D L, Page A L, Helmke P A, Loeppert R H, Soltanpour P N, editors. Methods of soil analysis: Part 3—Chemical methods. Madison: Soil Science Society of America and American Society of Agronomy. 1996; pp.1085–1121.

[18] Roberts P, Stockdale E A, Shepherd M A. Alkaline hydrolysis diffusion method for soil available nitrogen determination. Soil Biol Biochem, 2009; 41(6): 1320–1327.

[19] Bray R H, Kurtz L T. Determination of total, organic, and available forms of phosphorus in soils. Soil Sci, 1945; 59(1): 39–45.

[20] Olsen S R, Sommers L E. Phosphorus. In: Page A L, Miller R H, Keeney D R, editors. Methods of soil analysis: Part 2—Chemical and microbiological properties. Madison: American Society of Agronomy and Soil Science Society of America. 1982; pp.403–430.

[21] Knudsen D, Peterson G A, Pratt P F. Lithium, sodium, and potassium. In: Page A L, Miller R H, Keeney D R, editors. Methods of soil analysis: Part 2—Chemical and microbiological properties. Madison: American Society of Agronomy and Soil Science Society of America. 1982; pp.225–246.

[22] Helmke P A, Sparks D L. Lithium, sodium, potassium, rubidium, and cesium. In: Sparks D L, Page A L, Helmke P A, Loeppert R H, Soltanpour P N, Tabatabai M A, et al. editors. Methods of soil analysis: Part 3—Chemical methods. Madison: Soil Science Society of America and American Society of Agronomy, 1996; pp.551–574.

[23] Mirzakhaninafchi H, Mani I, Hasan M, Nafchi A M, Parray R A, Kumar D. Development of prediction models for soil nitrogen management based on electrical conductivity and moisture content. Sensors, 2022; 22(18): 6728.

[24] McLean E O. Soil pH and lime requirement. In: Page A L, Miller R H, Keeney D R, editors. Methods of soil analysis: Part 2—Chemical and microbiological properties. Madison: American Society of Agronomy and Soil Science Society of America. 1982; pp.199–224.

[25] Nelson D W, Sommers L E. Total carbon, organic carbon, and organic matter. In: Sparks D L, Page A L, Helmke P A, Loeppert R H, Soltanpour P N, Tabatabai M A, et al. editors. Methods of soil analysis: Part 3—Chemical methods. Madison: Soil Science Society of America and American Society of Agronomy, 1996; pp.961–1010.

[26] Blake G R, Hartge K H. Bulk density. In: Klute A, editor. Methods of soil analysis: Part 1—Physical and mineralogical methods. Madison: American Society of Agronomy and Soil Science Society of America. 1986; pp.363–375.

[27] Gardner W H. Water content. In: Klute A, editor. Methods of soil analysis: Part 1—Physical and mineralogical methods. Madison: American Society of Agronomy and Soil Science Society of America. 1986; pp.493–544.

[28] Yemm E W, Willis A J. The estimation of carbohydrates in plant extracts by anthrone. Biochem J, 1954; 57: 508–514.

[29] Miller G L. Use of dinitrosalicylic acid reagent for determination of reducing sugar. Anal Chem, 1959; 31: 426–428.

[30] Chow P S, Landhäusser S M. A method for routine measurements of total sugar and starch content in woody plant tissues. Tree Physiol, 2004; 24: 1129–1136.

[31] Li W T, Huang D J, Wang B, Hou X M, Zhang R, Yan M, et al. Changes of starch and sucrose content and related gene expression during the growth and development of Lanzhou lily bulb. PLoS ONE, 2022; 17(1): e0262506.

[32] Dubois M, Gilles K A, Hamilton J K, Rebers P A, Smith F. Colorimetric method for determination of sugars and related substances. Anal Chem, 1956; 28: 350–356.

[33] Trinder P. Determination of glucose in blood using glucose oxidase with an alternative oxygen acceptor. Ann Clin Biochem, 1969; 6: 24–31.

[34] Zhang Y, Li X, Wang H. Determination of fructose and glucose in tomato by HPLC with evaporative light-scattering detection. J Sci Food Agric, 2020; 100: 1234–1240.

[35] Tan C T, Zhang L, Duan X W, Chai X R, Huang R M, Kang Y Y, et al. Effects of exogenous sucrose and selenium on plant growth, quality, and sugar metabolism of pea sprouts. J Sci Food Agric, 2022; 102(7): 2855–2863.

[36] Zhang W T, Xu S J, Gao M, Peng S J, Chen L Y, Lao F, et al. Profiling the water soluble pectin in clear red raspberry (Rubus idaeus L. cv. Heritage) juice: Impact of high hydrostatic pressure and high-temperature short-time processing on the pectin properties. Food Hydrocoll, 2021; 125: 107439.

[37] Caruso G, Gomez L D, Ferriello F, Andolfi A, Borgonuovo C, Evidente A, et al. Exploring tomato Solanum pennellii introgression lines for residual biomass and enzymatic digestibility traits. BMC Genet, 2016; 17: 56.

[38] Giannopolitis C N, Ries S K. Superoxide dismutases: I. Occurrence in higher plants. Plant Physiology, 1977; 59(2): 309–314.

[39] Hadwan M H. Simple spectrophotometric assay for measuring catalase activity in biological tissues. BMC Biochemistry, 2018; 19: 7.

[40] Chance B, Maehly A C. Assay of catalases and peroxidases. Methods in Enzymology, 1955; 2: 764–775.

[41] Aguilar Diaz De Leon J, Borges C R. Evaluation of oxidative stress in biological samples using the thiobarbituric acid reactive substances assay. Journal of Visualized Experiments, 2020;(159). doi:10.3791/61122.

[42] Velikova V, Yordanov I, Edreva A. Oxidative stress and some antioxidant systems in acid rain-treated bean plants: protective role of exogenous polyamines. Plant Science, 2000; 151(1): 59–66.

[43] Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics, 2018; 34(17): i884–i890.

[44] Pertea M, Pertea G M, Antonescu C M, Chang T-C, Mendell J T, Salzberg S L, et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nature Biotechnology, 2015; 33(3): 290–295.

[45] Love M I, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol, 2014; 15(12): 550.

[46] Gene Ontology Consortium. Gene Ontology: Tool for the unification of biology. Nat Genet, 2000; 25(1): 25–29.

[47] Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res, 2000; 28(1): 27–30.

[48] Shen S, Park J W, Lu Z, Lin L, Henry M D, Wu Y N, et al. rMATS: Robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc Natl Acad Sci USA, 2014; 111(51): E5593–E5601.

[49] Gao J, Yu X, Ma F, Li J. RNA-Seq analysis of transcriptome and glucosinolate metabolism in seeds and sprouts of broccoli (Brassica oleracea var. Italica). PLoS ONE, 2014; 9(2): e88804.

[50] Lv Q, Liao J, Luo P, Zheng W, Liu J, Guo L, et al. Validation of suitable reference genes for qRT-PCR in cabbage (Brassica oleracea L.) under different abiotic stress experimental conditions. Plant Cell Rep, 2020; 39(5): 685–697.

[51] Livak K J, Schmittgen T D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-ΔΔCT method. Methods, 2001; 25(4): 402–408.

[52] Hassanien R H E, Ibrahim M M, Ghaly A E, Abdelrahman E N. Effect of photovoltaics shading on the growth of chili pepper in controlled greenhouses. Heliyon, 2022; 8(2): e08877.

[53] Liu Z, Peng T, Ma S, Qi C, Song Y, Zhang C, et al. Potential benefits and risks of solar photovoltaic power plants on arid and semi-arid ecosystems: an assessment of soil microbial and plant communities. Front Microbiol, 2023; 14: 1190650.

[54] Brouwer B, Gardeström P, Keech O. In response to partial plant shading, the lack of phytochrome A does not directly induce leaf senescence but alters the fine-tuning of chlorophyll biosynthesis. J Exp Bot, 2014; 65(14): 4037–4049.

[55] Petrakis T, Ioannou P, Kitsiou F, Kavga A, Grammatikopoulos G, Karamanos N. Growth and physiological characteristics of strawberry plants cultivated under greenhouse-integrated semi-transparent photovoltaics. Plants, 2024; 13(6): 768.

[56] Yang D L, Yao J, Mei C S, Tong X H, Zeng L J, Li Q, et al. Plant hormone jasmonate prioritizes defense over growth by interfering with gibberellin signaling cascade. Proc Natl Acad Sci USA, 2012; 109(19): E1192–E1200.

[57] Hu Y, Zhang X, Ma X. The influencing pathway of agrivoltaics on soybean protein concentration. Front Plant Sci, 2025; 16: 1618027.

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Published

2026-09-03

How to Cite

(1)
Chen, zhuo; Liu, X.; Ban, T.; Ma, C. Multifaceted Mechanisms Regulating Brassica Oleracea Growth under Shading Gradients in an Agrivoltaic System: Integrated Responses of the Soil-Plant System and Transcriptomic Analysis. Int J Agric & Biol Eng 2026, 19, 152-164.

Issue

Vol. 19 No. 4 (2026): IJABE

Section

Natural Resources and Environmental Systems

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