Will Claydon, Phoebe Sutton, Ethan J Redmond, Gina Y W Vong, Alana Kluczkovski, Alice Thomas, Katherine Denby, Daphne Ezer
{"title":"受控环境农业光异质性对微绿生物量的影响。","authors":"Will Claydon, Phoebe Sutton, Ethan J Redmond, Gina Y W Vong, Alana Kluczkovski, Alice Thomas, Katherine Denby, Daphne Ezer","doi":"10.1017/qpb.2025.10003","DOIUrl":null,"url":null,"abstract":"<p><p>Yield is impacted by the environmental conditions that plants are exposed to. Controlled environmental agriculture provides growers with an opportunity to fine-tune environmental conditions for optimising yield and crop quality. However, space and time constraints will limit the number of experimental conditions that can be tested, which will, in turn, limit the resolution to which environmental conditions can be optimised. Here we present an innovative experimental approach that utilises the existing heterogeneity in light quantity and quality across a vertical farm to evaluate hundreds of environmental conditions concurrently. Using an observational study design, we identify features in light quality that are most predictive of biomass in different kinds of microgreens (kale, radish and sunflower) that may inform future iterations of lighting technology development for vertical farms.</p>","PeriodicalId":101358,"journal":{"name":"Quantitative plant biology","volume":"6 ","pages":"e17"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12277203/pdf/","citationCount":"0","resultStr":"{\"title\":\"The impact of light heterogeneity in controlled environment agriculture on biomass of microgreens.\",\"authors\":\"Will Claydon, Phoebe Sutton, Ethan J Redmond, Gina Y W Vong, Alana Kluczkovski, Alice Thomas, Katherine Denby, Daphne Ezer\",\"doi\":\"10.1017/qpb.2025.10003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Yield is impacted by the environmental conditions that plants are exposed to. Controlled environmental agriculture provides growers with an opportunity to fine-tune environmental conditions for optimising yield and crop quality. However, space and time constraints will limit the number of experimental conditions that can be tested, which will, in turn, limit the resolution to which environmental conditions can be optimised. Here we present an innovative experimental approach that utilises the existing heterogeneity in light quantity and quality across a vertical farm to evaluate hundreds of environmental conditions concurrently. Using an observational study design, we identify features in light quality that are most predictive of biomass in different kinds of microgreens (kale, radish and sunflower) that may inform future iterations of lighting technology development for vertical farms.</p>\",\"PeriodicalId\":101358,\"journal\":{\"name\":\"Quantitative plant biology\",\"volume\":\"6 \",\"pages\":\"e17\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12277203/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quantitative plant biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1017/qpb.2025.10003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative plant biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/qpb.2025.10003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
The impact of light heterogeneity in controlled environment agriculture on biomass of microgreens.
Yield is impacted by the environmental conditions that plants are exposed to. Controlled environmental agriculture provides growers with an opportunity to fine-tune environmental conditions for optimising yield and crop quality. However, space and time constraints will limit the number of experimental conditions that can be tested, which will, in turn, limit the resolution to which environmental conditions can be optimised. Here we present an innovative experimental approach that utilises the existing heterogeneity in light quantity and quality across a vertical farm to evaluate hundreds of environmental conditions concurrently. Using an observational study design, we identify features in light quality that are most predictive of biomass in different kinds of microgreens (kale, radish and sunflower) that may inform future iterations of lighting technology development for vertical farms.