Participatory plant breeding of sweetcorn for adaptation at diverse Spanish locations

Participatory plant breeding of sweetcorn for adaptation at diverse Spanish locations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Participatory plant breeding of sweetcorn for adaptation at diverse Spanish locations Ana López-Malvar, Lorena Álvarez-Iglesias, Pedro Revilla This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7961927/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Sweet corn homozygous for the shrunken2 ( sh2 ) mutation exhibits narrow genetic diversity and limited adaptation to diverse environments. This study aimed to assess whether participatory plant breeding (PPB), led by farmers in specific environments, can enhance adaptation and generate phenotypic diversity associated with local conditions without compromising quality. Starting from the synthetic sweet corn population EPS18 — originally developed in the Spanish province of Pontevedra and with low genetic diversity — three PPB selection cycles were conducted in three ecologically distinct Spanish provinces: Lugo, Burgos, and Barcelona. The third selection cycle from each location was evaluated alongside the original EPS18 population and four commercial hybrids in both Pontevedra (the original site) and Burgos (the most environmentally challenging site). Temperature and water availability emerged as the primary environmental factors influencing selection outcomes. Yield and plant growth were the most affected traits, while quality parameters remained largely unchanged. These results demonstrate that PPB can effectively improve the adaptation of a genetically narrow sweet corn population to diverse northern Spanish environments without sacrificing quality. We conclude that selection for local adaptation through PPB can successfully induce phenotypic diversity in traits related to plant growth and yield, driven by environmental variables — particularly temperature and water availability — while maintaining desirable quality traits. Sweetcorn quality PPB Spanish environments phenotypic diversity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction In 1953, John R. Laughnan proposed the use of the shrunken2 ( sh2 ) allele to produce high-quality sweet corn. Within a few decades, this mutant became the predominant type of sweet corn cultivated in temperate regions. Today, it is estimated that 100% of sweet corn grown for the fresh market and approximately 75% of that used in the processing industry carries the sh2 mutation (Tracy et al., 2019 ). Despite its rapid success, Laughnan faced a major challenge in introducing this mutant to the market due to the extremely limited genetic diversity available — no other germplasm carried the sh2 allele at the time. Consequently, significant efforts have been made to broaden the genetic base of sh2 sweet corn. Some breeders have introgressed the sh2 allele into Sh2Sh2 inbred lines through crossing and backcrossing, aiming to enhance the agronomic performance of supersweet corn (Revilla et al., 2006 ). While backcrossing is effective for incorporating single recessive alleles, it can also introduce undesirable alleles affecting quality traits inherited from field corn. As an alternative, new variability can be generated by crossing existing sh2sh2 genotypes and selecting under diverse environmental conditions. Small-scale family farming remains the dominant form of agriculture globally, particularly in low-income countries, and is responsible for the majority of primary agricultural production. However, factors such as the widening income gap between agriculture and other sectors have led to a steady decline in the number of farms and agricultural workers over time (Suess-Reyes and Fuetsch, 2016 ; Kholová et al., 2024 ). To address this challenge, smallholder farmers are increasingly turning to more profitable agricultural models, including organic farming and the cultivation of high-value, quality-enhanced crops (Bold et al., 2022 ). The sustainability of these approaches can be supported through participatory plant breeding (PPB) programs, which improve heritability by enabling in situ selection in target environments. This approach reduces breeding costs and empowers farmers to participate in continuous selection (Colley et al., 2022 ; Mujjabi et al., 2024 ). As a specialty type of maize, sweet corn is marketed as a fresh vegetable, making high quality standards essential for consumer acceptance. At the same time, it offers a promising opportunity for smallholder farmers in temperate regions to produce high-value crops, given its similar agronomic requirements to field maize. PPB, which involves selection in farmers’ fields under diverse and often low-input conditions, provides a valuable strategy for developing genotypes better adapted to specific environments and production systems, such as organic or family farming (Carkner and Entz, 2024 ). The objective of this research was to determine whether selection for adaptation to target environments through farmer-led PPB can generate phenotypic diversity associated with local adaptation, without compromising sweet corn quality. Materials and methods In 1996, at the Misión Biológica de Galicia (CSIC), located in the Spanish province of Pontevedra, we developed four synthetic sweet corn populations derived from double-crossed commercial hybrids that were subsequently recombined. After evaluating the agronomic performance and quality of these four populations, EPS18 was selected for further breeding due to its superior characteristics. EPS18 was created by crossing two commercial supersweet corn hybrids, Marvel and 710A, both homozygous for the recessive shrunken2 ( sh2 ) allele. The resulting population was recombined annually through isolated open pollination, with mass selection focused on adaptation to the environmental conditions of Pontevedra (northwestern Spain), continuing until 2018. In 2018, a participatory plant breeding (PPB) program was initiated in three locations across northern Spain (Table 1), representing a wide range of geographic and climatic conditions. The selected sites were located in the provinces of Lugo, Burgos, and Barcelona, and are referred to hereafter by their respective province names. The climate in Pontevedra features short, warm, and mostly clear summers, with annual temperatures typically ranging from 7 °C to 26 °C, rarely falling below 2 °C or exceeding 32 °C. In O Páramo (Lugo), summers are short, warm, dry, and partly cloudy, with temperatures ranging from 1 °C to 26 °C, and extremes between −3 °C and 32 °C. Villangómez (Burgos) experiences short, dry summers with minimal cloud cover, and temperatures generally range from −1 °C to 28 °C, with occasional lows of −5 °C and highs of 33 °C. Piera (Barcelona) has short, hot, and mostly clear summers, with a dry climate year-round; temperatures typically range from 1 °C to 30 °C, rarely dropping below −3 °C or rising above 32 °C. The PPB program involved sowing over 100 EPS18 plants annually at each location. Collaborating farmers selected the 20 most outstanding plants based on growth, health, and ear size and shape, using their own criteria. The selected ears were naturally dried and used as seed for the following season. This process resulted in the first selection cycle in 2018, followed by second and third cycles in 2019 and 2020, respectively. Meanwhile, the original EPS18 population continued to be maintained in Pontevedra using the same methodology. In 2021, the third selection cycles from Lugo, Burgos, and Barcelona, along with the original EPS18 population, were multiplied in Pontevedra through manual crossing of at least 100 plants per cycle, used as both male and female parents. The original EPS18 population developed in Pontevedra (EPS18PO) was evaluated alongside the third selection cycles from Lugo (EPS18LU), Burgos (EPS18BU), and Barcelona (EPS18BA), as well as two local hybrids (EP84×Wh05041 and EP84×Wh16005) and two commercial hybrids (GSS15829R and Overland). Uniformly produced seed from all genotypes was evaluated over two growing seasons (2022 and 2023) in two contrasting environments: Pontevedra, representing the original and mildest environment, and Burgos, characterized by the most challenging climatic conditions. Additionally, in Pontevedra, both early and late sowing trials were conducted to assess performance under different planting dates. Field trials followed a randomized complete block design with two replications. Each experimental plot consisted of two rows spaced 80 cm apart, with 17 plants per row at 21 cm spacing, resulting in an average plant density of 60,000 plants per hectare. Due to space limitations, single-row plots were used in Burgos. The traits recorded included: emergence rate (percentage of seeds that germinated), plant vigor (rated on a scale from 1 = weak to 9 = vigorous), days from sowing to pollen shedding and silking, plant height (from soil surface to tassel tip), number of marketable ears per plant, plant and ear appearance (rated from 1 = poor to 9 = excellent), ear quality (1 = poor to 9 = excellent), ear weight per square meter, individual ear weight, ear length, and number of kernel rows. Analysis of variance (ANOVA) was performed for all traits, considering years, locations, replications, and genotypes as sources of variation. All factors were treated as random effects, except genotype, which was considered a fixed effect. Mean comparisons were conducted using Fisher’s protected least significant difference (LSD) test at a significance level of P = 0.05 (Steel et al., 1997). To identify environmental factors influencing sweet corn performance, multiple regression analyses were conducted using a stepwise selection method (P = 0.05), with sweet corn traits as dependent variables and environmental parameters (Table 1) as independent variables. All statistical analyses were performed using the Statistical Analysis System (SAS, 2002). Results and Discussion The objective of this study was to evaluate whether participatory plant breeding (PPB) for adaptation to specific environments could generate phenotypic diversity associated with environmental adaptation, without compromising sweet corn quality. Three cycles of PPB selection of the EPS18 population from three distinct locations — Lugo (EPS18LU), Burgos (EPS18BU), and Barcelona (EPS18BA) — were assessed alongside the original EPS18 population from Pontevedra (EPS18PO), two local hybrids (EP84×Wh05041 and EP84×Wh16005), and two commercial hybrids (GSS15829R and Overland). Significant differences were observed for ear weight and ear length (Table 2). The Barcelona population (EPS18BA) exhibited the lowest ear weight, significantly differing from the other populations and hybrids. Ear length was significantly greater in the Lugo population (EPS18LU) compared to Burgos (EPS18BU). In both traits, hybrids outperformed the populations (Figure 1). The number of marketable ears per plant was slightly below one across all populations, with no significant differences among genotypes. Emergence rates averaged around 80% across all environments, with populations showing higher emergence than hybrids, which were more affected by adverse conditions (Table 2, Figure 2). Vigor followed a similar pattern, with populations outperforming two of the hybrids (Overland and EP84×Wh05041). The commercial hybrid GSS15829R exhibited the tallest plants, significantly exceeding all other genotypes, while no significant differences were found among the remaining populations and hybrids. Regarding ear appearance, Overland and EP84×Wh05041 showed superior ratings, although no significant differences were detected among the populations (Table 2, Figure 3). In terms of yield, the four EPS18 populations, along with hybrids GSS15829R and EP84×Wh16005, achieved the highest values, significantly outperforming Overland and EP84×Wh05041 (Figure 4). Seed quality, assessed through emergence and vigor, was consistently high across all selection cycles. Germination rates of sweet corn hybrids often decline under unfavorable environmental conditions. Analysis of individual environments revealed that selection for adaptation to a specific set of stress factors — such as the arid climate and alkaline soils of Burgos — does not necessarily confer improved performance in other environments with different stress profiles, such as the humid climate and acidic soils of Pontevedra. PPB had limited impact on growth cycle duration. However, selection in Lugo, an environment with a shorter growing season, resulted in reduced time to flowering. Effects on plant height were also modest, although selection under the most arid conditions (Burgos) produced shorter plants. PPB did not significantly affect ear appearance or quality. Nevertheless, selection in diverse environments led to improvements in specific ear traits, particularly in Burgos and Barcelona. Notably, ear appearance improved in Burgos, while ear weight increased in both Burgos and Barcelona. Ear length was also enhanced in Burgos compared to Barcelona. These findings indicate that PPB effectively modified the population for agronomic traits such as emergence, vigor, plant height, ear appearance, ear weight, and ear length, while maintaining stable quality parameters. Significant genotype × environment (G×E) interactions were observed for several traits, including emergence, vigor (Figure 5), male and female flowering time (Figure 6), ear weight and plant height (Figure 7), ear and plant appearance, and ear length (Figure 8). To better understand these interactions, analyses were conducted separately for each environment: early sowing in Pontevedra (Environment 1), late sowing in Pontevedra (Environment 2), and Burgos (Environment 3). For emergence, the pattern was consistent across all environments: no significant differences were found among the EPS18 populations, but they consistently exhibited higher emergence rates than all hybrids. Regarding vigor, significant differences were detected in Environment 1, where the populations from Lugo, Pontevedra, and Barcelona showed greater vigor than the hybrids EP84×Wh05041 and Overland. In Environment 2, populations again outperformed most hybrids in both emergence and vigor, with significant differences in vigor only between the Pontevedra population and EP84×Wh05041 (Figure 5). In early sowing trials (Environment 1), all four EPS18 populations flowered earlier than Overland, which was the latest genotype for both silking and anthesis. The Lugo and Pontevedra populations were the earliest to reach anthesis. Similarly, in late sowing (Environment 2), the Lugo population was the earliest for both silking and anthesis. For plant height in Environment 1, the hybrids EP84×Wh05041 and Overland were the shortest, not significantly different from the Lugo population. The tallest genotype was EP84×Wh16005, which did not differ significantly from GSS15829R or the populations from Pontevedra and Barcelona. In Environment 2, the Burgos population was significantly shorter than GSS15829R (Figure 7). Ear weight varied across environments. In Environment 1, EP84×Wh16005 produced the heaviest ears, while no significant differences were found among the other genotypes. In Environment 2, the Burgos population had the lowest ear weight, and the Lugo and Pontevedra populations produced lighter ears than Overland, which did not differ significantly from the other hybrids or the Barcelona population. Ear appearance in Environment 1 was lower in all populations compared to the hybrids, except EP84×Wh05041. No significant differences were found in Environments 2 and 3 (Figure 8). For plant appearance in Environment 1, Overland and EP84×Wh05041 had the lowest scores. The EPS18 populations did not differ significantly among themselves, and the Pontevedra and Barcelona populations were comparable to the best-performing hybrid, while the Burgos and Lugo populations were similar to the lowest-performing hybrids. Ear length also varied across environments. In Environment 1, the longest ears were produced by EP84×Wh05041 and Overland, with the Pontevedra and Lugo populations not significantly different from Overland. In Environment 2, the shortest ears were from EP84×Wh05041, not differing from Overland or the Lugo population. In Burgos, the shortest ears were from the Burgos population, while the longest were from EP84×Wh16005 (Figure 8). In Burgos, ear length was the only trait showing significant differences among genotypes. To further explore environmental influences on sweet corn traits, multiple linear regression analyses were conducted using sweet corn traits as dependent variables and environmental descriptors (Table 3) as independent variables. Significant regression models were: 1. Emergence = 87.05 – 0.044 × Distance to sea (R 2 = 0.95*) 2. Vigor = 6.17 – 0.006 × Distance to sea (R 2 = 0.96*) 3. Plant height = 160.9 + 1.7 × Yearly temperature (R 2 = 0.91*) 4. Plant appearance = 4.96 – 0.0014 × Distance to sea (R 2 = 0.16*) + 0.0003 × Yearly rainfall (R 2 = 0.84*) 5. Row number = 18.16 – 0.0029 × Distance to sea (R 2 = 0.14*) – 0.001 × Yearly rainfall (R 2 = 0.86*) The regression models revealed that emergence and early vigor were primarily explained by the distance from the sea, accounting for 95% and 96% of the variability, respectively. Annual temperature explained 91% of the variability in plant height. For plant appearance and number of kernel rows per ear, annual rainfall was the main explanatory factor, accounting for 84% and 86% of the variability, respectively, with distance to the sea contributing an additional 16% and 14%. In contrast, no environmental variable was significantly associated with days to anthesis or silking, ears per plant, ear appearance and quality, or ear weight (per ear or per area), and thus these traits were not included in the final regression models. A basic characterization of the selection environments indicated that several environmental patterns influenced the response to selection. The most influential factor was distance to the sea, as locations closer to the coast tended to have lower elevation, warmer temperatures, and greater solar radiation. However, rainfall varied, with Pontevedra receiving the highest and Barcelona the lowest annual precipitation. Distance to the sea had a negative effect on emergence, vigor, plant appearance, and kernel row number. Rainfall positively influenced plant appearance but negatively affected row number, while temperature had a positive effect on plant height. Thus, emergence, vigor, and plant height were significantly influenced by a single environmental parameter, whereas plant appearance and row number were affected by two. The remaining traits showed no significant association with the environmental variables considered. Overall, these findings demonstrate clear environmental effects on the response to participatory breeding of sweet corn across diverse conditions. The main environmental drivers of breeding outcomes were temperature and water availability, with the most affected traits being yield and plant growth. Importantly, quality traits remained stable across environments. These results align with previous studies, such as Colley et al. (2022), who emphasized the benefits of PPB programs that leverage increased heritability through in situ selection. Similarly, Ceccarelli and Grando (2006) reported successful PPB initiatives that rapidly developed varieties adapted to marginal environments and traditional farming systems, while enhancing biodiversity. Dawson et al. (2008) also highlighted the suitability of PPB for heterogeneous environments and alternative agricultural systems, including organic farming. Based on these results, PPB applied to a sweet corn synthetic with a narrow genetic base proved effective in improving adaptation to specific environmental conditions without compromising quality. Therefore, the participatory breeding program can be continued and potentially expanded to additional target environments. In conclusion, selection for adaptation to local conditions successfully generated phenotypic diversity in traits related to plant growth and yield, driven by environmental factors — particularly temperature and water availability — while maintaining stable quality traits. Declarations Acknowledgements This research is part of the project PID2022-140991OB-I00, funded by MCIN/AEI/10.13039/501100011033/FEDER, UE. The authors thank to Eleuterio, Tomás and Jesús Revilla for their commitment to carry out this program, and to the Maize Breeding and Genetics team of Misión Biológica de Galicia (CSIC) for assistance. Authors contributions Ana López-Malvar and Lorena Álvarez data curation, investigation, and writing; Pedro Revilla conceptualization, formal analysis, funding acquisition, writing. All authors have reviewed and edited the final manuscript Data availability statement Data are available from the authors upon request Conflict of interest statement The authors declare no conflicts of interest References Bold T, Ghisolfi S, Nsonzi F, Svensson J (2022). Market access and quality upgrading: Evidence from four field experiments. Am Econ Rev 112: 2518-2552. Carkner MK, Entz MH (2024). Determining adaptability of farmer bred spring wheat ( Triticum aestivum L.) genotypes to Canadian organic production using stability analysis. Plant Breed 143: 500-517. Ceccarelli S, Grando S (2006). Decentralized-participatory plant breeding: An example of demand driven research. Euphytica 155: 349–360. Colley MR, Tracy WF, Lammerts van Bueren ET, Diffley M, Almekinders CJM (2022). How the Seed of Participatory Plant Breeding Found Its Way in the World through Adaptive Management. Sustainability 14: 2132. Dawson JC, Murphy KM, Jones SS (2008). Decentralized selection and participatory approaches in plant breeding for low-input systems. Euphytica 160: 143–154. Kholová J, Urban MO, Bavorová M, Ceccarelli S, Cosmas L, Desczka S, Bulte E (2024). Promoting new crop cultivars in low-income countries requires a transdisciplinary approach. Nature Plants 10: 1610-1613. Laughman JR (1953). The effect of sh2 factor on carbohydrate reserves in the mature endosperm of maize. Genetics 38: 485-499. Mujjabi C, Bohn MO, Wander MM, Ugarte CM (2024). Participatory breeding in organic systems: Experiences from maize case studies in the United States. J Agr Food Syst Com Develop 13: 23–36. Revilla P, Malvar RA, Rodríguez VM, Butrón A, Ordás B, Ordás A (2006). Variation of sugary1 and shrunken2 frequency in different maize genetic backgrounds. Plant Breed 25: 478-481. SAS Institute Inc (2002). SAS OnlineDoc, version 9. SAS Institute, Inc, Cary, North Carolina, USA. Steel RDG, Torrie J-H, Dickey DA (1997). Principles and Procedures in Statistics: A Biometrical Approach. 3rd ed. Mc Graw Hill, New York. Suess-Reyes J, Fuetsch E (2016). The future of family farming: A literature review on innovative, sustainable and succession-oriented strategies. J Rural Stud 47: 117-140. Tracy WF, Shuler SL, Dodson-Swenson H (2019). The use of endosperm genes for sweet corn improvement: A review of developments in endosperm genes in sweet corn since the seminal publication in Plant Breeding Reviews, Volume 1, by Charles Boyer and Jack Shannon (1984). In I. Goldman (Ed.), Plant Breed Rev 43: 215–241. John Wiley and Sons. Tables Table 1. Spanish locations and provinces (in parenthesis) involved in the participatory breeding program of the super sweet corn synthetic EPS18 Location and province Coordinates Height above the sea level (m) Distance from the sea (km) Mean annual rainfall (mm) Mean annual temperature (ºC) Pontevedra (Pontevedra) 42º25’53’’ N 8º38’37’’ W 20 0 1613 15 O Páramo (Lugo) 42º50’39’’ N 7º29’56’’ W 404 100 998 11.5 Villangómez (Burgos) 42º10’50’’ N 3º46’22’’ W 861 160 627 10.6 Piera (Barcelona) 41º31’14’’ N 1º44’49’’ E 300 40 360 19 Table 2. Means’ comparisons a of four versions of the sweetcorn synthetic EPS18 produced in Pontevedra (PO), after three cycles of participatory breeding for adaptation to three diverse Spanish locations: Lugo (LU), Burgos (BU), and Barcelona (BA), along with four hybrid checks, evaluated in the most extreme environments: Pontevedra (early and late sowing) and Burgos two years. The four checks were included only in the two environments of Pontevedra due to limiting availability in the farmer’s field. Genotype Emergence (%) Vigor (1-9) b Days to anthesis Days to silking Plant height (cm) Ears /plant Plant appearance (1-9) b EPS18PO 87.4a 6.1a 64.2 65.8 187.7b 0.83 5.4 EPS18LU 81.7a 5.7ab 62.5 65.0 177.8b 0.82 5.1 EPS18BU 80.6a 5.2ab 65.7 67.0 180.7b 0.87 4.9 EPS18BA 85.3a 6.0ab 64.7 67.3 192.8b 0.79 5.0 EP84×Wh05041 16.9d 2.8c 66.3 67.0 197.0b 1.03 3.5 EP84×Wh16005 67.1b 4.7b 64.5 67.5 194.0b 0.96 6.5 GSS15829R 33.1c 4.8ab 65.5 66.5 225.3a 1.06 4.5 Overland 16.2d 3.0c 69.3 70.3 189.8b 1.02 3.5 LSD (0.05) 6.1 1.4 25.2 Ear traits Genotype Ear appearance (1-9) b Quality (1-9) b Ear weight /m 2 (kg) Ear weight (kg) Ear length (cm) Row number EPS18PO 4.3c 4.8 0.89a 0.370c 19.41cd 16.58 EPS18LU 5.1bc 5.2 0.95a 0.375c 20.22c 16.93 EPS18BU 4.9bc 5.0 0.88a 0.317d 18.00d 17.10 EPS18BA 4.5c 5.2 0.92a 0.373c 19.16cd 17.67 EP84×Wh05041 5.0a 5.3 0.40b 0.393bc 24.23a 18.20 EP84×Wh16005 6.5bc 6.0 0.75a 0.485a 20.34bc 18.00 GSS15829R 6.0ab 6.3 0.74a 0.393bc 18.53cd 18.18 Overland 7.0a 6.0 0.38b 0.413b 22.25ab 17.15 LSD (0.05) 1.3 0.30 0.035 2.03 a Means followed by the same letter are not significantly different based on Fisher’s protected LSD at P = 0.05 b Scale from 1 = weak plants to 9 = vigorous plants for early vigor, or 1 = poor to 9 = great for appearance related traits and quality Table 3. Means of the four environments involved in the participatory breeding program of the sweetcorn synthetic EPS18 Genotype Emergence (%) Vigor (1-9) a Days to pollen Days to silking Plant height (cm) Ears /plant Plant appearance (1-9) a Pontevedra 87.4 6.1 64.2 65.8 187.7 0.83 5.4 Lugo 81.7 5.7 62.5 65.0 177.8 0.82 5.1 Burgos 80.6 5.2 65.7 67.0 180.7 0.87 4.9 Barcelona 85.3 6.0 64.7 67.3 192.8 0.79 5.0 Ear traits Genotype Ear appearance (1-9) † Quality (1-9) a Ear weight /m2 (kg) Ear weight * Ear length (cm) Row number Pontevedra 4.3 4.8 0.89 0.370 19.4 16.6 Lugo 5.1 5.2 0.95 0.375 20.2 16.9 Burgos 4.9 5.0 0.88 0.317 18.0 17.1 Barcelona 4.5 5.2 0.92 0.373 19.2 17.7 a Scale from 1 = weak plants to 9 = vigorous plants for early vigor, or 1 = poor to 9 = great for appearance related traits and quality Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 25 Feb, 2026 Reviewers agreed at journal 13 Feb, 2026 Reviews received at journal 12 Feb, 2026 Reviews received at journal 11 Feb, 2026 Reviewers agreed at journal 04 Feb, 2026 Reviews received at journal 02 Feb, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers agreed at journal 30 Jan, 2026 Reviewers agreed at journal 28 Jan, 2026 Reviewers invited by journal 28 Jan, 2026 Editor assigned by journal 28 Oct, 2025 Submission checks completed at journal 28 Oct, 2025 First submitted to journal 27 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7961927","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582065967,"identity":"c99e91c3-55cd-42a5-b108-cf87721489db","order_by":0,"name":"Ana López-Malvar","email":"","orcid":"","institution":"Universidad de Vigo, Unidad Asociada a la Misión Biológica de Galicia (CSIC)","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"","lastName":"López-Malvar","suffix":""},{"id":582065969,"identity":"30b78cbb-63b3-43e0-acee-c359f29ca80c","order_by":1,"name":"Lorena 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15:39:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7961927/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7961927/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101497819,"identity":"0a554206-a8ca-491b-b930-fd23eb799b33","added_by":"auto","created_at":"2026-01-30 12:57:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83329,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in Ear weight (A) and Ear Length (B) for the four versions of the sweetcorn synthetic EPS18 from Pontevedra (PO), after three cycles of participatory breeding for adaptation to three diverse Spanish locations: Lugo (LU), Burgos (BU), and Barcelona (BA), along with four hybrid checks, evaluated in the most extreme environments: Pontevedra (early and late sowing) and Burgos, during two years.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/eb88b6f22c5da973a02a6ebd.png"},{"id":101497824,"identity":"7efb85f7-c87e-47e3-a420-4092e59bd4e3","added_by":"auto","created_at":"2026-01-30 12:57:33","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":312808,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in Emergence (A) and Vigor (B) for the four versions of the sweetcorn synthetic EPS18 from Pontevedra (PO), after three cycles of participatory breeding for adaptation to three diverse Spanish locations: Lugo (LU), Burgos (BU), and Barcelona (BA), along with four hybrid checks, evaluated in the most extreme environments: Pontevedra (early and late sowing) and Burgos, during two years.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/bf41fc1bbffa5210e9301b34.jpeg"},{"id":101497820,"identity":"9205e730-fb97-4f7c-a1a2-6f61f7d34f29","added_by":"auto","created_at":"2026-01-30 12:57:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":95277,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in Plant Height (A) and Ear Appearance (B) for the four versions of the sweetcorn synthetic EPS18 from Pontevedra (PO), after three cycles of participatory breeding for adaptation to three diverse Spanish locations: Lugo (LU), Burgos (BU), and Barcelona (BA), along with four hybrid checks, evaluated in the most extreme environments: Pontevedra (early and late sowing) and Burgos, during two years.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/b94402a891a76dc029a44e2f.png"},{"id":101880492,"identity":"1b6ef2b5-f7d7-4384-b50b-bdea22df90ff","added_by":"auto","created_at":"2026-02-04 15:02:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":62991,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in Yield for the four versions of the sweetcorn synthetic EPS18 from Pontevedra (PO), after three cycles of participatory breeding for adaptation to three diverse Spanish locations: Lugo (LU), Burgos (BU), and Barcelona (BA), along with four hybrid checks, evaluated in the most extreme environments: Pontevedra (early and late sowing) and Burgos, during two years.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/38fd58fdf7661003ca861964.png"},{"id":101752848,"identity":"dd4e7ef9-41dc-4d00-93bd-f711ca01d5b9","added_by":"auto","created_at":"2026-02-03 10:36:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":477226,"visible":true,"origin":"","legend":"\u003cp\u003eEmergence percentage and vigor of maize genotypes across three environments. The panels correspond to Pontevedra (early sowing and late sowing), and Burgos. The bars represent different populations and hybrid checks, with different colors and patterns distinguishing the genotypes. Different letters mean significant differences.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/7f8b720b2827a7aef4dc4bff.png"},{"id":101497823,"identity":"401b4c57-de16-475a-88c8-2a723264052e","added_by":"auto","created_at":"2026-01-30 12:57:33","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":249939,"visible":true,"origin":"","legend":"\u003cp\u003eDay to Anthesis and Silking of maize genotypes across three environments. The panels correspond to Pontevedra (early sowing and late sowing). The bars represent different populations and hybrid checks, with different colors and patterns distinguishing the genotypes. Different letters mean significant differences.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/36da37416b3ca6e2aa91bb15.png"},{"id":101497825,"identity":"cffa8f2e-2b87-432f-84cc-fe497ddefedb","added_by":"auto","created_at":"2026-01-30 12:57:33","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":549206,"visible":true,"origin":"","legend":"\u003cp\u003ePlant Height and Ear weight of maize genotypes across three environments. The panels correspond to Pontevedra (early sowing and late sowing), and Burgos. The bars represent different populations and hybrid checks, with different colors and patterns distinguishing the genotypes. Different letters mean significant differences.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/9f772a4a08adfb9e97fb0ec2.png"},{"id":101497827,"identity":"c8b401e5-329a-4c2b-9fd8-bd0888c4cee5","added_by":"auto","created_at":"2026-01-30 12:57:33","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":331016,"visible":true,"origin":"","legend":"\u003cp\u003eEar appearance, Ear length and Plant appearance of maize genotypes across three environments. The panels correspond to Pontevedra (early sowing and late sowing), and Burgos. The bars represent different populations and hybrid checks, with different colors and patterns distinguishing the genotypes. Different letters mean significant differences.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/9df6a014ae6d964c7d8b4d51.png"},{"id":101882092,"identity":"c2ce810e-a46d-4e36-97f7-773da07eadcc","added_by":"auto","created_at":"2026-02-04 15:20:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3859789,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7961927/v1/b6ef5349-f565-4f17-9060-35d5a90ff065.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Participatory plant breeding of sweetcorn for adaptation at diverse Spanish locations","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn 1953, John R. Laughnan proposed the use of the \u003cem\u003eshrunken2\u003c/em\u003e (\u003cem\u003esh2\u003c/em\u003e) allele to produce high-quality sweet corn. Within a few decades, this mutant became the predominant type of sweet corn cultivated in temperate regions. Today, it is estimated that 100% of sweet corn grown for the fresh market and approximately 75% of that used in the processing industry carries the \u003cem\u003esh2\u003c/em\u003e mutation (Tracy et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Despite its rapid success, Laughnan faced a major challenge in introducing this mutant to the market due to the extremely limited genetic diversity available \u0026mdash; no other germplasm carried the \u003cem\u003esh2\u003c/em\u003e allele at the time. Consequently, significant efforts have been made to broaden the genetic base of \u003cem\u003esh2\u003c/em\u003e sweet corn. Some breeders have introgressed the \u003cem\u003esh2\u003c/em\u003e allele into \u003cem\u003eSh2Sh2\u003c/em\u003e inbred lines through crossing and backcrossing, aiming to enhance the agronomic performance of supersweet corn (Revilla et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). While backcrossing is effective for incorporating single recessive alleles, it can also introduce undesirable alleles affecting quality traits inherited from field corn. As an alternative, new variability can be generated by crossing existing \u003cem\u003esh2sh2\u003c/em\u003e genotypes and selecting under diverse environmental conditions.\u003c/p\u003e \u003cp\u003eSmall-scale family farming remains the dominant form of agriculture globally, particularly in low-income countries, and is responsible for the majority of primary agricultural production. However, factors such as the widening income gap between agriculture and other sectors have led to a steady decline in the number of farms and agricultural workers over time (Suess-Reyes and Fuetsch, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kholov\u0026aacute; et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To address this challenge, smallholder farmers are increasingly turning to more profitable agricultural models, including organic farming and the cultivation of high-value, quality-enhanced crops (Bold et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The sustainability of these approaches can be supported through participatory plant breeding (PPB) programs, which improve heritability by enabling in situ selection in target environments. This approach reduces breeding costs and empowers farmers to participate in continuous selection (Colley et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mujjabi et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs a specialty type of maize, sweet corn is marketed as a fresh vegetable, making high quality standards essential for consumer acceptance. At the same time, it offers a promising opportunity for smallholder farmers in temperate regions to produce high-value crops, given its similar agronomic requirements to field maize. PPB, which involves selection in farmers\u0026rsquo; fields under diverse and often low-input conditions, provides a valuable strategy for developing genotypes better adapted to specific environments and production systems, such as organic or family farming (Carkner and Entz, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The objective of this research was to determine whether selection for adaptation to target environments through farmer-led PPB can generate phenotypic diversity associated with local adaptation, without compromising sweet corn quality.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eIn 1996, at the Misi\u0026oacute;n Biol\u0026oacute;gica de Galicia (CSIC), located in the Spanish province of Pontevedra, we developed four synthetic sweet corn populations derived from double-crossed commercial hybrids that were subsequently recombined. After evaluating the agronomic performance and quality of these four populations, EPS18 was selected for further breeding due to its superior characteristics. EPS18 was created by crossing two commercial supersweet corn hybrids, Marvel and 710A, both homozygous for the recessive \u003cem\u003eshrunken2\u003c/em\u003e (\u003cem\u003esh2\u003c/em\u003e) allele. The resulting population was recombined annually through isolated open pollination, with mass selection focused on adaptation to the environmental conditions of Pontevedra (northwestern Spain), continuing until 2018.\u003c/p\u003e\n\u003cp\u003eIn 2018, a participatory plant breeding (PPB) program was initiated in three locations across northern Spain (Table 1), representing a wide range of geographic and climatic conditions. The selected sites were located in the provinces of Lugo, Burgos, and Barcelona, and are referred to hereafter by their respective province names. The climate in Pontevedra features short, warm, and mostly clear summers, with annual temperatures typically ranging from 7 \u0026deg;C to 26 \u0026deg;C, rarely falling below 2 \u0026deg;C or exceeding 32 \u0026deg;C. In O P\u0026aacute;ramo (Lugo), summers are short, warm, dry, and partly cloudy, with temperatures ranging from 1 \u0026deg;C to 26 \u0026deg;C, and extremes between\u0026nbsp;\u0026minus;3 \u0026deg;C and 32 \u0026deg;C. Villang\u0026oacute;mez (Burgos) experiences short, dry summers with minimal cloud cover, and temperatures generally range from\u0026nbsp;\u0026minus;1 \u0026deg;C to 28 \u0026deg;C, with occasional lows of\u0026nbsp;\u0026minus;5 \u0026deg;C and highs of 33 \u0026deg;C. Piera (Barcelona) has short, hot, and mostly clear summers, with a dry climate year-round; temperatures typically range from 1 \u0026deg;C to 30 \u0026deg;C, rarely dropping below\u0026nbsp;\u0026minus;3 \u0026deg;C or rising above 32 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003eThe PPB program involved sowing over 100 EPS18 plants annually at each location. Collaborating farmers selected the 20 most outstanding plants based on growth, health, and ear size and shape, using their own criteria. The selected ears were naturally dried and used as seed for the following season. This process resulted in the first selection cycle in 2018, followed by second and third cycles in 2019 and 2020, respectively. Meanwhile, the original EPS18 population continued to be maintained in Pontevedra using the same methodology. In 2021, the third selection cycles from Lugo, Burgos, and Barcelona, along with the original EPS18 population, were multiplied in Pontevedra through manual crossing of at least 100 plants per cycle, used as both male and female parents.\u003c/p\u003e\n\u003cp\u003eThe original EPS18 population developed in Pontevedra (EPS18PO) was evaluated alongside the third selection cycles from Lugo (EPS18LU), Burgos (EPS18BU), and Barcelona (EPS18BA), as well as two local hybrids (EP84\u0026times;Wh05041 and EP84\u0026times;Wh16005) and two commercial hybrids (GSS15829R and Overland). Uniformly produced seed from all genotypes was evaluated over two growing seasons (2022 and 2023) in two contrasting environments: Pontevedra, representing the original and mildest environment, and Burgos, characterized by the most challenging climatic conditions. Additionally, in Pontevedra, both early and late sowing trials were conducted to assess performance under different planting dates.\u003c/p\u003e\n\u003cp\u003eField trials followed a randomized complete block design with two replications. Each experimental plot consisted of two rows spaced 80 cm apart, with 17 plants per row at 21 cm spacing, resulting in an average plant density of 60,000 plants per hectare. Due to space limitations, single-row plots were used in Burgos. The traits recorded included: emergence rate (percentage of seeds that germinated), plant vigor (rated on a scale from 1 = weak to 9 = vigorous), days from sowing to pollen shedding and silking, plant height (from soil surface to tassel tip), number of marketable ears per plant, plant and ear appearance (rated from 1 = poor to 9 = excellent), ear quality (1 = poor to 9 = excellent), ear weight per square meter, individual ear weight, ear length, and number of kernel rows.\u003c/p\u003e\n\u003cp\u003eAnalysis of variance (ANOVA) was performed for all traits, considering years, locations, replications, and genotypes as sources of variation. All factors were treated as random effects, except genotype, which was considered a fixed effect. Mean comparisons were conducted using Fisher\u0026rsquo;s protected least significant difference (LSD) test at a significance level of P = 0.05 (Steel et al., 1997). To identify environmental factors influencing sweet corn performance, multiple regression analyses were conducted using a stepwise selection method (P = 0.05), with sweet corn traits as dependent variables and environmental parameters (Table 1) as independent variables. All statistical analyses were performed using the Statistical Analysis System (SAS, 2002).\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003eThe objective of this study was to evaluate whether participatory plant breeding (PPB) for adaptation to specific environments could generate phenotypic diversity associated with environmental adaptation, without compromising sweet corn quality. Three cycles of PPB selection of the EPS18 population from three distinct locations \u0026mdash; Lugo (EPS18LU), Burgos (EPS18BU), and Barcelona (EPS18BA) \u0026mdash; were assessed alongside the original EPS18 population from Pontevedra (EPS18PO), two local hybrids (EP84\u0026times;Wh05041 and EP84\u0026times;Wh16005), and two commercial hybrids (GSS15829R and Overland).\u003c/p\u003e\n\u003cp\u003eSignificant differences were observed for ear weight and ear length (Table 2). The Barcelona population (EPS18BA) exhibited the lowest ear weight, significantly differing from the other populations and hybrids. Ear length was significantly greater in the Lugo population (EPS18LU) compared to Burgos (EPS18BU). In both traits, hybrids outperformed the populations (Figure 1). The number of marketable ears per plant was slightly below one across all populations, with no significant differences among genotypes.\u003c/p\u003e\n\u003cp\u003eEmergence rates averaged around 80% across all environments, with populations showing higher emergence than hybrids, which were more affected by adverse conditions (Table 2, Figure 2). Vigor followed a similar pattern, with populations outperforming two of the hybrids (Overland and EP84\u0026times;Wh05041). The commercial hybrid GSS15829R exhibited the tallest plants, significantly exceeding all other genotypes, while no significant differences were found among the remaining populations and hybrids. Regarding ear appearance, Overland and EP84\u0026times;Wh05041 showed superior ratings, although no significant differences were detected among the populations (Table 2, Figure 3). In terms of yield, the four EPS18 populations, along with hybrids GSS15829R and EP84\u0026times;Wh16005, achieved the highest values, significantly outperforming Overland and EP84\u0026times;Wh05041 (Figure 4).\u003c/p\u003e\n\u003cp\u003eSeed quality, assessed through emergence and vigor, was consistently high across all selection cycles. Germination rates of sweet corn hybrids often decline under unfavorable environmental conditions. Analysis of individual environments revealed that selection for adaptation to a specific set of stress factors \u0026mdash; such as the arid climate and alkaline soils of Burgos \u0026mdash; does not necessarily confer improved performance in other environments with different stress profiles, such as the humid climate and acidic soils of Pontevedra. PPB had limited impact on growth cycle duration. However, selection in Lugo, an environment with a shorter growing season, resulted in reduced time to flowering. Effects on plant height were also modest, although selection under the most arid conditions (Burgos) produced shorter plants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePPB did not significantly affect ear appearance or quality. Nevertheless, selection in diverse environments led to improvements in specific ear traits, particularly in Burgos and Barcelona. Notably, ear appearance improved in Burgos, while ear weight increased in both Burgos and Barcelona. Ear length was also enhanced in Burgos compared to Barcelona. These findings indicate that PPB effectively modified the population for agronomic traits such as emergence, vigor, plant height, ear appearance, ear weight, and ear length, while maintaining stable quality parameters.\u003c/p\u003e\n\u003cp\u003eSignificant genotype \u0026times; environment (G\u0026times;E) interactions were observed for several traits, including emergence, vigor (Figure 5), male and female flowering time (Figure 6), ear weight and plant height (Figure 7), ear and plant appearance, and ear length (Figure 8). To better understand these interactions, analyses were conducted separately for each environment: early sowing in Pontevedra (Environment 1), late sowing in Pontevedra (Environment 2), and Burgos (Environment 3).\u003c/p\u003e\n\u003cp\u003eFor emergence, the pattern was consistent across all environments: no significant differences were found among the EPS18 populations, but they consistently exhibited higher emergence rates than all hybrids. Regarding vigor, significant differences were detected in Environment 1, where the populations from Lugo, Pontevedra, and Barcelona showed greater vigor than the hybrids EP84\u0026times;Wh05041 and Overland. In Environment 2, populations again outperformed most hybrids in both emergence and vigor, with significant differences in vigor only between the Pontevedra population and EP84\u0026times;Wh05041 (Figure 5). In early sowing trials (Environment 1), all four EPS18 populations flowered earlier than Overland, which was the latest genotype for both silking and anthesis. The Lugo and Pontevedra populations were the earliest to reach anthesis. Similarly, in late sowing (Environment 2), the Lugo population was the earliest for both silking and anthesis. For plant height in Environment 1, the hybrids EP84\u0026times;Wh05041 and Overland were the shortest, not significantly different from the Lugo population. The tallest genotype was EP84\u0026times;Wh16005, which did not differ significantly from GSS15829R or the populations from Pontevedra and Barcelona. In Environment 2, the Burgos population was significantly shorter than GSS15829R (Figure 7). Ear weight varied across environments. In Environment 1, EP84\u0026times;Wh16005 produced the heaviest ears, while no significant differences were found among the other genotypes. In Environment 2, the Burgos population had the lowest ear weight, and the Lugo and Pontevedra populations produced lighter ears than Overland, which did not differ significantly from the other hybrids or the Barcelona population.\u003c/p\u003e\n\u003cp\u003eEar appearance in Environment 1 was lower in all populations compared to the hybrids, except EP84\u0026times;Wh05041. No significant differences were found in Environments 2 and 3 (Figure 8). For plant appearance in Environment 1, Overland and EP84\u0026times;Wh05041 had the lowest scores. The EPS18 populations did not differ significantly among themselves, and the Pontevedra and Barcelona populations were comparable to the best-performing hybrid, while the Burgos and Lugo populations were similar to the lowest-performing hybrids.\u003c/p\u003e\n\u003cp\u003eEar length also varied across environments. In Environment 1, the longest ears were produced by EP84\u0026times;Wh05041 and Overland, with the Pontevedra and Lugo populations not significantly different from Overland. In Environment 2, the shortest ears were from EP84\u0026times;Wh05041, not differing from Overland or the Lugo population. In Burgos, the shortest ears were from the Burgos population, while the longest were from EP84\u0026times;Wh16005 (Figure 8). In Burgos, ear length was the only trait showing significant differences among genotypes.\u003c/p\u003e\n\u003cp\u003eTo further explore environmental influences on sweet corn traits, multiple linear regression analyses were conducted using sweet corn traits as dependent variables and environmental descriptors (Table 3) as independent variables. Significant regression models were:\u003c/p\u003e\n\u003cp\u003e1. Emergence = 87.05 \u0026ndash; 0.044 \u0026times; Distance to sea (R\u003csup\u003e2\u003c/sup\u003e = 0.95*)\u003c/p\u003e\n\u003cp\u003e2. Vigor = 6.17 \u0026ndash; 0.006 \u0026times; Distance to sea (R\u003csup\u003e2\u003c/sup\u003e = 0.96*)\u003c/p\u003e\n\u003cp\u003e3. Plant height = 160.9 + 1.7 \u0026times; Yearly temperature (R\u003csup\u003e2\u003c/sup\u003e = 0.91*)\u003c/p\u003e\n\u003cp\u003e4. Plant appearance = 4.96 \u0026ndash; 0.0014 \u0026times; Distance to sea (R\u003csup\u003e2\u003c/sup\u003e = 0.16*) + 0.0003 \u0026times; Yearly rainfall (R\u003csup\u003e2\u003c/sup\u003e = 0.84*)\u003c/p\u003e\n\u003cp\u003e5. Row number = 18.16 \u0026ndash; 0.0029 \u0026times; Distance to sea (R\u003csup\u003e2\u003c/sup\u003e = 0.14*) \u0026ndash; 0.001 \u0026times; Yearly rainfall (R\u003csup\u003e2\u003c/sup\u003e = 0.86*)\u003c/p\u003e\n\u003cp\u003eThe regression models revealed that emergence and early vigor were primarily explained by the distance from the sea, accounting for 95% and 96% of the variability, respectively. Annual temperature explained 91% of the variability in plant height. For plant appearance and number of kernel rows per ear, annual rainfall was the main explanatory factor, accounting for 84% and 86% of the variability, respectively, with distance to the sea contributing an additional 16% and 14%. In contrast, no environmental variable was significantly associated with days to anthesis or silking, ears per plant, ear appearance and quality, or ear weight (per ear or per area), and thus these traits were not included in the final regression models.\u003c/p\u003e\n\u003cp\u003eA basic characterization of the selection environments indicated that several environmental patterns influenced the response to selection. The most influential factor was distance to the sea, as locations closer to the coast tended to have lower elevation, warmer temperatures, and greater solar radiation. However, rainfall varied, with Pontevedra receiving the highest and Barcelona the lowest annual precipitation. Distance to the sea had a negative effect on emergence, vigor, plant appearance, and kernel row number. Rainfall positively influenced plant appearance but negatively affected row number, while temperature had a positive effect on plant height. Thus, emergence, vigor, and plant height were significantly influenced by a single environmental parameter, whereas plant appearance and row number were affected by two. The remaining traits showed no significant association with the environmental variables considered.\u003c/p\u003e\n\u003cp\u003eOverall, these findings demonstrate clear environmental effects on the response to participatory breeding of sweet corn across diverse conditions. The main environmental drivers of breeding outcomes were temperature and water availability, with the most affected traits being yield and plant growth. Importantly, quality traits remained stable across environments. These results align with previous studies, such as Colley et al. (2022), who emphasized the benefits of PPB programs that leverage increased heritability through in situ selection. Similarly, Ceccarelli and Grando (2006) reported successful PPB initiatives that rapidly developed varieties adapted to marginal environments and traditional farming systems, while enhancing biodiversity. Dawson et al. (2008) also highlighted the suitability of PPB for heterogeneous environments and alternative agricultural systems, including organic farming.\u003c/p\u003e\n\u003cp\u003eBased on these results, PPB applied to a sweet corn synthetic with a narrow genetic base proved effective in improving adaptation to specific environmental conditions without compromising quality. Therefore, the participatory breeding program can be continued and potentially expanded to additional target environments. In conclusion, selection for adaptation to local conditions successfully generated phenotypic diversity in traits related to plant growth and yield, driven by environmental factors \u0026mdash; particularly temperature and water availability \u0026mdash; while maintaining stable quality traits.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e This research is part of the project PID2022-140991OB-I00, funded by MCIN/AEI/10.13039/501100011033/FEDER, UE. The authors thank to Eleuterio, Tom\u0026aacute;s and Jes\u0026uacute;s Revilla for their commitment to carry out this program, and to the Maize Breeding and Genetics team of Misi\u0026oacute;n Biol\u0026oacute;gica de Galicia (CSIC) for assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u0026nbsp;\u003c/strong\u003eAna L\u0026oacute;pez-Malvar and Lorena \u0026Aacute;lvarez data curation, investigation, and writing; Pedro Revilla conceptualization, formal analysis, funding acquisition, writing. All authors have reviewed and edited the final manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003eData are available from the authors upon request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBold T, Ghisolfi S, Nsonzi F, Svensson J (2022). Market access and quality upgrading: Evidence from four field experiments. Am Econ Rev 112: 2518-2552.\u003c/li\u003e\n \u003cli\u003eCarkner MK, Entz MH (2024). Determining adaptability of farmer bred spring wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L.) genotypes to Canadian organic production using stability analysis. Plant Breed 143: 500-517.\u003c/li\u003e\n \u003cli\u003eCeccarelli S, Grando S (2006). Decentralized-participatory plant breeding: An example of demand driven research. Euphytica 155: 349\u0026ndash;360.\u003c/li\u003e\n \u003cli\u003eColley MR, Tracy WF, Lammerts van Bueren ET, Diffley M, Almekinders CJM (2022). How the Seed of Participatory Plant Breeding Found Its Way in the World through Adaptive Management. Sustainability 14: 2132.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDawson JC, Murphy KM, Jones SS (2008). Decentralized selection and participatory approaches in plant breeding for low-input systems. Euphytica 160: 143\u0026ndash;154.\u003c/li\u003e\n \u003cli\u003eKholov\u0026aacute; J, Urban MO, Bavorov\u0026aacute; M, Ceccarelli S, Cosmas L, Desczka S, Bulte E (2024). Promoting new crop cultivars in low-income countries requires a transdisciplinary approach. Nature Plants 10: 1610-1613.\u003c/li\u003e\n \u003cli\u003eLaughman JR (1953). The effect of \u003cem\u003esh2\u003c/em\u003e factor on carbohydrate reserves in the mature endosperm of maize. Genetics 38: 485-499.\u003c/li\u003e\n \u003cli\u003eMujjabi C, Bohn MO, Wander MM, Ugarte CM (2024). Participatory breeding in organic systems: Experiences from maize case studies in the United States. J Agr Food Syst Com Develop 13: 23\u0026ndash;36.\u003c/li\u003e\n \u003cli\u003eRevilla P, Malvar RA, Rodr\u0026iacute;guez VM, Butr\u0026oacute;n A, Ord\u0026aacute;s B, Ord\u0026aacute;s A (2006). Variation of \u003cem\u003esugary1\u003c/em\u003e and \u003cem\u003eshrunken2\u003c/em\u003e frequency in different maize genetic backgrounds. Plant Breed 25: 478-481.\u003c/li\u003e\n \u003cli\u003eSAS Institute Inc (2002). SAS OnlineDoc, version 9. SAS Institute, Inc, Cary, North Carolina, USA.\u003c/li\u003e\n \u003cli\u003eSteel RDG, Torrie J-H, Dickey DA (1997). Principles and Procedures in Statistics: A Biometrical Approach. 3rd ed. Mc Graw Hill, New York.\u003c/li\u003e\n \u003cli\u003eSuess-Reyes J, Fuetsch E (2016). The future of family farming: A literature review on innovative, sustainable and succession-oriented strategies. J Rural Stud 47: 117-140.\u003c/li\u003e\n \u003cli\u003eTracy WF, Shuler SL, Dodson-Swenson H (2019). The use of endosperm genes for sweet corn improvement: A review of developments in endosperm genes in sweet corn since the seminal publication in Plant Breeding Reviews, Volume 1, by Charles Boyer and Jack Shannon (1984). In I. Goldman (Ed.), Plant Breed Rev 43: 215\u0026ndash;241. John Wiley and Sons.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Spanish locations and provinces (in parenthesis) involved in the participatory breeding program of the super sweet corn synthetic EPS18\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eLocation and province\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eCoordinates\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eHeight above the sea level (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDistance from the sea (km)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMean annual rainfall (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eMean annual temperature (\u0026ordm;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ePontevedra (Pontevedra)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e42\u0026ordm;25\u0026rsquo;53\u0026rsquo;\u0026rsquo; N 8\u0026ordm;38\u0026rsquo;37\u0026rsquo;\u0026rsquo; W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eO P\u0026aacute;ramo (Lugo)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e42\u0026ordm;50\u0026rsquo;39\u0026rsquo;\u0026rsquo; N 7\u0026ordm;29\u0026rsquo;56\u0026rsquo;\u0026rsquo; W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eVillang\u0026oacute;mez (Burgos)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e42\u0026ordm;10\u0026rsquo;50\u0026rsquo;\u0026rsquo; N 3\u0026ordm;46\u0026rsquo;22\u0026rsquo;\u0026rsquo; W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003ePiera (Barcelona)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e41\u0026ordm;31\u0026rsquo;14\u0026rsquo;\u0026rsquo; N 1\u0026ordm;44\u0026rsquo;49\u0026rsquo;\u0026rsquo; E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2. Means\u0026rsquo; comparisons\u003csup\u003ea\u003c/sup\u003e of four versions of the sweetcorn synthetic EPS18 produced in Pontevedra (PO), after three cycles of participatory breeding for adaptation to three diverse Spanish locations: Lugo (LU), Burgos (BU), and Barcelona (BA), along with four hybrid checks, evaluated in the most extreme environments: Pontevedra (early and late sowing) and Burgos two years. The four checks were included only in the two environments of Pontevedra due to limiting availability in the farmer\u0026rsquo;s field.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"850\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eEmergence (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eVigor (1-9)\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eDays to anthesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eDays to silking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ePlant height (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eEars /plant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003ePlant appearance\u003c/p\u003e\n \u003cp\u003e(1-9)\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEPS18PO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e87.4a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.1a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e64.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e65.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e187.7b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEPS18LU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e81.7a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.7ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e62.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e177.8b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEPS18BU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e80.6a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.2ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e65.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e67.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e180.7b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEPS18BA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e85.3a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.0ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e64.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e67.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e192.8b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEP84\u0026times;Wh05041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e16.9d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e2.8c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e66.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e67.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e197.0b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEP84\u0026times;Wh16005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e67.1b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e4.7b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e64.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e67.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e194.0b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eGSS15829R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e33.1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e4.8ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e65.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e66.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e225.3a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eOverland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e16.2d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e3.0c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e69.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e70.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e189.8b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eLSD (0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e25.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 718px;\"\u003e\n \u003cp\u003eEar traits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eEar appearance (1-9)\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eQuality (1-9)\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eEar weight /m\u003csup\u003e2\u003c/sup\u003e (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eEar weight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eEar length (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eRow number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEPS18PO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e4.3c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.89a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.370c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e19.41cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e16.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEPS18LU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e5.1bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.95a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.375c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e20.22c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e16.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEPS18BU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e4.9bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.88a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.317d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e18.00d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e17.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEPS18BA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e4.5c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.92a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.373c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e19.16cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e17.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEP84\u0026times;Wh05041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e5.0a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.40b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.393bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e24.23a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e18.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eEP84\u0026times;Wh16005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e6.5bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.75a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.485a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e20.34bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e18.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eGSS15829R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e6.0ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.74a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.393bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e18.53cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e18.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eOverland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e7.0a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.38b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.413b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e22.25ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e17.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eLSD (0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Means followed by the same letter are not significantly different based on Fisher\u0026rsquo;s protected LSD at P = 0.05\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Scale from 1 = weak plants to 9 = vigorous plants for early vigor, or 1 = poor to 9 = great for appearance related traits and quality\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3. Means of the four environments involved in the participatory breeding program of the sweetcorn synthetic EPS18\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"862\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eEmergence (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eVigor (1-9)\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eDays to pollen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eDays to silking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePlant height (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eEars /plant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003ePlant appearance (1-9)\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003ePontevedra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e87.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e64.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e65.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e187.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eLugo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e81.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e62.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e177.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eBurgos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e80.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e65.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e67.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e180.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eBarcelona\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e85.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e64.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e67.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e192.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 739px;\"\u003e\n \u003cp\u003eEar traits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eEar appearance (1-9)\u003csup\u003e\u0026nbsp;\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eQuality (1-9)\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eEar weight /m2 (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eEar weight *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eEar length (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eRow number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003ePontevedra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eLugo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e16.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eBurgos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e18.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eBarcelona\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e17.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Scale from 1 = weak plants to 9 = vigorous plants for early vigor, or 1 = poor to 9 = great for appearance related traits and quality\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"euphytica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"euph","sideBox":"Learn more about [Euphytica](https://www.springer.com/journal/10681)","snPcode":"10681","submissionUrl":"https://submission.springernature.com/new-submission/10681/3","title":"Euphytica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Sweetcorn quality, PPB, Spanish environments, phenotypic diversity","lastPublishedDoi":"10.21203/rs.3.rs-7961927/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7961927/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSweet corn homozygous for the \u003cem\u003eshrunken2\u003c/em\u003e (\u003cem\u003esh2\u003c/em\u003e) mutation exhibits narrow genetic diversity and limited adaptation to diverse environments. This study aimed to assess whether participatory plant breeding (PPB), led by farmers in specific environments, can enhance adaptation and generate phenotypic diversity associated with local conditions without compromising quality. Starting from the synthetic sweet corn population EPS18 \u0026mdash; originally developed in the Spanish province of Pontevedra and with low genetic diversity \u0026mdash; three PPB selection cycles were conducted in three ecologically distinct Spanish provinces: Lugo, Burgos, and Barcelona. The third selection cycle from each location was evaluated alongside the original EPS18 population and four commercial hybrids in both Pontevedra (the original site) and Burgos (the most environmentally challenging site). Temperature and water availability emerged as the primary environmental factors influencing selection outcomes. Yield and plant growth were the most affected traits, while quality parameters remained largely unchanged. These results demonstrate that PPB can effectively improve the adaptation of a genetically narrow sweet corn population to diverse northern Spanish environments without sacrificing quality. We conclude that selection for local adaptation through PPB can successfully induce phenotypic diversity in traits related to plant growth and yield, driven by environmental variables \u0026mdash; particularly temperature and water availability \u0026mdash; while maintaining desirable quality traits.\u003c/p\u003e","manuscriptTitle":"Participatory plant breeding of sweetcorn for adaptation at diverse Spanish locations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-30 12:57:28","doi":"10.21203/rs.3.rs-7961927/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-25T12:24:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"222124031405224413770891248028840894162","date":"2026-02-13T08:41:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-12T15:50:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-11T15:52:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293374899846792325442802931654058233096","date":"2026-02-04T05:48:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-02T17:41:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176934410506865821214723864388445404783","date":"2026-02-02T08:15:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124649008641244411231934320794864626464","date":"2026-01-30T16:25:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25452560284889460744850475490607102860","date":"2026-01-28T22:31:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-28T07:52:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-28T15:00:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-28T14:59:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Euphytica","date":"2025-10-27T14:55:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"euphytica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"euph","sideBox":"Learn more about [Euphytica](https://www.springer.com/journal/10681)","snPcode":"10681","submissionUrl":"https://submission.springernature.com/new-submission/10681/3","title":"Euphytica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ee4e3de0-b244-4aad-b5da-88b5e3ac14e0","owner":[],"postedDate":"January 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-30T12:57:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-30 12:57:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7961927","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7961927","identity":"rs-7961927","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}