Interannual variability of planting-date effects on Fusarium verticillioides grain colonization and fumonisin contamination in maize

Interannual variability of planting-date effects on Fusarium verticillioides grain colonization and fumonisin contamination in maize | 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 Interannual variability of planting-date effects on Fusarium verticillioides grain colonization and fumonisin contamination in maize María Cecilia Pérez-Pizá, Sebastián Vicente, Francisco José Sautua, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8612955/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Fusarium ear rot, primarily caused by Fusarium verticillioides , and the associated fumonisin contamination represent major sanitary constraints to maize ( Zea mays L.) production worldwide. Previous single-season evidence under Argentine conditions indicated that late planting enhances fungal colonization and fumonisin accumulation in maize grains. Here, we evaluated the interannual variability of these planting-date effects through a multi-year field analysis conducted across three independent growing seasons (2020–2024). F. verticillioides grain colonization, fumonisin contamination, grain yield, and nutritional composition were assessed under contrasting planting dates (early vs. late) in San Antonio de Areco, Buenos Aires, Argentina. Across seasons, late plantings consistently exhibited higher F. verticillioides grain colonization, accompanied by markedly increased fumonisin concentrations, whereas early plantings showed lower sanitary pressure and higher yields. However, the magnitude of these responses and the relationship between fungal abundance and fumonisin accumulation varied substantially among years, indicating strong modulation by environmental conditions. Grain nutritional composition remained comparatively stable across planting dates and seasons. Overall, these results demonstrate that while the direction of planting-date effects on maize sanitary status is maintained across years, their intensity is highly dependent on interannual climatic variability. Under the evaluated conditions, early planting emerged as the most reliable strategy to reduce fumonisin risk while sustaining productivity in maize cropping systems. Zea mays Fusarium verticillioides fumonisins planting date interannual variability meteorological conditions Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION Maize ( Zea mays L.) ranks among the most important cereal crops worldwide, not only for its significant contribution to global food and feed supplies, but also as a raw material for various industrial applications (Bond, 2025 ). In Argentina, its cultivation spans diverse agroecological regions and plays a strategic role within extensive cropping systems (Maddonni et al., 2024 ). However, maize productivity and safety are frequently compromised by fungal diseases that colonize ears and grains, resulting in reduced yield and altered nutritional and sanitary quality (Sautua et al., 2018 ; Chiotta et al., 2020 ). Within this context, Fusarium species, particularly F. verticillioides , F. proliferatum , and F. graminearum , constitute the predominant pathogens of concern due to their capacity to infect developing kernels and synthesize mycotoxins such as fumonisins (FBs), deoxynivalenol (DON), and zearalenone (ZEA), which pose serious health risks to humans and animals (Krnjaja et al., 2019 , 2022 ; Logrieco et al., 2021 ). The extent of fungal colonization and mycotoxin contamination depends on complex interactions among host genotype, agronomic management, and environmental conditions throughout the growing cycle (Cao et al., 2014 ; Qi et al., 2023 ; Bugingo et al., 2025 ). In the past decade, Argentine maize production systems have progressively shifted from early-spring to late-summer planting (Papucci et al., 2016 ). This transition has been largely driven by the need to minimize the coincidence between flowering and water stress episodes, thereby stabilizing yields under increasingly variable rainfall patterns (Maddonni, 2012 ; Espósito and Ferraguti, 2019 ). Nonetheless, late planting can markedly modify the environmental conditions experienced by maize around silking and physiological maturity (Espósito and Ferraguti, 2019 ; Krnjaja et al., 2019 ), often shifting these critical stages toward conditions that favor F. verticillioides establishment, delay kernel drying, and increase the risk of fumonisin accumulation (Martínez and Moschini, 2010 ; Blandino et al., 2017 ; Moschini et al., 2020 ; Logrieco et al., 2021 ). Consequently, several studies have linked late planting to increased ear rot severity, higher incidence of Fusarium spp., and greater fumonisin accumulation (Castañares et al., 2019 ). In a previous study, Pérez-Pizá et al. ( 2024 ) demonstrated that the maize planting period exerts a strong influence on grain sanitary and nutritional attributes. Under Argentine field conditions, early planting resulted in higher yield and improved grain quality, whereas late planting promoted greater F. verticillioides colonization and FBs accumulation. Moreover, a positive linear association was observed between fungal incidence and toxin levels, providing a quantitative basis for linking field infection to mycotoxin contamination. However, these findings were derived from a single growing season, and the degree to which such relationships persist under different climatic scenarios remains unclear. Given that Fusarium infection and FBs biosynthesis are highly responsive to temperature, humidity, and rainfall distribution, multi-year studies are essential to evaluate the temporal consistency of these patterns and the magnitude of interannual variability. The present study addresses this knowledge gap by assessing the interannual variability of Fusarium mycobiota and FBs contamination in maize grains under contrasting planting dates across multiple growing seasons in Argentina. By integrating agronomic, nutritional, and sanitary parameters from three independent campaigns (2020–2024), this work extends previous evidence into a broader temporal framework. We hypothesized that planting date would consistently influence F. verticillioides grain colonization and FBs contamination, although the magnitude of these effects and the relationships between fungal abundance and mycotoxin accumulation would vary among growing seasons depending on environmental conditions. Understanding such variability is critical for developing predictive tools and refining management strategies aimed at reducing mycotoxin risk in maize production systems. 2. MATERIALS AND METHODS 2.1. Field experiments, determination of yield and sampling Field experiments were conducted over three independent maize growing seasons between 2020 and 2024 at the Experimental Field ‘La Fe’, AER INTA San Antonio de Areco, Buenos Aires, Argentina (-34.280625 S, -59.468321 W). Each growing season comprised one or two planting dates, depending on environmental conditions. Early planting (mid-September to early October) was performed in the 2020–21, 2021–22, and 2023–24 seasons, whereas late planting (mid-December to early January) was possible only in the 2020–21, 2022–23, and 2023–24 seasons. The study evaluated multiple commercial maize hybrids in hybrid-comparison trials. All hybrids carried resistance to major ear- and stalk-feeding lepidopteran pests. Each hybrid was treated as an independent data point for subsequent analyses. All field trials corresponded to official INTA hybrid-comparison experiments established in long, machine-harvestable plots (200-m length), managed according to standard field practices and conducted under no-till conditions. Previous crops consisted exclusively of non-maize species typical of regional rotations (e.i., vetch, oat, wheat/second soybean, and first soybean) depending on season and planting date (Table S1 ). No trial had maize as preceding crop, thus minimizing local inoculum carryover of F. verticillioides from maize stubble. Soil chemical properties at sowing (pH, organic matter, P Bray, nitrate-N) were provided in the original INTA reports corresponding to each season and summarized in Table S2. The presence of each hybrid across seasons and planting dates is detailed in Table S3. Sowing, flowering, and harvest dates for each season and planting type are presented in Table S1 . Harvest was performed approximately 15 days after physiological maturity (R6), when grain moisture had decreased to ≈ 14%. All plots were harvested with a combine harvester equipped with a yield monitor, and yield measurements were validated using a calibrated weigh wagon (“tolva balanza”); therefore, grain yield (GY) represents the production of the full net plot area. Yield components (number of grains per square meter, NGM; and 1000-grain weight, TGW) were also determined at harvest, following the procedures described by Pérez-Pizá et al. ( 2024 ). Grain samples for laboratory analyses were collected simultaneously, with approximately 1 kg of grain per plot placed in labeled craft paper bags and stored at 4°C until processing for grain mycobiota characterization and mycotoxin analysis. Data from the first campaign (2020–2021), previously published by Pérez-Pizá et al. ( 2024 ), were re-incorporated to provide a multi-year framework for comparison with subsequent campaigns (2021–2022 and 2023–2024 for early planting; 2022–2023 for late planting). 2.2. Quantification, isolation, and identification of grain-associated mycobiota Quantification and identification of grain-associated fungi followed the general procedures described by Pérez-Pizá et al. ( 2024 ). Briefly, the mycological quality of grains was assessed by quantifying colony-forming units (CFU) of filamentous fungi and yeasts, following Gimeno and Martins (2011) and Castellari et al. (2015). Decimal dilutions of grain suspensions were plated on chloramphenicol-supplemented glucose yeast extract agar (YGCA) and incubated at 25°C for seven days. The total number of viable fungi (NTotal, CFU g⁻¹) was calculated according to ANMAT (2014) guidelines. Fungal colonies were identified morphologically and confirmed by microscopic examination of conidial features. Colonization of maize grains by F. verticillioides was operationally assessed as the viable fungal population recovered from harvested grains (NFv), expressed as colony-forming units per gram (CFU g⁻¹) and determined using the same criteria applied for NTotal, considering only colonies of that species. The identity of F. verticillioides isolates was further verified by PCR amplification of the VERT locus (primers VERT-1 and VERT-2) and the TEF1 locus (primers EF-728 M and EF-2), as detailed by Pérez-Pizá et al. ( 2024 ). 2.3. Fumonisins quantification For fumonisin determinations (Total FBs, µg kg-1), extraction, cleanup, and chromatographic procedures followed the validated methods described in AOAC Official Method 995.15 (AOAC International, 1999 ). Briefly, 500 g of maize was ground, and a 50 g analytical sample was extracted with a methanol:water (3:1, v/v) solution, filtered, adjusted to pH 6, centrifuged, and purified using strong anion exchange columns for solid-phase extraction (SPE) cleanup. The eluates were evaporated to dryness and analyzed by HPLC with fluorescence detection after o-phthalaldehyde (OPA) derivatization. Calibration procedures, detection parameters, and LOD/LOQ values were as reported by Pérez-Pizá et al. ( 2024 ). 2.4. Grain quality and nutritional composition Grain crude protein (Protein, %), lipid (Lipid, %), and fiber (Fiber, %) contents were determined by near-infrared spectroscopy (NIRS). All analyses were performed on homogenized subsamples of the same grain lots used for fungal and fumonisin assessments, following the analytical procedures detailed in Pérez-Pizá et al. ( 2024 ). Gross energy (GE, kcal kg⁻¹) was estimated from crude nutrient composition using a prediction equation (Olocco-Diz et al., 2017 ). 2.5. Data analysis Data were tested for normality and homoscedasticity before analysis. Global comparisons between planting dates (early vs. late) were conducted using t-tests, whereas seasonal differences within each planting date were evaluated by one-way ANOVA followed by Tukey’s test (p < 0.05). Linear regressions were performed to assess the relationship between F. verticillioides population counts (NFv) and total fumonisin concentrations (FBs) within each campaign. All statistical analyses were carried out using InfoStat v.2024 (Di Rienzo et al., Universidad Nacional de Córdoba, Argentina), and all figures were generated using GraphPad Prism v.5.0 (GraphPad Software, San Diego, CA, USA). 3. RESULTS AND DISCUSSION Data from three independent growing seasons (2020–2024) were jointly analyzed to assess the interannual variability of planting-date effects on sanitary traits (NTotal, NFv), mycotoxin contamination (Total FBs), grain nutritional composition (protein, lipid, fiber, and gross energy), and productive performance (GY, NGM, and TGW). The 2020–2021 dataset, previously reported by Pérez-Pizá et al. ( 2024 ), was re-incorporated to provide a broader multi-year framework for comparison. 3.1. Mycobiota associated with maize grains 3.1.1. Total fungal population counts (NTotal) and mycological quality Across the three monitored seasons (2020–2024), total fungal populations associated with maize grains (NTotal) exhibited marked interannual and planting-date variability (Fig. 1 A). In early planting, mean NTotal values increased significantly among seasons (p = 0.0002), from approximately 2 × 10⁴ CFU g⁻¹ in 2020–2021 to 4.8 × 10⁴ CFU g⁻¹ in 2021–2022, and then slightly decreased to 3.6 × 10⁴ CFU g⁻¹ in 2023–2024. According to Tukey’s test, the first season differed from the subsequent two (C 20/21 < C 21/22, C 23/24), which did not differ from each other. [INSERT Fig. 1 HERE] In late planting, interannual differences were also significant (p = 0.0045). Mean NTotal increased from approximately 9.6 × 10⁴ CFU g⁻¹ in 2020–2021 to 1.5 × 10⁵ CFU g⁻¹ in 2022–2023, before decreasing to 8.6 × 10⁴ CFU g⁻¹ in 2023–2024. The 2022–2023 season showed significantly higher values than the other two (C 22/23 > C 20/21, C 23/24). When results were integrated across campaigns (Table 1 ), late plantings exhibited a highly significant overall increase in total mycobiota (p < 0.0001), with mean NTotal values (1.1 × 10⁵ CFU g⁻¹) more than threefold higher than those of early plantings (3.3 × 10⁴ CFU g⁻¹). According to the classification proposed by Gimeno and Martins (2011), early-planting samples mostly fell within the good (≤ 4 × 10⁴ CFU g⁻¹) or regular (4 × 10⁴ – 1 × 10⁵ CFU g⁻¹) mycological quality categories, whereas late plantings were predominantly regular or poor (> 1 × 10⁵ CFU g⁻¹). Table 1 Summary of sanitary, yield, and nutritional traits of maize grains collected under early and late planting dates across three growing seasons (2020–2024). Variables include total fungal population counts (NTotal), Fusarium verticillioides population counts (NFv, CFU g⁻¹), total fumonisins (Total FBs, µg kg⁻¹), grain yield (GY, kg ha⁻¹), number of grains per square meter (NGM, grains m⁻²), thousand-grain weight (TGW, g), lipid content (Lipids, %), protein content (Protein, %), fiber content (Fiber, %), and relative energy (RE, kcal kg⁻¹). Different lowercase letters within each variable indicate significant differences between planting dates (Tukey’s test, p < 0.05), based on the comparison of all early-planting data pooled across campaigns versus all late-planting data pooled across campaigns. Variable Early (mean ± SE) Range (Min-Max) Late (mean ± SE) Range (Min-Max) p-value Sanitary traits Ntotal (CFU g⁻¹) 32420 ± 3559 b 9091–78180 109400 ± 8839 a 37950–194200 < 0.0001 NFv (CFU g⁻¹) 11700 ± 2520 b 454–41820 55570 ± 4831 a 8636–99390 < 0.0001 Total FBs (µg kg⁻¹) 1058 ± 202 b 62–5007 6758 ± 1598 a 650–31430 0.0002 Yield and yield components GY (kg ha⁻¹) 7831 ± 443 a 5041–13530 6040 ± 263 b 4609–9510 0.0024 NGM (grains m⁻²) 3344 ± 140 a 2199–5086 2230 ± 179 b 966–4561 < 0.0001 TGW (g) 328.0 ± 6 a 282–403 339.8 ± 9 a 285–445 0.2812 Nutritional traits Lipids (%) 3.76 ± 0.07 a 3.13–4.53 3.72 ± 0.06 a 3.32–4.20 0.6736 Protein (%) 7.55 ± 0.08 a 8.58–9.21 7.09 ± 0.14 a 8.27–9.64 0.0529 Fiber (%) 2.00 ± 0.03 a 1.77–2.29 1.99 ± 0.03 a 1.85–2.33 0.9170 RE (kcal kg⁻¹) 4411 ± 2.30 a 4395–4436 4406 ± 3.30 a 4383–4440 0.2459 [INSERT Table 1 HERE] Since mycological quality derived from NTotal values does not necessarily reflect the sanitary safety of grains, the following section focuses on F. verticillioides as the principal toxigenic component of the grain-associated mycobiota. 3.1.2. Fusarium verticillioides population counts (NFv) Across the three monitored seasons (2020–2024), NFv exhibited clear differences between planting dates and relatively stable interannual behavior within each (Fig. 1 B). In early plantings, interannual differences were significant (p = 0,0002), with the first campaign showing significantly lower values than the subsequent two. The mean NFv values ranged from 5.3 × 10 3 CFU g⁻¹ (min 4.5 × 10 2 ; max 1.8 × 10⁴) in 2020–2021 to 2.3 × 10⁴ CFU g⁻¹ (min 9.1 × 10 3 ; max 4.2 × 10⁴) in 2021–2022 and 2.5 × 10⁴ CFU g⁻¹ in 2023–2024 (min 4.3 × 10 3 ; max 3.7 × 10⁴). These results indicate that early planting effectively restricted F. verticillioides proliferation, maintaining low fungal colonization levels. In late plantings, by contrast, NFv counts were consistently higher but statistically homogeneous among years (p = 0,4108). Mean values ranged from approximately 4.5 × 10⁴ to 6.5 × 10⁴ CFU g⁻¹ (min 8.6 × 10 3 ; max 9.9 × 10⁴), confirming that late planting systematically favored F. verticillioides colonization. When data were integrated across seasons (Table 1 ), the overall effect of planting date was highly significant (t-test, p < 0.0001). Late plantings exhibited mean NFv values of approximately 5.6 × 10⁴ CFU g⁻¹, nearly fivefold greater than those recorded in early planting (1.2 × 10⁴ CFU g⁻¹). This pattern mirrors that observed for NTotal, reinforcing that delayed planting markedly enhanced fungal presence. Importantly, all evaluated hybrids carried Bt or equivalent resistance traits, a prerequisite for late planting in Argentina due to intense lepidopteran pressure (Aapresid, 2022 ; Bonivardo et al., 2025 ). Because insect injury is a well-known predisposing factor for ear infection by F. verticillioides (Barroso et al., 2017 ; Li et al., 2023 a,b), the high NFv levels recorded in late compared with early plantings despite the use of insect-resistant hybrids strongly indicate that the differences observed here were driven by environmental conditions rather than by insect damage. 3.2. Fumonisin contamination Total fumonisins (Total FBs = FB₁ + FB₂) exhibited pronounced variability among planting dates and seasons (Fig. 1 C; Tables 1 – 2 ). Table 2 Total fumonisin (FBs, µg kg⁻¹) concentrations measured in maize hybrids across three campaigns under early and late planting dates. Exceedances of internationally and nationally established regulatory thresholds are indicated with “x”. Data from 2020–2021 were already published in Pérez-Pizá et al. ( 2024 ) and are included here as a reference. Hybrid Total FBs (µg kg⁻¹) > 1000* > 2000** > 4000*** Total FBs (µg kg⁻¹) > 1000* > 2000** > 4000*** Early 2020–2021 Late 2020–2021 A 1361,00 x 6317,00 x x x B 84,00 6997,00 x x x C 1457,00 x 2231,00 x x D 685,00 2691,00 x x E 2069,00 x x 5696,00 x x x F 131,00 2418,00 x x G 5007,00 x x x 650,00 H 867,00 2639,00 x x I 522,00 1043,00 x J 1704,00 x 3696,00 x x K 1889,00 x 7184,00 x x x L 108,70 2358,00 x x M 161,90 9396,00 x x x Hybrid Early 2021–2022 Late 2022–2023 B 1254,00 x 5246,00 x x x C 633,00 - D 904,00 17630,00 x x x F 87,00 - G 1646,00 x 8404,00 x x x I 1412,00 x 4826,00 x x x K 1035,00 x 1927,00 L 1068,00 x - M 1927,00 x - Hybrid Early 2023–2024 Late 2023–2024 B 352,00 31428,00 x x x G 835,00 - I 62,00 - K 248,00 - L - 12375,00 x x x *1000 µg kg⁻¹: European Commission Regulation (EC) No. 1126/2007, maximum level for maize intended for direct human consumption. ** > 2000 µg kg⁻¹: Argentine Food Code (CONAL/Codex Alimentarius Commission, 2019), maximum level for maize by-products. *** > 4000 µg kg⁻¹: European Commission Regulation (EC) No. 1126/2007, maximum level for unprocessed maize. In early plantings, mean Total FBs values remained low and stable across the three campaigns ( p = 0.3535), ranging from 374 to 1234 µg kg⁻¹ (min 62; max 5007; Fig. 1 C). When all early-planting data were considered together, most hybrids (12 out of 14) maintained fumonisin concentrations below 2000 µg kg⁻¹ and thus remained under both international and national regulatory thresholds (1000 µg kg⁻¹ for maize intended for human consumption and 4000 µg kg⁻¹ for unprocessed maize; European Commission Regulation 1126/2007; CONAL/Codex Alimentarius Commission, 2019). Exceedances were sporadic and restricted to two hybrids (E and G) in 2020–2021 (Table 2 ), confirming the overall stability of early planting in limiting fumonisin biosynthesis. [INSERT Table 2 HERE] In contrast, late planting showed recurrent and significant increases in fumonisin contamination across years ( p = 0.0008; Fig. 1 C). Mean Total FBs values rose from 4101 µg kg⁻¹ in 2020–2021 to 7607 µg kg⁻¹ in 2022–2023 and then escalated dramatically to > 21900 µg kg⁻¹ in 2023–2024. This sharp rise during the last campaign suggests that the environmental conditions prevailing during grain filling in 2023–2024 were particularly conducive to mycotoxin accumulation. Most late-planting hybrids (15 out of 18) exceeded 1000 µg kg⁻¹, two-thirds (12 out of 18) surpassed 2000 µg kg⁻¹, and 8 out of 18 reached or exceeded 4000 µg kg⁻¹ (the limit for unprocessed maize) while 4 out of 18 even exceeded 10000 µg kg⁻¹ (Table 2 ). Although some hybrids (G, I, and K) displayed low fumonisin levels in one season, these same genotypes showed high concentrations in another (Table 2 ). Overall, no hybrid exhibited a consistently low-fumonisin profile under late-planting conditions. When data were pooled across campaigns (Table 1 ), the overall effect of planting date on fumonisin concentration was highly significant ( t -test, p = 0.0002). Late plantings exhibited mean Total FBs values of ≈ 6758 µg kg⁻¹, about sixfold higher than those in early planting (≈ 1058 µg kg⁻¹). This integrated difference paralleled the increase in NFv observed for late planting, reinforcing the general association between fungal colonization intensity and fumonisin biosynthesis reported in previous studies (Munhoz et al., 2015 ; Castañares et al., 2019 ; Krnjaja et al., 2019 , 2022 ; Arias-Martín et al., 2021 ) and in Pérez-Pizá et al. ( 2024 ). However, this relationship was not consistently observed across campaigns. In Campaign 1 (Pérez-Pizá et al., 2024 ), a significant and positive linear association was detected between NFv and Total FBs (p < 0.0001), with similar slopes and intercepts for early and late plantings. In contrast, during Campaign 2 (2021–2022 early; 2022–2023 late), the NFv–FBs relationship was weak and non-significant in both planting dates (Fig. 2 ). In Campaign 3 (2023–2024), the limited number of observations precluded statistical testing. These findings indicate that the strength of the NFv–FBs association varies among years in agreement with previous reports (Table S5; van Rensburg et al., 2017 ; Castañares et al., 2019 ; Krnjaja et al., 2019 ; Silva et al., 2017 ; Ponce-García et al., 2020 ). This aspect is further developed in section 3.4 . [INSERT Fig. 2 HERE] 3.3. Productivity and grain quality patterns across seasons and planting dates Across the three monitored campaigns (2020–2024), grain yield (GY) and its main components showed consistent differences between planting dates (Tables 1 and 3 ). Early planting produced the highest yields, ranging from 7400 to 10500 kg ha⁻¹ (p < 0.0001), with the maximum in Campaign 2. The NGM followed the same trend, whereas TGW remained stable (≈ 330 g). Nutritional traits varied little among seasons, indicating a consistent compositional profile in early plantings. In late planting, mean yields were lower (5500–8200 kg ha⁻¹) but increased slightly across campaigns (p < 0.0001). NGM mirrored this trend, while TGW and nutritional attributes showed only minor year-to-year fluctuations. Table 3 Seasonal variation in yield and nutritional traits of maize under early and late planting dates across three growing campaigns (C1 = 2020–2021, C2 = 2021–2022/2022–2023, C3 = 2023–2024). Variables include grain yield (GY), number of grains per square meter (NGM), thousand-grain weight (TGW), lipid content, protein content, fiber content, and relative energy (RE). Different lowercase letters within each row indicate significant differences among campaigns (one-way ANOVA, Tukey’s test, p < 0.05). Variable C1 C2 C3 p-value Mean ± SE Min–Max Mean ± SE Min–Max Mean ± SE Min–Max Early Yield and yield components GY (kg ha⁻¹) 7344 ± 221 b 5640–8412 6436 ± 352 b 5041–7678 12550 ± 333 a 12073–13528 < 0.0001 NGM (grains m⁻²) 2851 ± 108 c 2199–3285 3595 ± 165 b 2879–4361 4380 ± 285 a 3689–5086 < 0.0001 TGW (g) 323 ± 6 a 296–365 324 ± 11 a 282–383 352 ± 22 a 312–403 0,2564 Nutritional traits Lipids (%) 3,55 ± 0,05 b 3,26 − 3,80 3,90 ± 0,13 a 3,13 − 4,53 4,10 ± 0,05 a 3,98 − 4,21 0,0018 Protein (%) 8,58 ± 0,14 a 7,55 − 9,20 8,62 ± 0,13 a 8,04–9,21 8,50 ± 0,15 a 8,14 − 8,77 0,9037 Fiber (%) 1,90 ± 0,02 c 1,79 − 2,00 2,03 ± 0,06 b 1,77 − 2,27 2,25 ± 0,02 a 2,22 − 2,29 0,0001 RE (kcal kg⁻¹) 4411 ± 3,15 a 4395–4433 4416 ± 3,94 a 4399–4436 4401 ± 3,77 a 4395–4412 0,1083 Late Yield and yield components GY (kg ha⁻¹) 5562 ± 163 b 4609–6684 6093 ± 237 b 5286–6571 9008 ± 502 a 8506–9510 < 0.0001 NGM (grains m⁻²) 2324 ± 120 b 1693–3166 1389 ± 141 c 966–1822 3721 ± 840 a 2881–4561 < 0.0001 TGW (g) 326 ± 9 b 285–393 349 ± 17 a 308–396 405 ± 40 a 365–445 0,0289 Nutritional traits Lipids (%) 3,62 ± 0,05 b 3,32 − 3,89 3,79 ± 0,11 ab 3,47 − 4,13 4,18 ± 0,03 a 4,15 − 4,20 0,0032 Protein (%) 7,96 ± 0,11 b 7,09 − 8,57 8,73 ± 0,33 a 7,71 − 9,64 9,13 ± 0,22 a 8,91 − 9,35 0,0036 Fiber (%) 1,93 ± 0,02 c 1,85 − 2,06 2,04 ± 0,04 b 1,94 − 2,14 2,31 ± 0,03 a 2,28 − 2,33 < 0.0001 RE (kcal kg⁻¹) 4400 ± 3,01 b 4383–4416 4424 ± 5,79 a 4411–4440 4407 ± 3,14 ab 4404–4410 0,003 [INSERT Table 3 HERE] When data were integrated across campaigns (Table 3 ), early planting significantly outperformed late planting in GY (7831 vs 6040 kg ha⁻¹; p = 0.0024) and NGM (3344 vs 2230 grains m⁻²; p < 0.0001), with no differences in TGW. Protein content was slightly higher in early than in late planting (7.55 vs 7.09%), while the remaining nutritional traits showed no differences. 3.4. Integrative interpretation of multi-year patterns within a meteorological framework The integrative heatmap (Fig. 3 ) revealed a stable multi-year structure, in which early plantings consistently clustered with high grain yields, low fungal loads (NTotal and NFv), and minimal fumonisin accumulation, whereas late plantings clustered with reduced yields, higher NFv values, and elevated fumonisin contamination. This tendency was reproduced across campaigns and is consistent with patterns reported in other maize-growing regions (Blandino et al., 2017 ; Krnjaja et al., 2022 ). In contrast, the nutritional composition of grains varied little between planting dates or seasons, indicating that proximate grain traits were substantially less sensitive to planting date effects than sanitary and agronomic outcomes. [INSERT Fig. 3 HERE] The patterns observed for NFv and Total FBs can be interpreted within the distinct meteorological regimes experienced by early and late planting (Table S4; Figs. S1–S3). Two phenological periods are particularly relevant: the flowering window and the ripening stage, each characterized by environmental conditions that modulate fungal establishment and fumonisin accumulation, respectively (Marin et al., 2004; Martínez et al., 2010 ; Cao et al., 2014 ; Moschini et al., 2020 ; Dinolfo et al., 2022; Gbashi et al., 2024 ; de Oliveira Rocha et al., 2024). Epidemiological models such as FUMAgrain (Maiorano et al., 2009 ) also distinguish these two phases, attributing early post-silking conditions primarily to infection risk and later grain-fill conditions to fumonisin synthesis. To assess how the environmental conditions during flowering related to the observed NFv and Total FBs patterns, we examined temperature and precipitation across the ~ 28-day anthesis window (− 7/+21 days; Table S4) and generated three-dimensional response surfaces based on these variables (Fig. S3). The surface showed that NFv increased primarily with temperature, indicating that warmer flowering environments promoted early fungal establishment (Fig. S3a). This response aligns with evidence showing that high temperatures around silking increase silk susceptibility and facilitate F. verticillioides infection and early colonization (Cao et al., 2014 ). Accordingly, the comparatively warmer flowering conditions of late planting likely enhanced the potential for early establishment of F. verticillioides relative to early-sown crops. According to Maiorano et al. ( 2009 ) and de la Campa et al. ( 2005 ), fumonisin contamination can be predicted from weather conditions occurring within specific sub-periods of the flowering stage (particularly the early post-silking window) where high maximum temperatures increase fumonisin levels and rainfall tends to mitigate them. In our study, however, the response surface for Total FBs (Fig. S3b) showed a marked increase in fumonisin accumulation when high temperatures coincided with high precipitation during flowering. This difference likely reflects our analytical approach, which considered the entire 28-day flowering window rather than distinguishing the discrete sub-stages. Regarding ripening, the meteorological divergence between planting dates was pronounced (Figs. S2–S3). Early-sown maize matured during the typically dry late-summer period, which likely limited kernel moisture retention and contributed to the low Total FBs values observed. In contrast, late-sown maize ripened under markedly wetter autumn conditions, with recurrent rainfall and higher ambient humidity, which likely prolonged kernel moisture. In this context, the higher fumonisin concentrations observed in late planting can be interpreted as being consistent with the well-established requirement of warm-to-moderate temperatures combined with elevated kernel moisture during grain maturation (Maiorano et al., 2009 ; Cao et al., 2014 ; van Rensburg et al., 2017 ; Moschini et al., 2020 ; Dinolfo et al., 2022; de Oliveira Rocha et al., 2024). Attempts to correlate fungal presence/colonization metrics (measured as counts of colony-forming units, incidence, severity, or fungal DNA quantification) with final fumonisin concentrations have yielded a notably inconsistent body of evidence. While some studies report positive associations between the presence of F. verticillioides and FBs levels, others find weak or no detectable relationships (Table S5). This inconsistency reflects the fact that fumonisin production is not strictly proportional to fungal proliferation and that the strength and direction of this association depend on multiple factors that are difficult to capture simultaneously in field experiments. These include hybrid-specific traits, environmental conditions during silking, ripening, and the pre-harvest period, the extent of insect damage, the load of primary inoculum from maize residues, tillage practices, and the potential contribution of seedborne or systemic infections (Martínez et al., 2010 ; Cao et al., 2014 ; van Rensburg et al., 2017 ; Moschini et al., 2020 ). Together, these mechanisms help explain the instability of the NFv–FBs relationship observed across years in our dataset and support the view that fungal load alone may not be a reliable predictor of fumonisin contamination. 4. CONCLUSIONS This multi-year analysis revealed clear differences between early and late maize plantings in sanitary status, fumonisin contamination, and grain yield. Across the evaluated campaigns, the direction of planting-date effects on grain sanitary status was maintained, although the magnitude of F. verticillioides colonization and fumonisin contamination varied among years. Overall, early planting were associated with lower F. verticillioides colonization and fumonisin levels and higher yields, whereas late planting generally showed higher fungal presence and mycotoxin contamination. These contrasts were observed despite all hybrids carrying lepidopteran resistance traits, indicating a predominant role of meteorological conditions during flowering and grain filling. The relationship between F. verticillioides abundance in grains and fumonisin contamination was not stable across years, highlighting that toxin accumulation is not strictly determined by infection levels but is strongly modulated by environmental conditions during specific reproductive periods. In contrast, grain nutritional composition remained comparatively stable across planting dates and seasons. Taken together, these results indicate that, while late planting is not intrinsically unfavorable, early planting can be associated with lower sanitary pressure and reduced fumonisin risk under certain climatic scenarios. Declarations Conflict of interest statement The authors report there are no competing interests to declare. Funding This work was supported by Vicerrectorado de Investigación y Desarrollo - Universidad del Salvador under grant PI USAL 80020230100004US, and University of Buenos Aires under grant UBACYT 20020220100114BA. Author's contribution María Cecilia Pérez-Pizá: Conceptualization, Methodology, Investigation, Data curation, Validation, Visualization, Project administration, Funding acquisition, Writing – original draft, Writing – review & editing. Sebastián Vicente: Investigation, Data curation, Validation, Visualization, Writing – original draft, Writing – review & editing. Francisco José Sautua: Investigation, Data curation, Validation, Writing – original draft, Writing – review & editing. Mousegne Fernando: Investigation, Data curation, Formal analysis, Writing – review & editing. Jecke Fernando: Investigation, Data curation, Formal analysis, Writing – review & editing. Vago María Elena: Investigation, Formal analysis, Writing – review & editing. Marcelo Aníbal Carmona: Conceptualization, Investigation, Data curation, Validation, Supervision, Project administration, Funding acquisition, Resources, Writing – review & editing. 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Maddonni, G. A. (2012). Analysis of the climatic constraints to maize production in the current agricultural region of Argentina: A probabilistic approach. Theoretical and Applied Climatology , 107 (3–4), 325–345. Maddonni, G. A., Cárcova, J., Otegui, M. E., & Slafer, G. A. (2024). Recent research on maize grain yield in Argentina. In Physiological Bases for Maize Improvement (pp. 191–204). Maiorano, A., Reyneri, A., Sacco, D., Magni, A., & Ramponi, C. (2009). A dynamic risk assessment model (FUMAgrain) of fumonisin synthesis by Fusarium verticillioides in maize grain in Italy. Crop Protection , 28 (3), 243–256. Marín, S., Magan, N., Ramos, A. J., & Sanchis, V. (2004). Fumonisin-producing strains of Fusarium: a review of their ecophysiology. Journal of food protection , 67 (8), 1792–1805. Martínez, M. I., Moschini, R. C., Barreto, D., Bodega, J., Comerio, R., Forján, H., Piatti, F., Presello, D., & Valentinuz, O. (2010). Environmental factors that affect the fumonisin content in maize grain. Tropical Plant Pathology , 35 (5), 277–284. Martínez, M. I., & Moschini, R. C. (2010). Riesgo climático de la región pampeana argentina con respecto a la contaminación con fumonisina en grano de maíz . Sitio Argentino de Producción Animal, Instituto Nacional de Tecnología Agropecuaria (INTA). Moschini, R. C., Borsarelli, M., Martinez, M. I., Presello, D. A., Ferraguti, F., Cristos, D., & Rojas, D. (2020). Analysis of preharvest meteorological conditions in relation to concentration of fumonisins in kernels of two genetically different maize hybrids. Australasian Plant Pathology , 49 (6), 665–677. Munhoz, A. T., Carvalho, R. V. D., Querales, P. J., Gonçalves, F. P., & Camargo, L. E. A. (2015). Relationship between resistance of tropical maize inbred lines for resistance to ear rot and fumonisin accumulation caused by Fusarium verticillioides . Summa Phytopathologica , 41 , 144–148. Olocco-Diz, M. J., Iglesias, B. F., & Schang, M. J. (2017). Estimación del contenido energético de maíces argentinos a partir de la espectrofotometría del infrarrojo cercano (NIRS). Technical Report. Cámara Argentina de Empresas de Nutrición Animal. Papucci, S., González, A., & Cruciani, M. (2016). Maíces tempranos versus tardíos. Agromensajes , 46 , 39–45. Pérez-Pizá, M. C., Vicente, S., Castellari, C. C., Mousegne, F., Jecke, F., Cornejo, P., & Pacin, A. (2024). Timing is everything: How planting period shapes nutritional quality, mycobiota characteristics, and mycotoxin contamination in maize ( Zea mays ) grains. European Journal of Plant Pathology , 169 (1), 201–217. Ponce-García, N., Ortíz-Islas, S., García-Lara, S., & Serna-Saldivar, S. O. (2020). Physical and chemical parameters, Fusarium verticillioides growth and fumonisin production in kernels of nine maize genotypes. Journal of Cereal Science , 96 , 103128. Qi, Z., Tian, L., Zhang, H., Lei, Y., & Tang, F. (2023). Fungal community analysis of hot spots in bulk maize under different storage conditions. LWT – Food Science and Technology , 182 (1), 114819. Sautua, F., Scandiani, M., Gordó, M., Carmona, M., Formento, N., Tartabini, M., & Luque, A. (2018). Seed-borne fungal pathogens infecting maize seeds in Argentina from 2009 to 2017. 8th ISTA Seed Health Symposium, Buenos Aires, Argentina. Silva, J. J., Viaro, H. P., Ferranti, L. S., Oliveira, A. L. M., Ferreira, J. M., Ruas, C. F., Ono, E. Y. S., & Fungaro, M. H. P. (2017). Genetic structure of Fusarium verticillioides populations and occurrence of fumonisins in maize grown in Southern Brazil. Crop Protection , 99 , 160–167. Singh, H., Kaur, H., Hunjan, M. S., & Sharma, S. (2025). Unveiling toxigenic Fusarium species causing maize ear rot: Insights into fumonisin production potential. Frontiers in Plant Science , 16 , 1516644. van Rensburg, B. J., McLaren, N. W., & Flett, B. C. (2017). Grain colonization by fumonisin-producing Fusarium spp. and fumonisin synthesis in South African commercial maize in relation to prevailing weather conditions. Crop Protection , 102 , 129–136. Supplementary Files Graphicalabstract.jpg SupplementaryMaterial.docx Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8612955","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588099490,"identity":"ac4d7a2b-64b8-48e2-92fc-152d57eaddfa","order_by":0,"name":"María Cecilia Pérez-Pizá","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYPACGwjF2EC8ljTStRwmQYvu7OZjHz78OS8vH334ADPvDjsG/tkH8Gsxu3MseeYMntuGG8+lJTDznklmkDiXQEDLjRxjZh6J24wbe3gMmHnbmBkYzhBwmNmN/M/MfwzO2UO11DPIE9aSw8zMkHAgcT4PWMthBgOCWu4cM2bsOZCcvIGHLeHg3DPHeQwJarnd/Jjhxx872/k9zAcfvN1RLSdHSAuDBJQ2OMDAAEQMPIQ0ILTINxBWOwpGwSgYBSMUAABEkEER+VJKtAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-6795-2968","institution":"Universidad de Buenos Aires Facultad de Agronomia","correspondingAuthor":true,"prefix":"","firstName":"María","middleName":"Cecilia","lastName":"Pérez-Pizá","suffix":""},{"id":588099491,"identity":"e1ecd213-fb31-4ac8-8f82-8485f63c5eb5","order_by":1,"name":"Sebastián Vicente","email":"","orcid":"","institution":"CIC: Comision de Investigaciones Cientificas de la Provincia de Buenos Aires","correspondingAuthor":false,"prefix":"","firstName":"Sebastián","middleName":"","lastName":"Vicente","suffix":""},{"id":588099492,"identity":"c625e9ee-92b5-4fdb-85d3-326b87aa1d2c","order_by":2,"name":"Francisco José Sautua","email":"","orcid":"","institution":"Universidad de Buenos Aires Facultad de Agronomia","correspondingAuthor":false,"prefix":"","firstName":"Francisco","middleName":"José","lastName":"Sautua","suffix":""},{"id":588099493,"identity":"a2ee7faa-2e24-48d8-80bd-de8189ef58b0","order_by":3,"name":"Fernando Mousegne","email":"","orcid":"","institution":"USAL: Universidad del Salvador","correspondingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"","lastName":"Mousegne","suffix":""},{"id":588099494,"identity":"3f14cf0e-8047-4663-a709-a247fc8ca668","order_by":4,"name":"Fernando Jecke","email":"","orcid":"","institution":"INTA: Instituto Nacional de Tecnologia Agropecuaria","correspondingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"","lastName":"Jecke","suffix":""},{"id":588099495,"identity":"d89eea33-cfd1-4db5-a685-a6eedfbb6631","order_by":5,"name":"María Elena Vago","email":"","orcid":"","institution":"Pontificia Universidad Católica Argentina: Pontificia Universidad Catolica Argentina","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"Elena","lastName":"Vago","suffix":""},{"id":588099496,"identity":"25c36e9b-5d12-4d45-b3db-378befadcad7","order_by":6,"name":"Marcelo Anibal Carmona","email":"","orcid":"","institution":"Universidad de Buenos Aires Facultad de Agronomia","correspondingAuthor":false,"prefix":"","firstName":"Marcelo","middleName":"Anibal","lastName":"Carmona","suffix":""},{"id":588099497,"identity":"cd6bf78d-3eb1-4e22-8a40-088794c44184","order_by":7,"name":"Sebastián Alberto Stenglein","email":"","orcid":"","institution":"CONICET Mar del Plata","correspondingAuthor":false,"prefix":"","firstName":"Sebastián","middleName":"Alberto","lastName":"Stenglein","suffix":""}],"badges":[],"createdAt":"2026-01-15 18:18:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8612955/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8612955/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102415689,"identity":"11688dce-a47c-4b8c-8995-98d9b9e0a331","added_by":"auto","created_at":"2026-02-11 12:47:16","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1369587,"visible":true,"origin":"","legend":"\u003cp\u003eA) Total fungal population counts associated with maize grains (NTotal, CFU g⁻¹) across three growing campaigns (1 = 2020–2021, 2 = 2021–2022 / 2022–2023, and 3 = 2023–2024) under early and late planting dates. B) \u003cem\u003eFusarium verticillioides\u003c/em\u003e population counts (NFv, CFU g⁻¹) quantified in the same grain samples, representing the main toxigenic component of the grain-associated mycobiota. C) Total fumonisins (FBs, µg kg⁻¹) detected in the corresponding samples across campaigns and planting periods. Boxplots show the distribution of hybrid values within each group; the horizontal line indicates the median, boxes represent the interquartile range, whiskers the minimum and maximum values, and the “+” symbol denotes the mean. Different lowercase letters indicate significant differences among seasons within early plantings, whereas uppercase letters indicate differences within late plantings (one-way ANOVA, Tukey’s test, p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8612955/v1/8da8223519f91d72b848b672.jpg"},{"id":102415685,"identity":"526093a2-889d-444d-b98b-44fa94622aea","added_by":"auto","created_at":"2026-02-11 12:47:16","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1256519,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between \u003cem\u003eFusarium verticillioides\u003c/em\u003ecolony-forming units (NFv, CFU g⁻¹) and total fumonisins (FBs, µg kg⁻¹) in maize grains from Campaign 2. A) Early planting (2021–2022). B) Late planting (2022–2023). Each point represents an individual hybrid.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8612955/v1/0ead88c5578d33c6cf173a02.jpg"},{"id":102415690,"identity":"ee77b444-b0da-4246-bab5-9d9d0a201199","added_by":"auto","created_at":"2026-02-11 12:47:16","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":51191,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap summarizing the relative values of maize yield, yield components (grains m⁻² and thousand-grain weight), sanitary variables (NTotal, NFv, total fumonisins), and nutritional traits (protein, lipid, fiber, and relative energy) across three growing campaigns (1 = 2020–2021, 2 = 2021–2022/2022–2023, 3 = 2023–2024) under early and late planting dates. A single color scale was applied across all variables (dark green = higher values, yellow = intermediate, red = lower).\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8612955/v1/129e23ea4c8b74966aefb124.jpg"},{"id":109318549,"identity":"9ec12ec7-ce16-4a84-91a1-0f7be9466a01","added_by":"auto","created_at":"2026-05-15 12:55:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3147095,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8612955/v1/c0209565-3bd2-48dd-9302-0449071c68aa.pdf"},{"id":102415686,"identity":"c8b27298-6005-4f58-901d-34ff1cea5086","added_by":"auto","created_at":"2026-02-11 12:47:16","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":5317158,"visible":true,"origin":"","legend":"","description":"","filename":"Graphicalabstract.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8612955/v1/63b412c434aebd231e14e530.jpg"},{"id":102415687,"identity":"34f4bef4-446c-49b9-bd4c-d56945c0ed99","added_by":"auto","created_at":"2026-02-11 12:47:16","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":756194,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8612955/v1/ffd2896f91066685394065d6.docx"}],"financialInterests":"","formattedTitle":"Interannual variability of planting-date effects on Fusarium verticillioides grain colonization and fumonisin contamination in maize","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eMaize (\u003cem\u003eZea mays\u003c/em\u003e L.) ranks among the most important cereal crops worldwide, not only for its significant contribution to global food and feed supplies, but also as a raw material for various industrial applications (Bond, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In Argentina, its cultivation spans diverse agroecological regions and plays a strategic role within extensive cropping systems (Maddonni et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, maize productivity and safety are frequently compromised by fungal diseases that colonize ears and grains, resulting in reduced yield and altered nutritional and sanitary quality (Sautua et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Chiotta et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Within this context, \u003cem\u003eFusarium\u003c/em\u003e species, particularly \u003cem\u003eF. verticillioides\u003c/em\u003e, \u003cem\u003eF. proliferatum\u003c/em\u003e, and \u003cem\u003eF. graminearum\u003c/em\u003e, constitute the predominant pathogens of concern due to their capacity to infect developing kernels and synthesize mycotoxins such as fumonisins (FBs), deoxynivalenol (DON), and zearalenone (ZEA), which pose serious health risks to humans and animals (Krnjaja et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Logrieco et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The extent of fungal colonization and mycotoxin contamination depends on complex interactions among host genotype, agronomic management, and environmental conditions throughout the growing cycle (Cao et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Qi et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Bugingo et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the past decade, Argentine maize production systems have progressively shifted from early-spring to late-summer planting (Papucci et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This transition has been largely driven by the need to minimize the coincidence between flowering and water stress episodes, thereby stabilizing yields under increasingly variable rainfall patterns (Maddonni, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Esp\u0026oacute;sito and Ferraguti, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Nonetheless, late planting can markedly modify the environmental conditions experienced by maize around silking and physiological maturity (Esp\u0026oacute;sito and Ferraguti, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Krnjaja et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), often shifting these critical stages toward conditions that favor \u003cem\u003eF. verticillioides\u003c/em\u003e establishment, delay kernel drying, and increase the risk of fumonisin accumulation (Mart\u0026iacute;nez and Moschini, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Blandino et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Moschini et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Logrieco et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, several studies have linked late planting to increased ear rot severity, higher incidence of \u003cem\u003eFusarium\u003c/em\u003e spp., and greater fumonisin accumulation (Casta\u0026ntilde;ares et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a previous study, P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) demonstrated that the maize planting period exerts a strong influence on grain sanitary and nutritional attributes. Under Argentine field conditions, early planting resulted in higher yield and improved grain quality, whereas late planting promoted greater \u003cem\u003eF. verticillioides\u003c/em\u003e colonization and FBs accumulation. Moreover, a positive linear association was observed between fungal incidence and toxin levels, providing a quantitative basis for linking field infection to mycotoxin contamination. However, these findings were derived from a single growing season, and the degree to which such relationships persist under different climatic scenarios remains unclear. Given that \u003cem\u003eFusarium\u003c/em\u003e infection and FBs biosynthesis are highly responsive to temperature, humidity, and rainfall distribution, multi-year studies are essential to evaluate the temporal consistency of these patterns and the magnitude of interannual variability.\u003c/p\u003e \u003cp\u003eThe present study addresses this knowledge gap by assessing the interannual variability of \u003cem\u003eFusarium\u003c/em\u003e mycobiota and FBs contamination in maize grains under contrasting planting dates across multiple growing seasons in Argentina. By integrating agronomic, nutritional, and sanitary parameters from three independent campaigns (2020\u0026ndash;2024), this work extends previous evidence into a broader temporal framework. We hypothesized that planting date would consistently influence \u003cem\u003eF. verticillioides\u003c/em\u003e grain colonization and FBs contamination, although the magnitude of these effects and the relationships between fungal abundance and mycotoxin accumulation would vary among growing seasons depending on environmental conditions. Understanding such variability is critical for developing predictive tools and refining management strategies aimed at reducing mycotoxin risk in maize production systems.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Field experiments, determination of yield and sampling\u003c/h2\u003e \u003cp\u003eField experiments were conducted over three independent maize growing seasons between 2020 and 2024 at the Experimental Field \u0026lsquo;La Fe\u0026rsquo;, AER INTA San Antonio de Areco, Buenos Aires, Argentina (-34.280625 S, -59.468321 W). Each growing season comprised one or two planting dates, depending on environmental conditions. Early planting (mid-September to early October) was performed in the 2020\u0026ndash;21, 2021\u0026ndash;22, and 2023\u0026ndash;24 seasons, whereas late planting (mid-December to early January) was possible only in the 2020\u0026ndash;21, 2022\u0026ndash;23, and 2023\u0026ndash;24 seasons. The study evaluated multiple commercial maize hybrids in hybrid-comparison trials. All hybrids carried resistance to major ear- and stalk-feeding lepidopteran pests. Each hybrid was treated as an independent data point for subsequent analyses. All field trials corresponded to official INTA hybrid-comparison experiments established in long, machine-harvestable plots (200-m length), managed according to standard field practices and conducted under no-till conditions. Previous crops consisted exclusively of non-maize species typical of regional rotations (e.i., vetch, oat, wheat/second soybean, and first soybean) depending on season and planting date (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). No trial had maize as preceding crop, thus minimizing local inoculum carryover of \u003cem\u003eF. verticillioides\u003c/em\u003e from maize stubble. Soil chemical properties at sowing (pH, organic matter, P Bray, nitrate-N) were provided in the original INTA reports corresponding to each season and summarized in Table S2. The presence of each hybrid across seasons and planting dates is detailed in Table S3. Sowing, flowering, and harvest dates for each season and planting type are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eHarvest was performed approximately 15 days after physiological maturity (R6), when grain moisture had decreased to \u0026asymp;\u0026thinsp;14%. All plots were harvested with a combine harvester equipped with a yield monitor, and yield measurements were validated using a calibrated weigh wagon (\u0026ldquo;tolva balanza\u0026rdquo;); therefore, grain yield (GY) represents the production of the full net plot area. Yield components (number of grains per square meter, NGM; and 1000-grain weight, TGW) were also determined at harvest, following the procedures described by P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Grain samples for laboratory analyses were collected simultaneously, with approximately 1 kg of grain per plot placed in labeled craft paper bags and stored at 4\u0026deg;C until processing for grain mycobiota characterization and mycotoxin analysis.\u003c/p\u003e\u003cp\u003eData from the first campaign (2020\u0026ndash;2021), previously published by P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), were re-incorporated to provide a multi-year framework for comparison with subsequent campaigns (2021\u0026ndash;2022 and 2023\u0026ndash;2024 for early planting; 2022\u0026ndash;2023 for late planting).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Quantification, isolation, and identification of grain-associated mycobiota\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eQuantification and identification of grain-associated fungi followed the general procedures described by P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Briefly, the mycological quality of grains was assessed by quantifying colony-forming units (CFU) of filamentous fungi and yeasts, following Gimeno and Martins (2011) and Castellari et al. (2015). Decimal dilutions of grain suspensions were plated on chloramphenicol-supplemented glucose yeast extract agar (YGCA) and incubated at 25\u0026deg;C for seven days. The total number of viable fungi (NTotal, CFU g⁻\u0026sup1;) was calculated according to ANMAT (2014) guidelines. Fungal colonies were identified morphologically and confirmed by microscopic examination of conidial features. Colonization of maize grains by \u003cem\u003eF. verticillioides\u003c/em\u003e was operationally assessed as the viable fungal population recovered from harvested grains (NFv), expressed as colony-forming units per gram (CFU g⁻\u0026sup1;) and determined using the same criteria applied for NTotal, considering only colonies of that species. The identity of \u003cem\u003eF. verticillioides\u003c/em\u003e isolates was further verified by PCR amplification of the VERT locus (primers VERT-1 and VERT-2) and the TEF1 locus (primers EF-728 M and EF-2), as detailed by P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Fumonisins quantification\u003c/h2\u003e \u003cp\u003eFor fumonisin determinations (Total FBs, \u0026micro;g kg-1), extraction, cleanup, and chromatographic procedures followed the validated methods described in AOAC Official Method 995.15 (AOAC International, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Briefly, 500 g of maize was ground, and a 50 g analytical sample was extracted with a methanol:water (3:1, v/v) solution, filtered, adjusted to pH 6, centrifuged, and purified using strong anion exchange columns for solid-phase extraction (SPE) cleanup. The eluates were evaporated to dryness and analyzed by HPLC with fluorescence detection after o-phthalaldehyde (OPA) derivatization. Calibration procedures, detection parameters, and LOD/LOQ values were as reported by P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Grain quality and nutritional composition\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eGrain crude protein (Protein, %), lipid (Lipid, %), and fiber (Fiber, %) contents were determined by near-infrared spectroscopy (NIRS). All analyses were performed on homogenized subsamples of the same grain lots used for fungal and fumonisin assessments, following the analytical procedures detailed in P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Gross energy (GE, kcal kg⁻\u0026sup1;) was estimated from crude nutrient composition using a prediction equation (Olocco-Diz et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data analysis\u003c/h2\u003e \u003cp\u003eData were tested for normality and homoscedasticity before analysis. Global comparisons between planting dates (early vs. late) were conducted using t-tests, whereas seasonal differences within each planting date were evaluated by one-way ANOVA followed by Tukey\u0026rsquo;s test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Linear regressions were performed to assess the relationship between \u003cem\u003eF. verticillioides\u003c/em\u003e population counts (NFv) and total fumonisin concentrations (FBs) within each campaign. All statistical analyses were carried out using InfoStat v.2024 (Di Rienzo et al., Universidad Nacional de C\u0026oacute;rdoba, Argentina), and all figures were generated using GraphPad Prism v.5.0 (GraphPad Software, San Diego, CA, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS AND DISCUSSION","content":"\u003cp\u003eData from three independent growing seasons (2020\u0026ndash;2024) were jointly analyzed to assess the interannual variability of planting-date effects on sanitary traits (NTotal, NFv), mycotoxin contamination (Total FBs), grain nutritional composition (protein, lipid, fiber, and gross energy), and productive performance (GY, NGM, and TGW). The 2020\u0026ndash;2021 dataset, previously reported by P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), was re-incorporated to provide a broader multi-year framework for comparison.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Mycobiota associated with maize grains\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1. Total fungal population counts (NTotal) and mycological quality\u003c/h2\u003e \u003cp\u003eAcross the three monitored seasons (2020\u0026ndash;2024), total fungal populations associated with maize grains (NTotal) exhibited marked interannual and planting-date variability (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). In early planting, mean NTotal values increased significantly among seasons (p\u0026thinsp;=\u0026thinsp;0.0002), from approximately 2 \u0026times; 10⁴ CFU g⁻\u0026sup1; in 2020\u0026ndash;2021 to 4.8 \u0026times; 10⁴ CFU g⁻\u0026sup1; in 2021\u0026ndash;2022, and then slightly decreased to 3.6 \u0026times; 10⁴ CFU g⁻\u0026sup1; in 2023\u0026ndash;2024. According to Tukey\u0026rsquo;s test, the first season differed from the subsequent two (C 20/21\u0026thinsp;\u0026lt;\u0026thinsp;C 21/22, C 23/24), which did not differ from each other.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[INSERT Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e HERE]\u003c/p\u003e \u003cp\u003eIn late planting, interannual differences were also significant (p\u0026thinsp;=\u0026thinsp;0.0045). Mean NTotal increased from approximately 9.6 \u0026times; 10⁴ CFU g⁻\u0026sup1; in 2020\u0026ndash;2021 to 1.5 \u0026times; 10⁵ CFU g⁻\u0026sup1; in 2022\u0026ndash;2023, before decreasing to 8.6 \u0026times; 10⁴ CFU g⁻\u0026sup1; in 2023\u0026ndash;2024. The 2022\u0026ndash;2023 season showed significantly higher values than the other two (C 22/23\u0026thinsp;\u0026gt;\u0026thinsp;C 20/21, C 23/24).\u003c/p\u003e \u003cp\u003eWhen results were integrated across campaigns (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), late plantings exhibited a highly significant overall increase in total mycobiota (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with mean NTotal values (1.1 \u0026times; 10⁵ CFU g⁻\u0026sup1;) more than threefold higher than those of early plantings (3.3 \u0026times; 10⁴ CFU g⁻\u0026sup1;). According to the classification proposed by Gimeno and Martins (2011), early-planting samples mostly fell within the good (\u0026le;\u0026thinsp;4 \u0026times; 10⁴ CFU g⁻\u0026sup1;) or regular (4 \u0026times; 10⁴ \u0026ndash; 1 \u0026times; 10⁵ CFU g⁻\u0026sup1;) mycological quality categories, whereas late plantings were predominantly regular or poor (\u0026gt;\u0026thinsp;1 \u0026times; 10⁵ CFU g⁻\u0026sup1;).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of sanitary, yield, and nutritional traits of maize grains collected under early and late planting dates across three growing seasons (2020\u0026ndash;2024). Variables include total fungal population counts (NTotal), \u003cem\u003eFusarium verticillioides\u003c/em\u003e population counts (NFv, CFU g⁻\u0026sup1;), total fumonisins (Total FBs, \u0026micro;g kg⁻\u0026sup1;), grain yield (GY, kg ha⁻\u0026sup1;), number of grains per square meter (NGM, grains m⁻\u0026sup2;), thousand-grain weight (TGW, g), lipid content (Lipids, %), protein content (Protein, %), fiber content (Fiber, %), and relative energy (RE, kcal kg⁻\u0026sup1;). Different lowercase letters within each variable indicate significant differences between planting dates (Tukey\u0026rsquo;s test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), based on the comparison of all early-planting data pooled across campaigns versus all late-planting data pooled across campaigns.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEarly (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRange (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLate\u003c/p\u003e \u003cp\u003e(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRange (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSanitary traits\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNtotal (CFU g⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32420\u0026thinsp;\u0026plusmn;\u0026thinsp;3559 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9091\u0026ndash;78180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109400\u0026thinsp;\u0026plusmn;\u0026thinsp;8839 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37950\u0026ndash;194200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNFv (CFU g⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11700\u0026thinsp;\u0026plusmn;\u0026thinsp;2520 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e454\u0026ndash;41820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55570\u0026thinsp;\u0026plusmn;\u0026thinsp;4831 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8636\u0026ndash;99390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal FBs (\u0026micro;g kg⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1058\u0026thinsp;\u0026plusmn;\u0026thinsp;202 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62\u0026ndash;5007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6758\u0026thinsp;\u0026plusmn;\u0026thinsp;1598 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e650\u0026ndash;31430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYield and yield components\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGY (kg ha⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7831\u0026thinsp;\u0026plusmn;\u0026thinsp;443 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5041\u0026ndash;13530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6040\u0026thinsp;\u0026plusmn;\u0026thinsp;263 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4609\u0026ndash;9510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGM (grains m⁻\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3344\u0026thinsp;\u0026plusmn;\u0026thinsp;140 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2199\u0026ndash;5086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2230\u0026thinsp;\u0026plusmn;\u0026thinsp;179 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e966\u0026ndash;4561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTGW (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e328.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282\u0026ndash;403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e339.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e285\u0026ndash;445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2812\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNutritional traits\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipids (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.13\u0026ndash;4.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.32\u0026ndash;4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6736\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.58\u0026ndash;9.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.27\u0026ndash;9.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0529\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.77\u0026ndash;2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.85\u0026ndash;2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9170\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRE (kcal kg⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4411\u0026thinsp;\u0026plusmn;\u0026thinsp;2.30 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4395\u0026ndash;4436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4406\u0026thinsp;\u0026plusmn;\u0026thinsp;3.30 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4383\u0026ndash;4440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2459\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[INSERT Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e HERE]\u003c/p\u003e \u003cp\u003eSince mycological quality derived from NTotal values does not necessarily reflect the sanitary safety of grains, the following section focuses on \u003cem\u003eF. verticillioides\u003c/em\u003e as the principal toxigenic component of the grain-associated mycobiota.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2. Fusarium verticillioides population counts (NFv)\u003c/h2\u003e \u003cp\u003eAcross the three monitored seasons (2020\u0026ndash;2024), NFv exhibited clear differences between planting dates and relatively stable interannual behavior within each (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In early plantings, interannual differences were significant (p\u0026thinsp;=\u0026thinsp;0,0002), with the first campaign showing significantly lower values than the subsequent two. The mean NFv values ranged from 5.3 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e CFU g⁻\u0026sup1; (min 4.5 \u0026times; 10\u003csup\u003e2\u003c/sup\u003e; max 1.8 \u0026times; 10⁴) in 2020\u0026ndash;2021 to 2.3 \u0026times; 10⁴ CFU g⁻\u0026sup1; (min 9.1 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e; max 4.2 \u0026times; 10⁴) in 2021\u0026ndash;2022 and 2.5 \u0026times; 10⁴ CFU g⁻\u0026sup1; in 2023\u0026ndash;2024 (min 4.3 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e; max 3.7 \u0026times; 10⁴). These results indicate that early planting effectively restricted \u003cem\u003eF. verticillioides\u003c/em\u003e proliferation, maintaining low fungal colonization levels. In late plantings, by contrast, NFv counts were consistently higher but statistically homogeneous among years (p\u0026thinsp;=\u0026thinsp;0,4108). Mean values ranged from approximately 4.5 \u0026times; 10⁴ to 6.5 \u0026times; 10⁴ CFU g⁻\u0026sup1; (min 8.6 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e; max 9.9 \u0026times; 10⁴), confirming that late planting systematically favored \u003cem\u003eF. verticillioides\u003c/em\u003e colonization.\u003c/p\u003e \u003cp\u003eWhen data were integrated across seasons (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), the overall effect of planting date was highly significant (t-test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Late plantings exhibited mean NFv values of approximately 5.6 \u0026times; 10⁴ CFU g⁻\u0026sup1;, nearly fivefold greater than those recorded in early planting (1.2 \u0026times; 10⁴ CFU g⁻\u0026sup1;). This pattern mirrors that observed for NTotal, reinforcing that delayed planting markedly enhanced fungal presence.\u003c/p\u003e \u003cp\u003eImportantly, all evaluated hybrids carried Bt or equivalent resistance traits, a prerequisite for late planting in Argentina due to intense lepidopteran pressure (Aapresid, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Bonivardo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Because insect injury is a well-known predisposing factor for ear infection by \u003cem\u003eF. verticillioides\u003c/em\u003e (Barroso et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea,b), the high NFv levels recorded in late compared with early plantings despite the use of insect-resistant hybrids strongly indicate that the differences observed here were driven by environmental conditions rather than by insect damage.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Fumonisin contamination\u003c/h2\u003e \u003cp\u003eTotal fumonisins (Total FBs\u0026thinsp;=\u0026thinsp;FB₁ + FB₂) exhibited pronounced variability among planting dates and seasons (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC; Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal fumonisin (FBs, \u0026micro;g kg⁻\u0026sup1;) concentrations measured in maize hybrids across three campaigns under early and late planting dates. Exceedances of internationally and nationally established regulatory thresholds are indicated with \u0026ldquo;x\u0026rdquo;. Data from 2020\u0026ndash;2021 were already published in P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and are included here as a reference.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHybrid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal FBs (\u0026micro;g kg⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1000*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2000**\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4000***\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal FBs (\u0026micro;g kg⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1000*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2000**\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4000***\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEarly 2020\u0026ndash;2021\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eLate 2020\u0026ndash;2021\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1361,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6317,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6997,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1457,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2231,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e685,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2691,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2069,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5696,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2418,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5007,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e650,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e867,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2639,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e522,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1043,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1704,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3696,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1889,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7184,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108,70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2358,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161,90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9396,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHybrid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEarly 2021\u0026ndash;2022\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eLate 2022\u0026ndash;2023\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1254,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5246,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e633,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e904,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17630,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1646,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8404,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1412,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4826,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1035,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1927,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1068,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1927,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHybrid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEarly 2023\u0026ndash;2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eLate 2023\u0026ndash;2024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e352,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31428,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e835,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e248,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12375,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e*1000 \u0026micro;g kg⁻\u0026sup1;: European Commission Regulation (EC) No. 1126/2007, maximum level for maize intended for direct human consumption.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e** \u0026gt; 2000 \u0026micro;g kg⁻\u0026sup1;: Argentine Food Code (CONAL/Codex Alimentarius Commission, 2019), maximum level for maize by-products.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e*** \u0026gt; 4000 \u0026micro;g kg⁻\u0026sup1;: European Commission Regulation (EC) No. 1126/2007, maximum level for unprocessed maize.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn early plantings, mean Total FBs values remained low and stable across the three campaigns (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3535), ranging from 374 to 1234 \u0026micro;g kg⁻\u0026sup1; (min 62; max 5007; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). When all early-planting data were considered together, most hybrids (12 out of 14) maintained fumonisin concentrations below 2000 \u0026micro;g kg⁻\u0026sup1; and thus remained under both international and national regulatory thresholds (1000 \u0026micro;g kg⁻\u0026sup1; for maize intended for human consumption and 4000 \u0026micro;g kg⁻\u0026sup1; for unprocessed maize; European Commission Regulation 1126/2007; CONAL/Codex Alimentarius Commission, 2019). Exceedances were sporadic and restricted to two hybrids (E and G) in 2020\u0026ndash;2021 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), confirming the overall stability of early planting in limiting fumonisin biosynthesis.\u003c/p\u003e \u003cp\u003e[INSERT Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e HERE]\u003c/p\u003e \u003cp\u003eIn contrast, late planting showed recurrent and significant increases in fumonisin contamination across years (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0008; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Mean Total FBs values rose from 4101 \u0026micro;g kg⁻\u0026sup1; in 2020\u0026ndash;2021 to 7607 \u0026micro;g kg⁻\u0026sup1; in 2022\u0026ndash;2023 and then escalated dramatically to \u0026gt;\u0026thinsp;21900 \u0026micro;g kg⁻\u0026sup1; in 2023\u0026ndash;2024. This sharp rise during the last campaign suggests that the environmental conditions prevailing during grain filling in 2023\u0026ndash;2024 were particularly conducive to mycotoxin accumulation. Most late-planting hybrids (15 out of 18) exceeded 1000 \u0026micro;g kg⁻\u0026sup1;, two-thirds (12 out of 18) surpassed 2000 \u0026micro;g kg⁻\u0026sup1;, and 8 out of 18 reached or exceeded 4000 \u0026micro;g kg⁻\u0026sup1; (the limit for unprocessed maize) while 4 out of 18 even exceeded 10000 \u0026micro;g kg⁻\u0026sup1; (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although some hybrids (G, I, and K) displayed low fumonisin levels in one season, these same genotypes showed high concentrations in another (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall, no hybrid exhibited a consistently low-fumonisin profile under late-planting conditions.\u003c/p\u003e \u003cp\u003eWhen data were pooled across campaigns (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), the overall effect of planting date on fumonisin concentration was highly significant (\u003cem\u003et\u003c/em\u003e-test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0002). Late plantings exhibited mean Total FBs values of \u0026asymp;\u0026thinsp;6758 \u0026micro;g kg⁻\u0026sup1;, about sixfold higher than those in early planting (\u0026asymp;\u0026thinsp;1058 \u0026micro;g kg⁻\u0026sup1;). This integrated difference paralleled the increase in NFv observed for late planting, reinforcing the general association between fungal colonization intensity and fumonisin biosynthesis reported in previous studies (Munhoz et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Casta\u0026ntilde;ares et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Krnjaja et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Arias-Mart\u0026iacute;n et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and in P\u0026eacute;rez-Piz\u0026aacute; et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, this relationship was not consistently observed across campaigns. In Campaign 1 (P\u0026eacute;rez-Piz\u0026aacute; et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), a significant and positive linear association was detected between NFv and Total FBs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with similar slopes and intercepts for early and late plantings. In contrast, during Campaign 2 (2021\u0026ndash;2022 early; 2022\u0026ndash;2023 late), the NFv\u0026ndash;FBs relationship was weak and non-significant in both planting dates (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In Campaign 3 (2023\u0026ndash;2024), the limited number of observations precluded statistical testing. These findings indicate that the strength of the NFv\u0026ndash;FBs association varies among years in agreement with previous reports (Table S5; van Rensburg et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Casta\u0026ntilde;ares et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Krnjaja et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Silva et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ponce-Garc\u0026iacute;a et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This aspect is further developed in section \u003cspan refid=\"Sec14\" class=\"InternalRef\"\u003e3.4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[INSERT Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e HERE]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Productivity and grain quality patterns across seasons and planting dates\u003c/h2\u003e \u003cp\u003eAcross the three monitored campaigns (2020\u0026ndash;2024), grain yield (GY) and its main components showed consistent differences between planting dates (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Early planting produced the highest yields, ranging from 7400 to 10500 kg ha⁻\u0026sup1; (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with the maximum in Campaign 2. The NGM followed the same trend, whereas TGW remained stable (\u0026asymp;\u0026thinsp;330 g). Nutritional traits varied little among seasons, indicating a consistent compositional profile in early plantings. In late planting, mean yields were lower (5500\u0026ndash;8200 kg ha⁻\u0026sup1;) but increased slightly across campaigns (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). NGM mirrored this trend, while TGW and nutritional attributes showed only minor year-to-year fluctuations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSeasonal variation in yield and nutritional traits of maize under early and late planting dates across three growing campaigns (C1\u0026thinsp;=\u0026thinsp;2020\u0026ndash;2021, C2\u0026thinsp;=\u0026thinsp;2021\u0026ndash;2022/2022\u0026ndash;2023, C3\u0026thinsp;=\u0026thinsp;2023\u0026ndash;2024). Variables include grain yield (GY), number of grains per square meter (NGM), thousand-grain weight (TGW), lipid content, protein content, fiber content, and relative energy (RE). Different lowercase letters within each row indicate significant differences among campaigns (one-way ANOVA, Tukey\u0026rsquo;s test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eC2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eC3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin\u0026ndash;Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u0026ndash;Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMin\u0026ndash;Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEarly\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYield and yield components\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGY (kg ha⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7344\u0026thinsp;\u0026plusmn;\u0026thinsp;221 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5640\u0026ndash;8412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6436\u0026thinsp;\u0026plusmn;\u0026thinsp;352 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5041\u0026ndash;7678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e12550\u0026thinsp;\u0026plusmn;\u0026thinsp;333 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12073\u0026ndash;13528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGM (grains m⁻\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2851\u0026thinsp;\u0026plusmn;\u0026thinsp;108 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2199\u0026ndash;3285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3595\u0026thinsp;\u0026plusmn;\u0026thinsp;165 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2879\u0026ndash;4361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4380\u0026thinsp;\u0026plusmn;\u0026thinsp;285 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3689\u0026ndash;5086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTGW (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e323\u0026thinsp;\u0026plusmn;\u0026thinsp;6 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e296\u0026ndash;365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e324\u0026thinsp;\u0026plusmn;\u0026thinsp;11 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e282\u0026ndash;383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e352\u0026thinsp;\u0026plusmn;\u0026thinsp;22 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e312\u0026ndash;403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,2564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNutritional traits\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipids (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,55\u0026thinsp;\u0026plusmn;\u0026thinsp;0,05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,26\u0026thinsp;\u0026minus;\u0026thinsp;3,80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,90\u0026thinsp;\u0026plusmn;\u0026thinsp;0,13 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,13\u0026thinsp;\u0026minus;\u0026thinsp;4,53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4,10\u0026thinsp;\u0026plusmn;\u0026thinsp;0,05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3,98\u0026thinsp;\u0026minus;\u0026thinsp;4,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,0018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,58\u0026thinsp;\u0026plusmn;\u0026thinsp;0,14 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,55\u0026thinsp;\u0026minus;\u0026thinsp;9,20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,62\u0026thinsp;\u0026plusmn;\u0026thinsp;0,13 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,04\u0026ndash;9,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e8,50\u0026thinsp;\u0026plusmn;\u0026thinsp;0,15 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8,14\u0026thinsp;\u0026minus;\u0026thinsp;8,77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,9037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,90\u0026thinsp;\u0026plusmn;\u0026thinsp;0,02 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,79\u0026thinsp;\u0026minus;\u0026thinsp;2,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,03\u0026thinsp;\u0026plusmn;\u0026thinsp;0,06 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,77\u0026thinsp;\u0026minus;\u0026thinsp;2,27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e2,25\u0026thinsp;\u0026plusmn;\u0026thinsp;0,02 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,22\u0026thinsp;\u0026minus;\u0026thinsp;2,29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRE (kcal kg⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4411\u0026thinsp;\u0026plusmn;\u0026thinsp;3,15 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4395\u0026ndash;4433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4416\u0026thinsp;\u0026plusmn;\u0026thinsp;3,94 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4399\u0026ndash;4436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4401\u0026thinsp;\u0026plusmn;\u0026thinsp;3,77 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4395\u0026ndash;4412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,1083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYield and yield components\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGY (kg ha⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5562\u0026thinsp;\u0026plusmn;\u0026thinsp;163 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4609\u0026ndash;6684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6093\u0026thinsp;\u0026plusmn;\u0026thinsp;237 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5286\u0026ndash;6571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e9008\u0026thinsp;\u0026plusmn;\u0026thinsp;502 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8506\u0026ndash;9510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGM (grains m⁻\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2324\u0026thinsp;\u0026plusmn;\u0026thinsp;120 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1693\u0026ndash;3166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1389\u0026thinsp;\u0026plusmn;\u0026thinsp;141 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e966\u0026ndash;1822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e3721\u0026thinsp;\u0026plusmn;\u0026thinsp;840 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2881\u0026ndash;4561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTGW (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e326\u0026thinsp;\u0026plusmn;\u0026thinsp;9 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e285\u0026ndash;393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e349\u0026thinsp;\u0026plusmn;\u0026thinsp;17 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e308\u0026ndash;396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e405\u0026thinsp;\u0026plusmn;\u0026thinsp;40 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e365\u0026ndash;445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,0289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNutritional traits\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipids (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,62\u0026thinsp;\u0026plusmn;\u0026thinsp;0,05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,32\u0026thinsp;\u0026minus;\u0026thinsp;3,89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,79\u0026thinsp;\u0026plusmn;\u0026thinsp;0,11 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,47\u0026thinsp;\u0026minus;\u0026thinsp;4,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4,18\u0026thinsp;\u0026plusmn;\u0026thinsp;0,03 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4,15\u0026thinsp;\u0026minus;\u0026thinsp;4,20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,0032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,96\u0026thinsp;\u0026plusmn;\u0026thinsp;0,11 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,09\u0026thinsp;\u0026minus;\u0026thinsp;8,57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,73\u0026thinsp;\u0026plusmn;\u0026thinsp;0,33 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,71\u0026thinsp;\u0026minus;\u0026thinsp;9,64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e9,13\u0026thinsp;\u0026plusmn;\u0026thinsp;0,22 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8,91\u0026thinsp;\u0026minus;\u0026thinsp;9,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,0036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,93\u0026thinsp;\u0026plusmn;\u0026thinsp;0,02 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,85\u0026thinsp;\u0026minus;\u0026thinsp;2,06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,04\u0026thinsp;\u0026plusmn;\u0026thinsp;0,04 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,94\u0026thinsp;\u0026minus;\u0026thinsp;2,14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e2,31\u0026thinsp;\u0026plusmn;\u0026thinsp;0,03 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,28\u0026thinsp;\u0026minus;\u0026thinsp;2,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRE (kcal kg⁻\u0026sup1;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4400\u0026thinsp;\u0026plusmn;\u0026thinsp;3,01 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4383\u0026ndash;4416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4424\u0026thinsp;\u0026plusmn;\u0026thinsp;5,79 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4411\u0026ndash;4440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4407\u0026thinsp;\u0026plusmn;\u0026thinsp;3,14 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4404\u0026ndash;4410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0,003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[INSERT Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e HERE]\u003c/p\u003e \u003cp\u003eWhen data were integrated across campaigns (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), early planting significantly outperformed late planting in GY (7831 vs 6040 kg ha⁻\u0026sup1;; p\u0026thinsp;=\u0026thinsp;0.0024) and NGM (3344 vs 2230 grains m⁻\u0026sup2;; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with no differences in TGW. Protein content was slightly higher in early than in late planting (7.55 vs 7.09%), while the remaining nutritional traits showed no differences.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Integrative interpretation of multi-year patterns within a meteorological framework\u003c/h2\u003e \u003cp\u003eThe integrative heatmap (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) revealed a stable multi-year structure, in which early plantings consistently clustered with high grain yields, low fungal loads (NTotal and NFv), and minimal fumonisin accumulation, whereas late plantings clustered with reduced yields, higher NFv values, and elevated fumonisin contamination. This tendency was reproduced across campaigns and is consistent with patterns reported in other maize-growing regions (Blandino et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Krnjaja et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast, the nutritional composition of grains varied little between planting dates or seasons, indicating that proximate grain traits were substantially less sensitive to planting date effects than sanitary and agronomic outcomes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[INSERT Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e HERE]\u003c/p\u003e \u003cp\u003eThe patterns observed for NFv and Total FBs can be interpreted within the distinct meteorological regimes experienced by early and late planting (Table S4; Figs. S1\u0026ndash;S3). Two phenological periods are particularly relevant: the flowering window and the ripening stage, each characterized by environmental conditions that modulate fungal establishment and fumonisin accumulation, respectively (Marin et al., 2004; Mart\u0026iacute;nez et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Cao et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Moschini et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dinolfo et al., 2022; Gbashi et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; de Oliveira Rocha et al., 2024). Epidemiological models such as FUMAgrain (Maiorano et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) also distinguish these two phases, attributing early post-silking conditions primarily to infection risk and later grain-fill conditions to fumonisin synthesis.\u003c/p\u003e \u003cp\u003eTo assess how the environmental conditions during flowering related to the observed NFv and Total FBs patterns, we examined temperature and precipitation across the ~\u0026thinsp;28-day anthesis window (\u0026minus;\u0026thinsp;7/+21 days; Table S4) and generated three-dimensional response surfaces based on these variables (Fig. S3). The surface showed that NFv increased primarily with temperature, indicating that warmer flowering environments promoted early fungal establishment (Fig. S3a). This response aligns with evidence showing that high temperatures around silking increase silk susceptibility and facilitate \u003cem\u003eF. verticillioides\u003c/em\u003e infection and early colonization (Cao et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Accordingly, the comparatively warmer flowering conditions of late planting likely enhanced the potential for early establishment of \u003cem\u003eF. verticillioides\u003c/em\u003e relative to early-sown crops. According to Maiorano et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and de la Campa et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), fumonisin contamination can be predicted from weather conditions occurring within specific sub-periods of the flowering stage (particularly the early post-silking window) where high maximum temperatures increase fumonisin levels and rainfall tends to mitigate them. In our study, however, the response surface for Total FBs (Fig. S3b) showed a marked increase in fumonisin accumulation when high temperatures coincided with high precipitation during flowering. This difference likely reflects our analytical approach, which considered the entire 28-day flowering window rather than distinguishing the discrete sub-stages.\u003c/p\u003e \u003cp\u003eRegarding ripening, the meteorological divergence between planting dates was pronounced (Figs. S2\u0026ndash;S3). Early-sown maize matured during the typically dry late-summer period, which likely limited kernel moisture retention and contributed to the low Total FBs values observed. In contrast, late-sown maize ripened under markedly wetter autumn conditions, with recurrent rainfall and higher ambient humidity, which likely prolonged kernel moisture. In this context, the higher fumonisin concentrations observed in late planting can be interpreted as being consistent with the well-established requirement of warm-to-moderate temperatures combined with elevated kernel moisture during grain maturation (Maiorano et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Cao et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; van Rensburg et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Moschini et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dinolfo et al., 2022; de Oliveira Rocha et al., 2024).\u003c/p\u003e \u003cp\u003eAttempts to correlate fungal presence/colonization metrics (measured as counts of colony-forming units, incidence, severity, or fungal DNA quantification) with final fumonisin concentrations have yielded a notably inconsistent body of evidence. While some studies report positive associations between the presence of \u003cem\u003eF. verticillioides\u003c/em\u003e and FBs levels, others find weak or no detectable relationships (Table S5). This inconsistency reflects the fact that fumonisin production is not strictly proportional to fungal proliferation and that the strength and direction of this association depend on multiple factors that are difficult to capture simultaneously in field experiments. These include hybrid-specific traits, environmental conditions during silking, ripening, and the pre-harvest period, the extent of insect damage, the load of primary inoculum from maize residues, tillage practices, and the potential contribution of seedborne or systemic infections (Mart\u0026iacute;nez et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Cao et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; van Rensburg et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Moschini et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Together, these mechanisms help explain the instability of the NFv\u0026ndash;FBs relationship observed across years in our dataset and support the view that fungal load alone may not be a reliable predictor of fumonisin contamination.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. CONCLUSIONS","content":"\u003cp\u003eThis multi-year analysis revealed clear differences between early and late maize plantings in sanitary status, fumonisin contamination, and grain yield. Across the evaluated campaigns, the direction of planting-date effects on grain sanitary status was maintained, although the magnitude of \u003cem\u003eF. verticillioides\u003c/em\u003e colonization and fumonisin contamination varied among years. Overall, early planting were associated with lower \u003cem\u003eF. verticillioides\u003c/em\u003e colonization and fumonisin levels and higher yields, whereas late planting generally showed higher fungal presence and mycotoxin contamination. These contrasts were observed despite all hybrids carrying lepidopteran resistance traits, indicating a predominant role of meteorological conditions during flowering and grain filling. The relationship between \u003cem\u003eF. verticillioides\u003c/em\u003e abundance in grains and fumonisin contamination was not stable across years, highlighting that toxin accumulation is not strictly determined by infection levels but is strongly modulated by environmental conditions during specific reproductive periods. In contrast, grain nutritional composition remained comparatively stable across planting dates and seasons. Taken together, these results indicate that, while late planting is not intrinsically unfavorable, early planting can be associated with lower sanitary pressure and reduced fumonisin risk under certain climatic scenarios.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report there are no competing interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Vicerrectorado de Investigaci\u0026oacute;n y Desarrollo - Universidad del Salvador under grant PI USAL 80020230100004US, and University of Buenos Aires under grant UBACYT 20020220100114BA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026apos;s contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMar\u0026iacute;a Cecilia P\u0026eacute;rez-Piz\u0026aacute;: Conceptualization, Methodology, Investigation, Data curation, Validation, Visualization, Project administration, Funding acquisition, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eSebasti\u0026aacute;n Vicente: Investigation, Data curation, Validation, Visualization, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eFrancisco Jos\u0026eacute; Sautua: Investigation, Data curation, Validation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eMousegne Fernando: Investigation, Data curation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eJecke Fernando: Investigation, Data curation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eVago Mar\u0026iacute;a Elena: Investigation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eMarcelo An\u0026iacute;bal Carmona: Conceptualization, Investigation, Data curation, Validation, Supervision, Project administration, Funding acquisition, Resources, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eSebasti\u0026aacute;n Alberto Stenglein: Conceptualization, Investigation, Data curation, Validation, Supervision, Project administration, Resources, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAapresid (2022). \u003cem\u003eAlerta de enfermedades e insectos en ma\u0026iacute;z tard\u0026iacute;o.\u003c/em\u003e Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.aapresid.org.ar/blog/alerta-enfermedades-e-insectos-maiz-tardio\u003c/span\u003e\u003cspan address=\"https://www.aapresid.org.ar/blog/alerta-enfermedades-e-insectos-maiz-tardio\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnumudu, C. 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Grain colonization by fumonisin-producing \u003cem\u003eFusarium\u003c/em\u003e spp. and fumonisin synthesis in South African commercial maize in relation to prevailing weather conditions. \u003cem\u003eCrop Protection\u003c/em\u003e, \u003cem\u003e102\u003c/em\u003e, 129\u0026ndash;136.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Zea mays, Fusarium verticillioides, fumonisins, planting date, interannual variability, meteorological conditions","lastPublishedDoi":"10.21203/rs.3.rs-8612955/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8612955/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFusarium ear rot, primarily caused by \u003cem\u003eFusarium verticillioides\u003c/em\u003e, and the associated fumonisin contamination represent major sanitary constraints to maize (\u003cem\u003eZea mays\u003c/em\u003e L.) production worldwide. Previous single-season evidence under Argentine conditions indicated that late planting enhances fungal colonization and fumonisin accumulation in maize grains. Here, we evaluated the interannual variability of these planting-date effects through a multi-year field analysis conducted across three independent growing seasons (2020\u0026ndash;2024). \u003cem\u003eF. verticillioides\u003c/em\u003e grain colonization, fumonisin contamination, grain yield, and nutritional composition were assessed under contrasting planting dates (early vs. late) in San Antonio de Areco, Buenos Aires, Argentina. Across seasons, late plantings consistently exhibited higher \u003cem\u003eF. verticillioides\u003c/em\u003e grain colonization, accompanied by markedly increased fumonisin concentrations, whereas early plantings showed lower sanitary pressure and higher yields. However, the magnitude of these responses and the relationship between fungal abundance and fumonisin accumulation varied substantially among years, indicating strong modulation by environmental conditions. Grain nutritional composition remained comparatively stable across planting dates and seasons. Overall, these results demonstrate that while the direction of planting-date effects on maize sanitary status is maintained across years, their intensity is highly dependent on interannual climatic variability. Under the evaluated conditions, early planting emerged as the most reliable strategy to reduce fumonisin risk while sustaining productivity in maize cropping systems.\u003c/p\u003e","manuscriptTitle":"Interannual variability of planting-date effects on Fusarium verticillioides grain colonization and fumonisin contamination in maize","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 12:47:07","doi":"10.21203/rs.3.rs-8612955/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ec58e248-2431-4c46-ac68-6fd015bb3d66","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Reject after review","date":"2026-05-15T08:53:24+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T12:55:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-11 12:47:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8612955","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8612955","identity":"rs-8612955","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}