Environmental Drivers of Broiler Carcass Condemnation in Humid Subtropical Regions: A Predictive Model Incorporating Lagged Climatic Effects

Environmental Drivers of Broiler Carcass Condemnation in Humid Subtropical Regions: A Predictive Model Incorporating Lagged Climatic Effects | 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 Environmental Drivers of Broiler Carcass Condemnation in Humid Subtropical Regions: A Predictive Model Incorporating Lagged Climatic Effects Alessandro Silva Lopes, Guilherme Francisco Sobierai Batista, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9003534/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Intensive poultry production in humid subtropical agro-ecologies faces unique environmental challenges that compromise carcass quality, welfare, and food security. While climatic influences are recognized, the temporal dimensions of these effects remains largely underexplored. This study quantified the immediate and time-lagged (1–3 months) influences of climatic variables on 12 causes of broiler carcass condemnation in a representative subtropical hub. Longitudinal data (2021–2023) from federally inspected slaughterhouses in Santa Catarina, Brazil, a global sentinel for Köppen Cfa and Cfb climate zones, were analyzed using Spearman rank correlation and advanced regression models, including Generalized Linear Models (GLM) with a quasibinomial distribution. Total condemnation rates rose from 13.1% in 2021 to 15.5% in 2023, dominated by gastrointestinal contamination (5.0%) and skin lesions (3.5%). Regression analysis revealed that lagged precipitation was a significant predictor for arthritis and cellulitis (p < 0.05), whereas higher temperatures and heat index reduced rejections for ascites and skin lesions (p < 0.01). A quasibinomial GLM identified lagged heat index (β = − 0.096, p = 0.051) as a critical driver for inflammatory lesions. These findings demonstrate that avian health in intensive systems is governed by a temporal environmental paradigm where conditions during early rearing phases dictate final carcass quality. The established predictive models offer an extrapolatable blueprint for seasonal management across global humid subtropical belts to mitigate economic leakages and enhance production sustainability. carcass condemnation broiler production climatic variability lagged effects poultry health Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction The global intensification of the poultry industry has increasingly centered on tropical and subtropical regions, which now account for a significant portion of the world’s animal protein supply (Alvares et al. 2013 ; Chaiban et al. 2020 ). In these agro-ecological zones, particularly those characterized by humid subtropical climates (Köppen-Geiger Cfa and Cfb), intensive broiler production faces unique environmental challenges (Liu et al. 2020 ). High thermal amplitude, seasonal surges in precipitation, and sustained relative humidity above 70% are primary stressors that mediate host-pathogen interactions and metabolic homeostasis (Mottet and Tempio 2017 ). The efficiency and sustainability of these systems are measured by their ability to deliver wholesome carcases. Any deviation from clinical health or processing standards results in carcass condemnation, the total or partial rejection of meat during sanitary inspection. Beyond the immediate economic impact, which can represent substantial annual losses for individual processing facilities (Hortêncio et al. 2022 ), condemnations represent a critical “leakage” in the food value chain (Buzdugan et al. 2020 ). This food waste directly undermines the United Nations’ Sustainable Development Goals (SDGs), specifically Zero Hunger (SDG 2) and Responsible Consumption and Production (SDG 12), while signaling compromised animal welfare on the farm (Karlsson et al. 2025 ). In humid subtropical belts, encompassing production hubs in Southern Brazil, the Southeastern United States, Southern China, and Eastern Australia, carcass rejections often follow cyclical patterns (Meteyake et al. 2020 ; Kpomasse et al. 2021 ). Pathologies such as ascites syndrome are strongly linked to environmental stressors during specific seasonal windows (Hu and Cheng 2021 ), whereas inflammatory lesions, cellulitis, and arthritis are mediated by litter moisture and ambient humidity (Wideman et al. 2013 ; Pirompud et al. 2023 ). However, the biological impact of environmental stressors is rarely instantaneous. Delayed physiological responses or the gradual deterioration of litter quality suggest that climatic conditions weeks or months prior to slaughter may be more predictive of condemnation rates than concurrent weather on the day of processing (Kang et al. 2020 ; Nawaz et al. 2021 ). Despite the global significance of these subtropical belts, comprehensive models quantifying lagged meteorological effects on condemnation causes remain scarce. Most existing literature focuses on single-cause analyses or concurrent climatic effects, failing to capture the complex temporal dynamics of intensive avian health in these sensitive environments (Hortêncio et al. 2022 ; Carvalho et al. 2025 ; Pirompud et al. 2024 ). Santa Catarina, Brazil, serves as an ideal global sentinel for this research due to its status as a premier regional poultry exporter operating high-density intensive systems under representative Cfa/Cfb climates. Therefore, quantifying the environmental drivers of poultry health in this region provides a generalizable blueprint for intensive systems across the humid subtropical belt (Liu et al. 2020 ). This study aims to quantify the effects of temperature, precipitation, humidity, and heat index, with time lags of 1 to 3 months, on the condemnation rates for 12 distinct causes in federally inspected broiler slaughterhouses between 2021 and 2023. By utilizing advanced statistical approaches, including Generalized Linear Models with a quasibinomial distribution, this research seeks to establish a predictive environmental framework to mitigate economic losses and enhance animal welfare in subtropical agro-ecologies. 2. Materials and Methods 2.1. Study Site and Representative Subtropical Context The study was conducted using data from broiler production systems in the West region of Santa Catarina, Southern Brazil. This region is a global sentinel for intensive poultry production, characterized by a humid subtropical climate, Köppen-Geiger types Cfa and Cfb (Alvares et al. 2013 ). This agro-ecological zone is defined by well-distributed rainfall throughout the year and pronounced thermal amplitude, mirroring intensive poultry hubs in the Southeastern United States, Southern China, and Eastern Australia. The municipality of Chapecó serves as the primary processing hub for this region, which accounts for approximately 79.4% of the state’s poultry output. 2.2. Carcass Condemnation Data and Sanitary Inspection Data on carcass condemnations were retrieved from the management information system of the Federal Inspection Service (SIF), under Brazil’s Ministry of Agriculture, Livestock, and Food Supply (MAPA), covering the period from February 2021 to December 2023 (MAPA 2017 ). The records were filtered for broilers, excluding animals that died during transport or pre-slaughter phases. Twelve primary condemnation causes were analyzed: gastrointestinal contamination (GC), skin lesions (SL), arthritis (AR), airsacculitis (AI), cellulitis (CE), processing failures (PF), traumatic lesions (TL), ascites (AS), visual defects (VD), septicaemia (SE), cachexia (CA), and inflammatory lesions (IL) (Salines et al. 2017 ). Partial and total condemnations were merged into a single variable for each cause to standardize the quantitative analysis. 2.3. Environmental Monitoring and Climate Indices Meteorological data were obtained from the Chapecó climate station, maintained by the National Institute of Meteorology (INMET). The variables included total monthly precipitation (mm), mean monthly temperature (°C), and mean relative humidity (%). To quantify the combined effect of temperature and moisture, the Heat Index (HI) was calculated using Eq. 1, where 𝑇 is the mean monthly temperature (°F), and 𝑅𝐻 is the mean monthly relative humidity (%) (Steadman 1979 ). 2.4. Statistical Modeling and Predictive Analytics Monthly aggregated data (Feb 2021-Dec 2023; n = 34 observations) were analyzed. Given the limited number of time points relative to the potential predictors, modeling strategies prioritized parsimony and biological plausibility. To explore the nonlinear relationship between climatic drivers and poultry health, Spearman rank correlation (ρ) was applied to concurrent data and time-lagged variables (1, 2, and 3 months). Spearman’s rank correlation was chosen because the datasets are nonlinear and nonnormal (Zar 2010 ). For each month, the total values for each condemnation cause were divided by the total number of slaughters in that month and multiplied by 100 to obtain percentage values, ensuring that correlations reflected condemnation proportions rather than total numbers. Additionally, because the effects of climatic variables on various aspects of poultry production may not be immediate (Kumar et al. 2021 ), heatmaps accounting for time lags of 1, 2, and 3 months were produced. Correlation coefficients with p-values less than 0.05 were considered statistically significant. All heatmaps were created using the R package corrplot (Wei and Simko 2024 ). To quantify the effects of climatic variables on the total condemnation rate and each of the 12 condemnation causes, as dependent variables, multiple linear regression models were initially fitted using R software version 4.3.3 (R Core Team 2024 ). The dependent variable \(Y\) , representing the condemnation rate for each cause, was modelled (Eq. 2) as a function of the concurrent and lagged (1-month) climatic variables: precipitation (mm, \({X}_{1}\) ), mean temperature (°C, \({X}_{2}\) ), mean humidity (%, \({X}_{3}\) ), heat index (a composite measure of temperature and humidity, \({X}_{4}\) ), the precipitation lag-1 (mm, \({X}_{5}\) ), mean temperature lag-1 ( \({X}_{6}\) , °C), mean humidity lag-1 (%, \({X}_{7}\) ), and heat index lag-1 ( \({X}_{8}\) ). These variables were selected based on their relevance to slaughterhouse condemnations and prior Spearman correlation analyses. The maximum and minimum temperatures and humidities were excluded because they were highly correlated with their respective means, thereby reducing multicollinearity. Month and year were included as categorical control variables to account for seasonality and temporal trends, respectively. April was selected as the reference month because it is a transition season, with intermediate climatic conditions, and 2021 was selected as the reference year because it was the first year of analysis. $$Y={\beta}_{0}+\sum_{\text{i}=1}^{8}{\beta}_{\text{i}}{X}_{\text{i}}+\sum_{\text{i}=1}^{11}{\alpha}_{\text{i}}{\text{M}\text{o}\text{n}\text{t}\text{h}}_{\text{i}}+\sum_{\text{i}=1}^{2}{\gamma}_{\text{i}}{\text{Y}\text{e}\text{a}\text{r}}_{\text{i}}+ϵ\left(2\right)$$ where \({\beta}_{0}\) is the intercept, \({\beta}_{\text{i}}\) (i = 1 to 8) are coefficients for the climatic variables, \({\alpha}_{\text{i}}\) (i = 1 to 11) are coefficients for the month levels, \({\gamma}_{\text{i}}\) (i = 1 to 2) are coefficients for the year levels, and \(ϵ\) is the residual error. To optimize model fit and select the most relevant predictors, stepwise regression was performed using the Akaike Information Criterion (AIC) with the stepAIC function from the MASS package (Venables and Ripley 2022 ). Predictors with p < 0.05 were considered significant, while those with p < 0.1 were reported as marginally significant to capture potential trends relevant to slaughterhouse conditions. Model diagnostics included tests for normality of residuals (Shapiro-Wilk test), homoscedasticity (Breusch-Pagan test, using the lmtest package; Zeileis and Hothorn 2022 ), and multicollinearity (Variance Inflation Factor, VIF, using the car package; Fox and Weisberg 2019 ). Complete diagnostic results, including Shapiro-Wilk p-values, Breusch-Pagan statistics, and full VIF tables for all 13 models (TC + 12 causes), are reported in Tables S3-S8. Moderate multicollinearity was observed in some stepwise models (e.g., VIF > 5 for \({X}_{2}\) up to 22.92 in total condemnation (TC) model; GVIF (1/(2df)) > 4.5 in several; see Tables S3-S6). To address this, a robustness check using ridge regression (Zhang and Politis 2022 ) confirmed consistent effect directions and significance for key predictors. Predictors with high VIFs were retained because of their biological relevance to poultry health, such as interactions between temperature and humidity (Nawab et al. 2018 ). Post hoc power analysis (G*Power 3.1, Faul et al. 2007 ) confirmed > 80% power for key predictors (e.g., lagged precipitation in arthritis (AR)/cellulitis (CE) models: n = 34, effect size f 2 = 0.15, α = 0.05). For inflammatory lesions, the linear model violated assumptions (Shapiro-Wilk p = 0.0769, Breusch-Pagan p = 0.001, adjusted R 2 = − 0.471 in the base model), leading to the adoption of a generalized linear model (GLM) with quasibinomial distribution to account for the proportional nature of the data, heteroscedasticity, and potential non-normality. The GLM included the heat index, lag-1 heat index, and year, with a dispersion parameter estimated to account for overdispersion. Results were summarized using regression coefficients (β), standard errors, p-values, adjusted R 2 for linear models, or deviance reduction and dispersion parameters for the GLM. Detailed regression tables for all models are provided in Supplementary Tables (S3-S6). 3. Results 3.1. Condemnation Patterns in the Representative Subtropical Hub Between February 2021 and December 2023, the total condemnation rate (TC) in the intensive production hub of Santa Catarina, serving as a sentinel for humid subtropical regions, increased significantly, rising from an average of 13.1% in 2021 to 15.5% in 2023. The evolution of these rates is illustrated in a ridgeline plot (Fig. 1 ), which displays a unimodal distribution in 2021 with low variability, transitioning to a bimodal distribution in 2022 and 2023, with seasonal peaks consistently appearing in the May-June window. Analysis of the 12 primary causes (Fig. 2 ) revealed that gastrointestinal contamination (GC, 5.0%) and skin lesions (SL, 3.5%) were the dominant drivers of rejection. Other significant contributors included arthritis (AR, 1.3–2.3%), airsacculitis (AI, 0.2–1.4%), processing failures (PF, 0.7–0.9%), and cellulitis (CE, ~ 0.7%). Contamination and skin-related rejections remain the primary technological bottlenecks, consistent with findings from other high-density production hubs in Southern Brazil (Kanabata et al. 2023 ; Muchon et al. 2019 ). Descriptive statistics for annual production and condemnation rates are summarized in Table 1 . Table 1 Descriptive statistics for selected condemnation causes and the number of slaughters Variable Year Mean Standard Deviation Minimum Maximum Animals Slaughtered (Million) 2021 44.07 2.87 41.97 50.86 2022 48.18 7.79 38.77 58.86 2023 61.03 3.94 55.68 68.06 Condemnation Rate 2021 0.1309 0.0051 0.1259 0.1424 2022 0.1447 0.0129 0.1263 0.1647 2023 0.1545 0.0137 0.1367 0.1760 Gastrointestinal Contamination Proportion 2021 0.0505 0.0020 0.0477 0.0535 2022 0.0468 0.0040 0.0413 0.0527 2023 0.0501 0.0042 0.0432 0.0548 Skin Lesions Proportion 2021 0.0326 0.0122 0.0204 0.0423 2022 0.0352 0.0077 0.0289 0.0453 2023 0.0376 0.0065 0.0293 0.0505 Arthritis Proportion 2021 0.0131 0.0026 0.0100 0.0186 2022 0.0176 0.0040 0.0131 0.0236 2023 0.0225 0.0083 0.0137 0.0370 3.2. Environmental Dynamics and Time-Lagged Correlations The behavior of climatic variables during the study period, including significant surges in precipitation and high relative humidity, is displayed in time-series plots (Fig. 3 ). Spearman rank correlation analysis (Fig. 4 ) identified that the influence of the subtropical environment on poultry health is often characterized by significant time lags. While concurrent temperature showed a weak positive correlation with TC (ρ = 0.24), lagged relative humidity at 2 months exhibited a much stronger positive association (ρ = 0.52, p < 0.05), as shown in the supplementary heatmaps (Figs. S1-S3). Pathology-specific correlations further highlighted the role of seasonal stressors in Cfa climates: Airsacculitis (AI): Positively correlated with mean, maximum, and minimum temperatures (ρ = 0.22–0.24, p = 0.02) without lag (Fig. 4 ) and at a 1-month lag (Fig. S1 ). Ascites (AS): Strongly associated with winter conditions, showing a negative correlation with temperature range without lag (ρ = − 0.55, p = 0.01; Fig. 4 ). Arthritis (AR) and Cellulitis (CE): Demonstrated delayed responses to environmental moisture, with AR showing positive correlations with precipitation and humidity at 1 to 3-month lags (Figs. S1-S3). 3.3. Predictive Modeling of Climatic Stressors Stepwise multiple linear regression and Generalized Linear Models (GLM) quantified the magnitude of environmental drivers while controlling for temporal effects (see results in Tables S4-S6). Ridge regression confirmed consistent effect directions for key predictors. The model for Ascites (AS) demonstrated exceptional robustness (adjusted R 2 = 0.975), driven by the negative effects of mean temperature (β = − 0.021) and heat index (β = − 0.008), confirming the cold-stress axis typical of subtropical winters. For inflammatory lesions (IL), the quasibinomial GLM successfully addressed overdispersion and heteroscedasticity, identifying the lagged heat index (β = − 0.096) as a significant environmental predictor. This suggests that warmer conditions in the month prior to slaughter mitigate immune-mediated pathologies. 4. Discussion 4.1. The Subtropical Paradigm and Environmental Dynamics The observed total condemnation rates in this study are higher than those reported for previous decades in Brazilian industrial poultry clusters (Muchon et al. 2019 ), reflecting the cumulative impact of production intensification and the evolving sensitivity of Federal Inspection Service (SIF) protocols. The increase in broiler carcass condemnation rates from 13.1% in 2021 to 15.5% in 2023 underscores a growing challenge for intensive poultry systems in humid subtropical regions (Kpomasse et al. 2021 ). The transition to a bimodal distribution in 2022 and 2023 (Fig. 1 ), with consistent peaks in the May-June window, identifies a seasonal vulnerability tied to the climatic characteristics of Köppen-Geiger Cfa and Cfb zones (Alvares et al. 2013 ). These agro-ecological zones, characterized by high relative humidity and significant thermal amplitude, mirror production conditions in the Southeastern United States, Southern China, and Eastern Australia, making these findings globally representative (Peel et al. 2007 ; Thobe et al. 2025 ). While global broiler condemnation rates are often reported around 1.04% for total rejection in some regions, the high rates observed here (reflecting the sum of partial and total rejections) highlight the sensitivity of high-performance genetic strains to environmental stressors in the subtropics (Salines et al. 2017 ; Belintani et al. 2019 ). The significant “year effects” identified in the regression models for 2022 and 2023 suggest that, beyond climate, operational factors such as refined inspection protocols or changes in slaughter-line technology are influencing the data trends. 4.2. Delayed Environmental Effects on Health Causes A novel contribution of this study is the identification of the temporal dimension of poultry rejections. Gastrointestinal contamination (GC, 5.0%), the leading cause of rejection, exhibited strengthened correlations with temperature at 2- and 3-month lags (ρ = 0.62–0.63, p = 0.02; Fig. S2 ). Unlike previous studies focusing on slaughter-day weather, this suggests that environmental conditions during the early rearing phases influence the microbial load or intestinal integrity of the birds at the end of the cycle (Rouger et al. 2017 ). For inflammatory lesions (IL), the use of a Generalized Linear Model (GLM) with a quasibinomial distribution was essential to handle the overdispersion of proportional data (Table S6). The identification of the lagged heat index (β = − 0.096, p = 0.051) as a predictor suggests that warmer conditions in the month prior to slaughter may mitigate cold-induced immune stress and reduce the subsequent metabolic demand (Bohler et al. 2021 ). 4.3. The Moisture-Litter-Lesion Axis Arthritis (AR) and cellulitis (CE) were significantly predicted by lagged precipitation (β = 0.002) and mean humidity (β = − 0.038 to − 0.027; Table S4). In humid subtropical agro-ecologies, heavy rainfall surges lead to “moist litter” or caking, which increases ammonia levels and facilitates the entry of pathogens like Mycoplasma and E. coli into the joints and subcutaneous tissues. The delay of 1–3 months between high moisture events and carcass rejection confirms that litter quality early in the flock’s life dictates final carcass quality. Similarly, skin lesions (SL) were negatively correlated with temperature range (ρ = − 0.66) and positively with humidity (ρ = 0.31–0.38; Fig. 4 ). These results align with findings from high-rainfall regions in Southeast Asia, where high stocking densities combined with sustained humidity exacerbate contact dermatitis (Kang et al. 2020 ). 4.4. Metabolic Stress and Thermoregulation Ascites (AS) showed an exceptionally robust fit (adjusted R 2 = 0.975), driven primarily by cold stress (negative effects of mean temperature and heat index; Table S5) (Wideman et al. 2013 ). In the Southern Hemisphere winter, low temperatures increase the metabolic demand for oxygen to maintain thermogenesis (Kumar et al. 2021 ; Moreira et al. 2024 ). In rapidly growing broilers, this leads to pulmonary arterial hypertension and abdominal fluid accumulation, a pattern also documented in temperate-subtropical transition zones worldwide (Wideman et al. 2113; Belintani et al. 2019 ). Airsacculitis (AI) peaked at 1.4% in 2023, showing a positive correlation with concurrent temperature (Fig. 4 ). This indicates that warmer conditions may exacerbate the effects of respiratory pathogens, possibly through increased dust levels or poor air quality during periods of low ventilation aimed at heat conservation. 4.5. Economic and Sustainability Implications With an estimated annual financial loss of US $ 150,000 per processing facility, carcass rejections represent a significant “leakage” in the protein value chain (Salines et al. 2017 ; Azizpour and Amirajam 2024 ). Reducing these losses directly contributes to the United Nations Sustainable Development Goals, specifically Zero Hunger (SDG 2) and Responsible Consumption and Production (SDG 12), by decreasing food waste and improving the environmental footprint per kilogram of meat produced (McManus et al. 2023 ). 4.6. Limitations and Future Directions Reliance on meteorological data from a single station may limit generalizability to mountainous microclimates within the region. Additionally, the model did not include farm-level variables such as stocking density, vaccination protocols, or specific genetic lineages, like Ross 308 or Hubbard, which are known to mediate environmental sensitivity. Future research should expand the geographic scope by incorporating grid-based climatic data and utilize machine learning algorithms, such as random forest or ARIMA models, to improve predictive accuracy for seasonal peaks. Including One Health indicators, such as the phylogenetic profiling of E. coli in condemned carcasses, could further link environmental management with public health safety. 4.7. Conclusion This study demonstrates that broiler carcass condemnation patterns are influenced by both concurrent climatic conditions and environmental factors from earlier production phases. Specifically, cold stress increased ascites rates (p < 0.01), while lagged precipitation/humidity drove inflammatory and joint lesions (p ≤ 0.05). Given this ecological/regional study design, findings represent associations rather than causation. Nevertheless, results provide actionable insights for anticipating seasonal risks and optimizing management in humid subtropical poultry systems. Declarations Disclosure Statement The authors declare that they have no relevant financial or non-financial interests to disclose. Ethical Compliance Compliance with ethical standards was strictly maintained. The manuscript does not contain clinical studies or direct experimentation with human or animal subjects. All data were retrieved from official secondary records provided by governmental sanitary inspection services, ensuring anonymity and adherence to international guidelines for epidemiological reporting. Funding This study was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES (ASL, Financial Code 001) and Fundação de Apoio à Pesquisa e Inovação do Estado de Santa Catarina - FAPESC (GFSB for the grant and ACG for project number 2025TR1577). Authors Contributions All authors contributed to equally to the study and to the final version of the manuscript. Moreover, all authors read and approved the final manuscript. Acknowledgements The authors express their gratitude to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES (ASL, Financial Code 001) and Fundação de Apoio à Pesquisa e Inovação do Estado de Santa Catarina - FAPESC (GFSB for the grant and ACG for project number 2025TR1577). Data Availability Statement The data that support the findings of this study are available from the corresponding author, WSR, upon reasonable request. References Alvares CA, Stape JL, Sentelhas PC, Gonçalves JLM, Sparovek G (2013) Köppen’s climate classification map for Brazil. Meteorol Z 22(6):711–728. https://doi.org/10.1127/0941-2948/2013/0507 Azizpour A, Amirajam Z (2024) Causes for carcass condemnations of slaughtered poultry in the industrial slaughterhouse of Namin, Ardabil province, Iran. Iran J Vet Sci Technol 16:1–8. https://doi.org/10.22067/IJVST.2024.82675.1260 Belintani RT, Garcia RG, Gil JLRS, de Alencar Nääs I, Gandra ERS, de Cassia Komiyama C., Caldara FR (2019) Broiler carcass condemnation pattern during processing. Rev Bras Zootec 48:e20180046. https://doi.org/10.1590/rbz4820180046 Bohler MW, Chowdhury VS, Cline MA, Gilbert ER (2021) Heat stress response in birds: a review of the neural components. Biology 10:1095. https://doi.org/10.3390/biology10111095 Buzdugan SN, Chang YM, Huntington B, Rushton J, Guitian J, Alarcon P, Blake DP (2020) Identification of production chain risk factors for slaughter condemnation of broiler chickens. Prev Vet Med 181:105036. https://doi.org/10.1016/j.prevetmed.2020.105036 Carvalho FES, Salle FO, Borges KA, Carvalho KBM, Furian TQ, Salle CTP (2025) Carcass condemnation prediction using artificial neural networks in poultry slaughterhouses. Res Vet Sci 196:105884. https://doi.org/10.1016/j.rvsc.2025.105884 Chaiban C, Robinson TP, Fèvre EM, Ogola J, Akoko J., Gilbert M, Vanwambeke SO (2020) Early intensification of backyard poultry systems in the tropics: a case study. Animals 14(11):2387–2396. https://doi.org/10.1017/S175173112000110X Faul F, Erdfelder E, Lang A-G, Buchner A (2007) G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39(2):175–191. https://doi.org/10.3758/BF03193146 Fox J, Weisberg S (2019) An R Companion to Applied Regression. 3rd Edition. Sage. Hortêncio MC, Costa LRM, Souza MVP, Freitas WD, Fonseca BB, Silva MJB, Cossi MVC (2022) Time series evaluation of condemnation at poultry slaughterhouses enable to export in Southeastern Brazil (2009–2019): a tool for optimizing resources in the poultry production chain. BMC Vet Res 18:427. https://doi.org/10.1186/s12917-022-03521-z Hu JY, Cheng HW (2021) Warm perches: a novel approach for reducing cold stress effect on production, plasma hormones, and immunity in laying hens. Poult Sci 100(8):101294. https://doi.org/10.1016/j.psj.2021.101294 Kanabata BT, Souza FL, Biz G, Pescim RR, Soares AL (2023) Relationship between pre-slaughter factors and major causes of carcass condemnation in a broiler slaughterhouse under federal inspection. Braz J Poult Sci 25:1–6. https://doi.org/10.1590/1806-9061-2022-1669 Kang S, Kim DH, Lee S, Lee T, Lee KW, Chang HH, Moon B, Ayasan T, Chi YH (2020) An acute, rather than progressive, increase in temperature-humidity index has severe effects on mortality in laying hens. Front Vet Sci 7:568093. https://doi.org/10.3389/fvets.2020.568093 Karlsson L, Keeling L, Röös E (2025) What is a better chicken? Exploring trade-offs between animal warfare and greenhouse gas emissions in higher-welfare broiler systems. Sustain Prod Consump 55:203–216. https://doi.org/10.1016/j.spc.2025.02.015 Kpomasse CC, Oke OE, Houndonougbo FM, Tona K (2021) Broiler production challenges in the tropics: A review. Vet Med Sci 7(3):831–842. https://doi.org/10.1002/vms3.435 Kumar M, Ratwan P, Dahiya SP, Nehra AK (2021) Climate change and heat stress: impact on production, reproduction and growth performance of poultry and its mitigation using genetic strategies. J Therm Biol 97:102867. https://doi.org/10.1016/j.jtherbio.2021.102867 Liu L, Ren M, Ren K, Jin Y, Yan M (2020) Heat stress impacts on broiler performance: a systematic review and meta-analysis. Poult Sci 99(11):6205–6211. https://doi.org/10.1016/j.psj.2020.08.019 MAPA, 2017. Ministry of Agriculture, Livestock and Food Supply. Decree No. 9,013, of March 29, 2017. Regulamento de Inspeção Industrial e Sanitária de Produtos de Origem Animal (RIISPOA). Diário Oficial da União, Brasília, Brazil. McManus C, Lourenço-Silva J, Paim TP, Oliveira F., Giannoni-Guzmán MA (2023) Tropical Animal Health and Production: a 55-year bibliographic analysis setting the course for a globalized international reference journal. Trop Anim Health Prod 55:160. https://doi.org/10.1007/s11250-023-03577-5 Meteyake HT, Bilalissi A, Oke OE, Voemesse K, Tona K (2020) Effect of thermal manipulation during incubation and heat challenge during the early juvenile stage on production parameters of broilers reared under a tropical climate. Eur Poult Sci 84:1–16. https://doi.org/10.1399/eps.2020.318 Moreira LM, Sousa LS, Guamán CAG, Vieira MC, Santini MB, Cardoso AR, Leme FOP, Lara LJC, Araújo ICS (2024) Effects of cold stress on physiologic metabolism in the initial phase and performance of broiler rearing. J Therm Biol 119:103773. https://doi.org/10.1016/j.jtherbio.2023.103773 Mottet A, Tempio G (2017) Global poultry production: current state and future outlook and challenges. Worlds Poult Sci J 73(2):245–256. https://doi.org/10.1017/S0043933917000071 Muchon JL, Garcia RG, Gandra ERS, Assunção ASA, Komiyama CM, Caldara FR, Nääs IA, Santos RA (2019) Origin of broiler carcass condemnations. Rev Bras Zootec 48:e20180249. https://doi.org/10.1590/rbz4820180249 Nawab A, Ibtisham F, Li G, Kieser B, Wu J, Liu W, Zhao Y, Nawab Y, Li K, Xiao M, An L (2018) Heat stress in poultry production: Mitigation strategies to overcome the future challenges facing the global poultry industry. J Therm Biol 78:131–139. https://doi.org/10.1016/j.jtherbio.2018.08.010 Nawaz AH, Amoah K, Leng QY, Zheng JH, Zhang WL, Zhang L (2021) Poultry response to heat stress: Its physiological, metabolic, and genetic implications on meat production and quality including strategies to improve broiler production in a warming world. Front Vet Sci 8:699081. https://doi.org/10.3389/fvets.2021.699081 Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Köppen-Geiger climate classification. Hydrol Earth Syst Sci 11(5):1633–1644. https://doi.org/10.5194/hess-11-1633-2007 Pirompud P, Sivapirunthep P, Punyapornwithaya V, Chaosap C (2023) Preslaughter handling factors affecting dead on arrival, condemnations, and bruising in broiler chickens raised without an antibiotic program. Poult Sci 102(8):102828. https://doi.org/10.1016/j.psj.2023.102828 Pirompud P, Sivapirunthep P, Punyapornwithaya V, Chaosap C (2024) Machine learning predictive modeling for condemnation risk assessment in antibiotic-free raised broilers. Poult Sci 103(12):104270. https://doi.org/10.1016/j.psj.2024.104270 R Core Team (2024) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. https://www.R-project.org/ Rouger A, Tresse O, Zagorec M (2017) Bacterial contaminants of poultry meat: sources, species, and dynamics. Microorganisms 5:50. https://doi.org/10.3390/microorganisms5030050 Salines M, Allain V, Roul H, Magras C, Le Bouquin S (2017) Rates of and reasons for condemnation of poultry carcases: harmonised methodology at the slaughterhouse. Vet Rec 180(21):516. https://doi.org/10.1136/vr.104000 Steadman RG (1979) The assessment of sultriness. Part I: A temperature-humidity index based on human physiology and clothing science. J Appl Meteorol 18(7):861–873. https://doi.org/10.1175/1520-0450(1979)018%3C0861:TAOSPI%3E2.0.CO;2 Thobe P, Chibanda C, Almadani MI, Koch S (2025) Chicken meat production in global comparison – production systems and economics. Stud Agric Econ 127:220–227. https://doi.org/10.7896/j.3313 Venables WN, Ripley BD (2022) Modern Applied Statistics with S. 4th ed. Springer, New York. ISBN: 0-387-95457-0 Wei T, Simko V (2024) R package ‘corrplot’: Visualization of a correlation matrix (version 0.95). Available from https://github.com/taiyun/corrplot Wideman RF, Rhoads DD, Erf GF, Anthony NB (2013) Pulmonary arterial hypertension (ascites syndrome) in broilers: A review. Poult Sci 92(1):64–83. https://doi.org/10.3382/ps.2012-02745 Zar JH (2010) Biostatistical Analysis, 5th Edition. Prentice Hall. Zeileis A, Hothorn T (2022) Diagnostic checking in regression relationships. R News 2(3):7–10 Zhang Y, Politis, DN (2022) Ridge regression revisited: debiasing, thresholding and bootstrap. Ann Stat 50(3):1401–1422. https://doi.org/10.1214/21-AOS2156 Supplementary Files SupplementaryFile.docx Highlights.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 13 Mar, 2026 Reviewers invited by journal 11 Mar, 2026 Editor assigned by journal 04 Mar, 2026 First submitted to journal 02 Mar, 2026 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-9003534","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":604446018,"identity":"643340aa-46d6-430c-b2bf-3e91bf4ec4e9","order_by":0,"name":"Alessandro Silva Lopes","email":"","orcid":"","institution":"MAPA: Ministerio da Agricultura Pecuaria e Abastecimento","correspondingAuthor":false,"prefix":"","firstName":"Alessandro","middleName":"Silva","lastName":"Lopes","suffix":""},{"id":604446019,"identity":"129623bc-4d55-4e48-8a2d-2518299711f6","order_by":1,"name":"Guilherme Francisco Sobierai Batista","email":"","orcid":"","institution":"Santa Catarina State University: Universidade do Estado de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Guilherme","middleName":"Francisco Sobierai","lastName":"Batista","suffix":""},{"id":604446023,"identity":"f9659528-9e65-4db7-af36-38aa999e02a0","order_by":2,"name":"Denise Ortigosa Stolf","email":"","orcid":"","institution":"Unidade Central de Educação Faem Faculdade","correspondingAuthor":false,"prefix":"","firstName":"Denise","middleName":"Ortigosa","lastName":"Stolf","suffix":""},{"id":604446024,"identity":"f1cf0b97-a85b-4434-8c7c-8534f23d9efa","order_by":3,"name":"Marcel Manente Boiago","email":"","orcid":"","institution":"Santa Catarina State University: Universidade do Estado de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Marcel","middleName":"Manente","lastName":"Boiago","suffix":""},{"id":604446025,"identity":"baa8c4f8-62ab-484c-88a2-3e9e934432eb","order_by":4,"name":"Alessandro Cazonatto Galvão","email":"","orcid":"","institution":"Santa Catarina State University: Universidade do Estado de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Alessandro","middleName":"Cazonatto","lastName":"Galvão","suffix":""},{"id":604446026,"identity":"cddd2826-e339-4ce7-8032-ed2ed89a3612","order_by":5,"name":"Weber Robazza","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYFACHghlACISKhgYG4A0MwlazpCshbGNCC0Gx3sPPq5guCdnzn788YeH8w7L9vMffsBcuAePljPnkg3PMBQbW/YkJBgkbjtsPHNGmgHzjGe4tZjdyDGTbGBISNxwIOFAAlBL4oYbPAzMPAfwaLn/xvwnWMv5hw0HEuccTtx//gwBLTd4zBjBWm4kMzYkNgBtYcjBr8X+TF6yZINBgrHljGfMDAnH0o1n3EgzODwDjxbJ9rMHPzZUJMiZ86c//vijxlq2v//ww8cFeLRAgAEan6CGUTAKRsEoGAX4AQBfUVdGwg66OwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-7995-8777","institution":"Santa Catarina State University: Universidade do Estado de Santa Catarina","correspondingAuthor":true,"prefix":"","firstName":"Weber","middleName":"","lastName":"Robazza","suffix":""}],"badges":[],"createdAt":"2026-03-01 19:29:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9003534/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9003534/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104653733,"identity":"57aa0024-c94e-47d2-a059-5e0595b671d1","added_by":"auto","created_at":"2026-03-15 09:29:35","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40172,"visible":true,"origin":"","legend":"\u003cp\u003eRidgeline plot showing the evolution of the condemnation rate of broiler carcases from 2021 to 2023.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9003534/v1/4b20c2e9a101e4e119c6777f.jpg"},{"id":104653734,"identity":"b834c3f8-3176-4a1e-8cc0-ef073d40eea8","added_by":"auto","created_at":"2026-03-15 09:29:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75386,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of condemnation causes in Santa Catarina relative to total animals slaughtered in poultry processing (a) 2021, (b) 2022, and (c) 2023.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9003534/v1/53bf77793470e38bb4d78c7c.jpg"},{"id":104782083,"identity":"1d31e5df-cb34-44d3-ba78-5e8446fbc74b","added_by":"auto","created_at":"2026-03-17 07:56:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":118906,"visible":true,"origin":"","legend":"\u003cp\u003eTime series plots of mean temperature (°C) and mean humidity (%) in Chapecó from 2021 to 2023.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9003534/v1/cf22763b61ec053c78b95cce.jpg"},{"id":104783105,"identity":"b6186005-22ce-4113-9f2b-980c5ab6e541","added_by":"auto","created_at":"2026-03-17 07:58:14","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":106404,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation heatmap between poultry condemnation causes and climatic variables. Each cell displays the Spearman rank correlation coefficient and its corresponding p-value. P-values \u0026lt; 0.05 indicate statistically significant correlation.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9003534/v1/21705cf09cc7716562682fde.jpg"},{"id":104784929,"identity":"e0df30ef-6613-4403-a04f-5aada2f925e5","added_by":"auto","created_at":"2026-03-17 08:09:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1208029,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9003534/v1/9a5b8115-b101-4b01-9110-0f0bb58c90a2.pdf"},{"id":104653737,"identity":"e5957f63-44e7-412d-a22d-71c9dda3f69c","added_by":"auto","created_at":"2026-03-15 09:29:35","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":919955,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.docx","url":"https://assets-eu.researchsquare.com/files/rs-9003534/v1/06740103179ef036c941798a.docx"},{"id":104653738,"identity":"6f6e0e56-b446-4c1e-b74a-21431733bac4","added_by":"auto","created_at":"2026-03-15 09:29:35","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":14009,"visible":true,"origin":"","legend":"","description":"","filename":"Highlights.docx","url":"https://assets-eu.researchsquare.com/files/rs-9003534/v1/2866b79a6e17e9e9f752e9a5.docx"}],"financialInterests":"","formattedTitle":"Environmental Drivers of Broiler Carcass Condemnation in Humid Subtropical Regions: A Predictive Model Incorporating Lagged Climatic Effects","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe global intensification of the poultry industry has increasingly centered on tropical and subtropical regions, which now account for a significant portion of the world\u0026rsquo;s animal protein supply (Alvares et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Chaiban et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In these agro-ecological zones, particularly those characterized by humid subtropical climates (K\u0026ouml;ppen-Geiger Cfa and Cfb), intensive broiler production faces unique environmental challenges (Liu et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). High thermal amplitude, seasonal surges in precipitation, and sustained relative humidity above 70% are primary stressors that mediate host-pathogen interactions and metabolic homeostasis (Mottet and Tempio \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe efficiency and sustainability of these systems are measured by their ability to deliver wholesome carcases. Any deviation from clinical health or processing standards results in carcass condemnation, the total or partial rejection of meat during sanitary inspection. Beyond the immediate economic impact, which can represent substantial annual losses for individual processing facilities (Hort\u0026ecirc;ncio et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), condemnations represent a critical \u0026ldquo;leakage\u0026rdquo; in the food value chain (Buzdugan et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This food waste directly undermines the United Nations\u0026rsquo; Sustainable Development Goals (SDGs), specifically Zero Hunger (SDG 2) and Responsible Consumption and Production (SDG 12), while signaling compromised animal welfare on the farm (Karlsson et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn humid subtropical belts, encompassing production hubs in Southern Brazil, the Southeastern United States, Southern China, and Eastern Australia, carcass rejections often follow cyclical patterns (Meteyake et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kpomasse et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Pathologies such as ascites syndrome are strongly linked to environmental stressors during specific seasonal windows (Hu and Cheng \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), whereas inflammatory lesions, cellulitis, and arthritis are mediated by litter moisture and ambient humidity (Wideman et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Pirompud et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the biological impact of environmental stressors is rarely instantaneous. Delayed physiological responses or the gradual deterioration of litter quality suggest that climatic conditions weeks or months prior to slaughter may be more predictive of condemnation rates than concurrent weather on the day of processing (Kang et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Nawaz et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the global significance of these subtropical belts, comprehensive models quantifying lagged meteorological effects on condemnation causes remain scarce. Most existing literature focuses on single-cause analyses or concurrent climatic effects, failing to capture the complex temporal dynamics of intensive avian health in these sensitive environments (Hort\u0026ecirc;ncio et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Carvalho et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Pirompud et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Santa Catarina, Brazil, serves as an ideal global sentinel for this research due to its status as a premier regional poultry exporter operating high-density intensive systems under representative Cfa/Cfb climates. Therefore, quantifying the environmental drivers of poultry health in this region provides a generalizable blueprint for intensive systems across the humid subtropical belt (Liu et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aims to quantify the effects of temperature, precipitation, humidity, and heat index, with time lags of 1 to 3 months, on the condemnation rates for 12 distinct causes in federally inspected broiler slaughterhouses between 2021 and 2023. By utilizing advanced statistical approaches, including Generalized Linear Models with a quasibinomial distribution, this research seeks to establish a predictive environmental framework to mitigate economic losses and enhance animal welfare in subtropical agro-ecologies.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Site and Representative Subtropical Context\u003c/h2\u003e \u003cp\u003eThe study was conducted using data from broiler production systems in the West region of Santa Catarina, Southern Brazil. This region is a global sentinel for intensive poultry production, characterized by a humid subtropical climate, K\u0026ouml;ppen-Geiger types Cfa and Cfb (Alvares et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This agro-ecological zone is defined by well-distributed rainfall throughout the year and pronounced thermal amplitude, mirroring intensive poultry hubs in the Southeastern United States, Southern China, and Eastern Australia. The municipality of Chapec\u0026oacute; serves as the primary processing hub for this region, which accounts for approximately 79.4% of the state\u0026rsquo;s poultry output.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Carcass Condemnation Data and Sanitary Inspection\u003c/h2\u003e \u003cp\u003eData on carcass condemnations were retrieved from the management information system of the Federal Inspection Service (SIF), under Brazil\u0026rsquo;s Ministry of Agriculture, Livestock, and Food Supply (MAPA), covering the period from February 2021 to December 2023 (MAPA \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The records were filtered for broilers, excluding animals that died during transport or pre-slaughter phases. Twelve primary condemnation causes were analyzed: gastrointestinal contamination (GC), skin lesions (SL), arthritis (AR), airsacculitis (AI), cellulitis (CE), processing failures (PF), traumatic lesions (TL), ascites (AS), visual defects (VD), septicaemia (SE), cachexia (CA), and inflammatory lesions (IL) (Salines et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Partial and total condemnations were merged into a single variable for each cause to standardize the quantitative analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Environmental Monitoring and Climate Indices\u003c/h2\u003e \u003cp\u003eMeteorological data were obtained from the Chapec\u0026oacute; climate station, maintained by the National Institute of Meteorology (INMET). The variables included total monthly precipitation (mm), mean monthly temperature (\u0026deg;C), and mean relative humidity (%). To quantify the combined effect of temperature and moisture, the Heat Index (HI) was calculated using Eq.\u0026nbsp;1, where \u0026#119879; is the mean monthly temperature (\u0026deg;F), and \u0026#119877;\u0026#119867; is the mean monthly relative humidity (%) (Steadman \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1979\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAr0AAADPCAYAAAD4UWk7AAAQAElEQVR4AezdB5wlRdUF8GpExQhmVFAQDHwmMGdBUTEhKipmjJjBgGIGs2JAMUcQc0RREQNiREUlB5GMgJJzDt/+G2rt7X1v5s3OvNmZ2cOP2n5ddau66lTVvaduVfesdFX+CwJBIAgEgSAQBIJAEAgCCxyBlUr+CwJBIAis8AgEgCAQBIJAEFjoCIT0LvQeTvuCQBAIAkEgCASBIDAKAgtcJqR3gXdwmhcEgkAQCAJBIAgEgSBQSkhvRkEQCAKjIBCZIBAEgkAQCALzGoGQ3nndfal8EAgCQSAIBIEgMHsI5EnzGYGQ3vnce6l7EAgCQSAIBIEgEASCwEgIhPSOBFOEgsDkCEQiCASBIBAEgkAQmLsIhPTO3b5JzYJAEAgCQSAIzDcE5mR9r7jiinLWWWeVE088sRx99NHlpJNOKhdffPG063rhhReWU045pRxzzDHl2GOPLeeee+60y0wB40MgpHd82KbkIBAEgkAQCAJBYA4gcNhhh5WXvvSl5Z3vfGd5+9vfXp773OeWD37wg9OumbJe//rXl+23375sscUW5c1vfnM5/fTTp11uChgPAiG948E1pQ5CIHFBIAgEgSAQBJYDAjyx559/fnnPe95TvvSlL5V73vOe5UMf+tC0a/Ktb32rvPzlLy+f+9znyrvf/e7y7W9/u/zud7+bdrkpYDwIhPSOB9eUGgSCQBCY0wggAA972MPK4YcfPqfruRArlzbNPgKPfvSjyze/+c1ym9vcplzvetcrV111Vbn3ve897Yr8/e9/Lw9+8IPbMu985zuXlVZaqf097YJTwFgQWCbS+5///Kc84xnPKCuvvHIbnvKUp7TnZNTw5JNPLre61a3ajr/+9a9fXve614leHB7zmMe0eeR9wAMesDh+Pv0444wzyrOe9axyrWtda6lq29bYZZddykte8pJy97vfvay77rplvfXWa1eAp5566lLyNeLyyy8vBx98cHnXu95VHve4x5W73vWuZY011ijw2n333Zc4e7TPPvu0aU3TlKZZOmyyySalPuuyyy4rf/jDH8rzn//88n//93/lTne6U1v+9773vSXKrPUYx9W5qV//+tftto+6wWSttdYqm222WfnjH/9YnLWa6Llnn312+fjHP17ue9/7ljve8Y7lfve7X/nKV75SLrjggqHZtPu9731vq3x+8IMfLCF35ZVXluOPP77ssMMO5YEPfGDbRxtssEG7PXXmmWcultUnq666allttdXKOuus04amacoNb3jDth7irnOd65QHPehB5YQTTlicb9w/nBnbc8892zHypz/9aeDjLrnkkvLDH/6wPOQhDyl3uMMdWtn3ve99BdEZmKETyRg4p/bXv/61POEJTyhve9vbOqmDf1500UXlmc98ZoHHoYceuoSQ+cLYbLnllq2RUZ973OMe5R3veEfp4l0zaRvcm6Ypa665Zov12muv3bZFG7S/yrrC/vGPf/xivUIfVRltuMUtbtHOkxvf+Mbli1/8oixjD8b0vvvuW5761KcWdb/LXe7S6oTTTjttwmer99e//vXyspe9rNzrXvdq226+vOUtb1lijCn/H//4R+u1etrTntb27+1vf/uy/vrrt4Zd/9UHnXPOOe2zm6ZpcWiaq683utGNyu9///tWP5E13m92s5sVOOkj47sacPPOvf6l13jN5BlnOOigg8ptb3vbts43velNWyzUw1y1nexcZun9t/nmm5drX/va7Vggd+mll7YSBxxwQEtMtEcbXv3qVxe4tImz8I/+opN5A80Ti42//e1vQ59sDh533HGtJ/LhD39423Z25MlPfnLZbbfdSrd/nSc1rl/wghcU40w/0ZEf/vCHl2qj+U920003bWX182Mf+9iy0047lf/+979ltv4z1uDx6U9/uh2zw8aT+mqHvjSPkFS2i36rdaXr6YCjjjqqDAp1ziG6qy3S5QceeGB54xvfWI488sjy1a9+tRbTXtnJVVZZpay11lot5je4wQ1anVbv6aVb3vKWhY5qMyz6Z/XVV2/5Djv3qU99qrUT85XbLGrOgv9/mUivTqZ0KEgD0aBknKB161vfup2oFAtiaCtBfA2f+cxnWsJGoTOENX6+XE3WH/3oR+WXv/xlQZ769abUnBlCNig154he/OIXl4997GNlxx137IsvvneoftNNNy377bdf2XnnnQvisPfee7er0Ve84hUFaazClHXFV9k1UKbXve51y8Ybb1xMTPI//vGP260XWznKVu6jHvWoloBqA5mpBIa2W5dR8jI42uAlAttKRxxxRGuYKR0ERZ2GlUOhff7zny/f/e53y0c+8pHWK/Wc5zynID+2lQbl0y/q+IUvfGFQcvuyAcw892tf+1pRH+OSMnXmC8mWkQKlyN7//veXQw45pO2DpmkKkvGvf/2rjbOQ4Dkw7uUZJVDQv/jFLwqiOIp8lWHofvazn5Xtt9++JUXGVk3rXo1RhHe77bYrr3zlKwv8LaY++clPFnETPZexRdYYwWc/+9lLKPcy5D999I1vfKNYjPVFlGeev/Wtby2IKa8IMsO4qM8LX/jCfpay0UYbtYs0CT//+c8LrLUBoUHA9Yc2Shdud7vbtXgY84yiOYi4SbNQgpffFuD63e9xh7/85S/Fs4wPbUZk999///L0pz+9cAwMez4j/NrXvrZdMCOk2q7PEBVjvuZDULbaaqtifjtDqGwLIFi86lWvKv2FnnwM8Yte9KK2XupWgzTBSzh0C7wswH/zm9+0xhwpUg9zgB6h/y3I5RlnsDCy2EVi9Z06CGyKeWBMd8eBuuy6667tIg/u9AY9Kd5iYNttt23JMByMRwRG2rgDgrbXXnsV/Qpj/Yk03ec+9xn6aCQQMf/pT39aEEPtptM4Q8RrZ20724Js0f90gvm7ySLHh0X9Jz7xicXPOO+884rFk3FkjJiH+tm8YsOVYS4vzjCmH5xm9MVrXvOass022wxdiNNTzsuaEzAwj574xCcW494Rgtp+Y5audz53UKBDuk2hd/7973+3ZJaNrWnabpHsXC5bCUueW4TXvT5wjAERFl/zuSLn9I78xt1NbnIT0QlzEIFlIr3ddmy44YatkunGGYwGEAXL29tNs9pCJHgwkYVu2nz4TRlRRMPqzjOG2DFuCCila1vFihpxG9ZGngzKi/KxUifHK8swWcnzTIoTKFFKzSQz2Wvw7Jvf/Oatd4kckvSmN72pMFIO7ZusDAiiabFCQZCbSmBkEcSp5NEe7XLeieeGl5+HFSGhsCjpYeVZpVNSvN/yyMvbUcsclA+pQGYHGRUeFwaHAWeElKNMhpCy07dVESL4xinsjFukgqx6e644BM0CDq7iRgmMDWOk7aPIVxl1+/Of/9wuaiyqanz/yqgwFOrJECKAxgaPkbHC09HPU+8ZZeT/Los8k8h9jZ/oanFgAcXTOEjukY98ZOthRXql85TzNFko6Atx/YAsm2O8nNIQFMZOPHI9yENMzoKIZ9fvGswXu0/IW40b55UBtCCzE4Skm9vIuPGl7ubQsOc/4hGPKLvsskvZcssti/lKziIWifvJT37SLoLFwQOpseNh/NEz5hYyAxsLbnqWbA2er//7oaYbl8azXSrPVga87WSQMd6NIePK88QNCuaPuTMoTZzxoi39+klbHK754fkIBC/nNVGtx1ad7ICZzzXeVb3pPZ5B+lNcDcaB34gTnej3bAQLoI9+9KOFHbD7ZOGgnhM9G4ZIrjGP6JI1HxBm84cuqjtdbA1Hib7hybb4Yx/I//a3v5W1DUijxRNdZ5zpQ/Ww42Z73vPY7VZ4wD/qZGduQFIbRVdbLMO/jRjyj0Uw3cfBYEwNESvsgrFqgUz3m0cWLpxt3/nOd4rnycvmsS1kBwX6m1wNZNhOc9Li57hFHnVpbKzxtMOiHUA6xD19yHa7J8NDb54J7gWYGYsWYvrZToj4hLmJwDKTXgrS4Da5uk2jWHjwDIrq/e2mOz/Gk8aYIYXdtPnwmxHjgaD4B9WXQmOkupMZUUKKJlK0thopn/4K0nbnaqutVkzs+jxKG2GlsGqcvjCRGcu1Fm3NiGdcbAH28+sX+CNQ+oLsOAOFoc6u3eeoPyVNiXXju78pWit+uMBQmrHFoP3zn/8sfeNKaSFtiB4FRb4bLMh4xZCGfn0QXAqMkZLnSU96UruVyMi4t9rXl0iGe4G3aeutt/Zz7AFpY/QsACbytFHUCAtDVitlrvHwwwdBrfH9q7Fhp8JYRLT66f175TGkSHIXlyrXNE27fc7IdhfACI+8gwwE0sYQKU+9a1l1TiFCQo135ZVxjAKxcN8NdJVtcWSgGz+u3xYdxoot5m79YeCZDKTroABz/Wtu1HTkGUHp1l86uUqIqmzF2JjtPrumT3Q1vizM6SJy5gmc73//+7ttAy8wb2F7M+QfC207gfRPX8Ruz/Oe97x2XiE+/fT+PS+duYx41DR40AXGT42rV/bFETPjUb4a76pP5Om2R/y4g61088piXd1HeR5s6L2u3pdPv9Jd9Ji2iLO4twju9jc7TJd1x4d5ZRfMIoIek1eApTI9T3+L6wdeYmTRYnWfffbpJ7fHlPQ5u8TpsJRAJ8LuDjJvPnTr0RFpf+6xxx7tEbyuHjfuzXH9TEe0giP+o//ZPOLGON2jXXARZ9HuKKCrezuAcLZody+w7XZ6u1grk3fXjovFFrmEuYvAMpFeE8eqkeFC8rrNM3F4kkxEA7Sb5rdBxWB3lZj4QcHEtaXQCe1W57B7A3hQOTMRR8HwcJpovCkTTdbu8ygRRxdsRzIq3bRhvz0L2TWZeASdn0ZYqjzjb9I2TdNGeYbtct8ftP3SNFfHm7AEmqZpz8X5LSCalK/nII7iZjsg6YwqQj6RouCRZby6xFj9eQkpHmV06+7IAk+aXQaKvJtWf2t30zT1dvGV8pdG2Yk0fmsZDAiviWdaMEgX9AM5v8cdGLxKaiZ6FvLHC2Jx0JWzGDJ3zc9ufPc3DLQZxt34Yb9t2zImDBlshsnVePrB8Q7bs+Rt+9e0elV3C+eubjHGEaCmuZpE89xWeXOFvHpbHNV4V3PAm9RIL2MvbtyBHmL4HTXoPovec69/EGO/RwnOPprbvLBNs/S4rWXoW21Fjs2ppllSlgdaOfSnhRECWvO6Glvmo99w49Wj57qYGoMCmWHBVjTiSRfVduo/u2SIjrFlsdjtw0FlqQPiY/5X7MjZ+bKQgYeyxNXgSIY5qb+b5n/t1ycWyMY3bKr8uK/GOY8hsmjsWwgI7IH2DXu+xQ+izHuo3/QtHcQmKO9ud7tb0c5ufjJsMpxt/8PMIrnKcNbwltqCt71Pnr4zH+lZ5BI+Vb579SzH8+Bq0WLhXOuvr7fffvvWM6u/uvqxW0b9bZ5axNX7QVdlG6PqB4euDO6g/vREN36y37gHsm1c01kWeMaQxbW82m7u+C3ACQep6eLUu2uL9I2jexZS9K2+tcvG804+Ye4hamfSZgAAEABJREFUsEykl9I26AwSSsYKsIYvf/nLBSE2KSnRfpMNPJOxbxD6cu4pTBNt1FDJirwzHUwSxxZ84qQ76Cd7DsMCE6tHymIyeYoR0XXWyfayVa3tlokMtv6g5GxzmXj1GbwEJimCaXLWeIpRXL2f7auXS2zh6l/K0hGDYXWAO5LfN7TwMP667YKD1baVOQU/qExGUv/xcNftwSonf/3dvyIKyJWtQbj20+fKPUNG8apPn1RoN/IxU33vOW94wxva87SjzGeLEV5kuxE80c4QdgmVOgsII/1i+9E9wuJ8qyMyPC1dQy5dXyJz2lf1UL0yPsqyM8Bwkx93UB9EAsHoPqsaVIbcHOimDfvN6NrBQRSW1B9L50CInHf28lx3kWyBK78FIVxssVsUMtb08dIllYJw8IDZVq71HiQ3KA5JsM1rPjlSYZElIBzmrToM6vd+WcYXLBEtuzLGLUKnT41jx5OQ8m4+O0PSEFzPqUEeeenT2RoH6sVmuLJNCDBb5iVFuh2hNV+l98NDH/rQYgeJV5EHlcPF+HfcjdPFWX36r+ajy77//e8X+tRZfPPBeeju7iIy6vgBXepogfnn6Jg5qT/MZfailtm/stueYTHKe/2rX/2q/R6tM9aIpLL0fT/fstxb6LGd8nbb4J7+NX8sAtyPGswLdpWtdCyILtcng/KzkRZWq6yySvtC6SAZceyCOcIzr28FZLnrYSeXMHcQWCbSy3PJkNiy5uXqBvGICEXVn0CUoLNIBjFP3WQwIIq2DUYNw44cTPacydKtyk1ok2bDDTecTHyJdCSZZ4IxGoUYNE3Tfv2C8uAZdo6TAUEQlyj4mhsK3iQz+dTvmuj24nmMGwPgDBQDqu9M+GrsGMNWeJb+UV9ntayGvZyCAM3Eo7WNUXDlYeoahG75jKQjOcYmXHkLLDQYIOOsaZoyCBOeROSL0eyWt6L+RkYc9bHAsG07Cg4WL14ocuzC4sNiDlHr5jU+GBsEh6FnwJ3TZaxh7ygFA93Nw0AiFc40dnWR3xZNyCfSi/x1882H37aL7WZ4+WgiQ2p8IjzmExLDO1rbB3d6wIJQnyGC9JKjTzz0CHqVrddKeh35qXGjXuHMo+sdBfrGM5A0XmT91z2fO1GZ+g4p9BJjHQfmNmeK8YAYNs3/vLnGpK13toXTRf/XQH8i8d3FwETPnok045IDSFnO1/q6wmc/+9nCqaFe+oNNlN4PdkEsWvWd8WuxAAv6SkCyunnMJ/ha7JtfFui86exCV85uj7ItZJD/pmla4qpMwfzryvd/c6rAHoF2vhaBt9tjfOpz9ejnmSv37KE+gL/dCC8EwnZQ/Yxb/ccOw36QjDi7BuxGN+AKsJCeMAsITPERy0R6kTjeGOf+fKGhGyhbK0IvSjXN/xSSejmHY9vCxEQ6xM1msGI2aUcJtj20k1cG8UR4HKjv19eK04oZaeqnIVW8vM7AOd/HGPRl+vdWlvCk3BkNHgHl85KpS1/eitTq23aYhUY/nTLiHXDQX59QtDxiZCk9136eem/i9rHSJnj04xm2YQq8ludqUURZ2kpjoGdqHPAEOisJs74i4xFgbG1nNU1TLFx4QRAl57oYQgTAkRx9BEt17QakgiFBrLrxk/1mIPpYGUdeGkEA+2mTlTdX0o05njikjGHu1ssiAqG11d6Nh7OxjXiZEwwy76VFcpVj2G218p7wSH7gAx9ov3KBsJgLDFeVrVcGSvDSnvK7gQfMeGekq/ywqxc8+/0x7N6z6MBhZc1EPHJqsQwvY9aCbVC55h05Cz39gSx15YxpRNNYR3jI8aJb/OlDW9Jdeb95RWFOB7ifavBMc5xXzaJb//Cy2ZoetSz5kDAEnf7ioTRvOFvoU+3olqXO9LTndseA38aNsSCtm2fQby/BDuv3QfE86IPK0S/GszzqwFvdNFcfz9Gf7KGxPiivo1TmELJvMSM/7yqHBe8kPWye1bzmYJ1fPK8WGd5NcL66yvD+coyoE48kPUSOjjIXzTdOgyo/7KoPvQCmj30lhufZDky/P4blnw/x5rZFgIX2fKhv6jg6AlMmvYiXc6BWmgxT/1HOliK9/XM45KzCTU7kwv1kAaFDNkYNFN5EZfrkFeU7SnBsg8eAEqDUECREmJdJ8Ha2ZzEk3kblfXAvIPYUk1W9T7NQRlNdAVMovAHePKWsYa4uyu8G9bLSdmbMSr+b5rc4K36eGxOZh5VHnCcNifAccoOCrcI+Vryz3sLvxyP3yMWgcmocI8pg2R5DvpHumjbsaqxQPhR2VwaRpbzhL563273P7+gfwTY4zNSZkq99QDlbsDEKPEC83lb9SK1FR9/QI2Vw9hwrf9dRA0Pfx8rY4CHlweqnjVruMLmmaQpvTtM0xZZyVw4WMECAuvFT/Q0neJhvPB2wFrTL2NcHxv2w/kW8vHiDnDkjL9Q6yK8/1JF3lh5hVO0QCVWuXpEi5MiLS7xXNb6UUowRhM64hEk3bdBvn/nq98ewe3Oe925QOXYK6MA+oYE/ebj06yq+BjpWXWzJW6h5oVK/1fTuVZkIkAU6D1NXD3Xl+r+bpmm/7ds0TXuUoZuOTOlf9TD/ummj/tYvSKjFMJKkz3mg6aBRyjC2eLgtiuldZdh+h4MdHXO9Xw7PsDr3F6ZsFf1pLBkn/Xz9ezsLw/p9UPwwDzzd2jRN+9k3Oqdc81/TNO0Xj4xL4/2a6MUX49YcsCBBUmEnURleXtQONskOpPh+oMNs3dsp5Qio6c7h8l6yR5WAqyNniK9h+JIKJ06VH3ZF5h3bYJe03UKLrRjUlmFlTBYPG7aLnHHgWoMxb7eYTI2b6SsniLFqcTXTZae85YvAlEkvhUiZGwxW3t3q216yNWlAOnfTTTOREWITcpAnrStbf5vUFPqogaKueWfqyoggy5RmNzir5hniKCgrd/eUsfNNvAWUsxWweO2vRNn9qIEBnUjWVg1F7iD9RHI1Tf1sucGWt6rGj/vqZQffZURmeO/qlhEyrj7Dno/UGnOIZ5WhXGtfa7t4nkN90Q2ew2AgD+IZELKDAgXHg80g2InoyiDr0ufDqr9prj4eY/6pd7cdjAfSYOu3Gz/V33ZzLCJg2g08R7yRcBSPEA8rmx4g20+3wIU1El31C8LjXv378saz4zLGVd8IWlQ0TVPkVed+3nHdexbSa8x3n0E3uldX7fd7UFBvi0g7Ij41R8aYt9vjdw0Iim1V+oenF3mR5rkIoHT3CLGzoRYr7mtABpHTvo4h58gDnWa8VPlRr/pEG5wb1SfqbTvZGU06h1dxsrLoBeTKnLNIIG9eWixIo7/E1QAfOHh23xmDQMtjwbos7anPmOqVdxm2dL86dPOzlUgj+9KN95u8PvCbk8i1G2DavR/0G0FGaLtpxoX+ltaNJzeoHl2Z+ptO4XU35+xA2uE0z3mh7ezAv8pO50pvm/fqpt7dsrwPwHtOx3XjZ+o3Uo30wl7bZqrc5VdOntxFYMqkl4cQSbFdaGB2C3M+j/JhZHgpu2k8dVb+CLHQTRv220qVt3TUwIM5rKzZikfObBdRvJXweraPgPNU+C3wzjpfhJC5p8SRQhPafQ1W+wwkg9bHm2FhUJz9HeZ1quXUq+dYpfMe8QbU+HFeKREvrvHoIUtVaRtLjCGSVJ9ft/EYKXG8NuSNOUZCHO+sdF+1GLXd8g0LSHV9WchCBd5dWc9jqHmou/Fz9bexwkPX9fLoA1um8OKpV3dvgcPbB+AZM3EzHRhZhtE47xp+hgzuvL08V/W5FsYWRI7dMHjieXzI0C/uu0GZ4rWrkuSaXj3Doy4Ia77pXuk3+CMBPGu1PKTMb8d6XAX42w1A9t0L5giDb1fEvWD82VKGp3tBf9oCd2wLIRQnOAJgGxy+7uX10hp94V5AiC3OlUd/iKsB2fQJOF68GjeVqwWpbXXHjBwrUg4C7egRAm4HBqmeqEx40FUWoV055SCE5n83Hs50JQ+mBUc3TXvoX8eJZpP00iN2PYx1+qvWiY2wADJO7GbY0dRfxoJ6yscxZPHETtR8rna92FHjg14UZ4fF4sccdy9YYNCXvOTuBfPAQtO46cqSg6fdlz4hlq8Gz/ZynTnqKISyYc0phQ84hqPfqvx0r8Y/LBylqmWpq3HLMw2DGj+TV/3j6Ilxa6dhJstOWcsfgSmTXgrVxERYuqs6g9E5SU2iULuTyj0DbHWLFHfTyM+3QBnb5lJv3hLXGpxxQuJ4YCkCxligvCn8Kkc52LqshtlEQ2C9cMKTTo4xt9Vmu915w0oCpAlW3K6+2tBPE98NSI0tU9vqvKe8SH2S0JWfyd+MLi83Qm+HAB4CpYVsdp9l2xhJUl/xjpg4d+ZFPLjavjSWEFHHFsgMC0gHo16N/yA5RwAsNmDtxSl16soZr7YFEXYEq5u2vH4be7Y3PZ8Bc+0G2Dorq84ILQMIU3hYQPKWkTcf4a195rO4GqSZ6/AzHhGNmjboCmNHTKT57VoDr6+tbc8Sp2+RNQthnyzjDROvTxGjpmmW+MQeEmwB7DgKMka2Blv6+oVOMTZqPBJkzLlHKlxnK5hX8EfWzV/6Asmx8EMMzIFaF5g4goFQiOORNU/J8gjrS8FLWwwxGYHesa2M0Dmzb1FATuBh7fcB3eNsrDGhry02jQneur43y1v5CCSd5FlTCcaaIw3IgvpZgMlPP2mDZ+pDBF4fSesHbTMmkcU+SUXQ5XOGn0dUXnPU0TnEzW/jQXwNdDJ8Z3sceD6CzwHENpoH5hOC61viju1YGKgzUmwsmAPa7BgDkspRwi7oTzaDowTR9AKZceYZjvd4d8PYYZP1sd1JNln/khG84GZcOronHU7muQWpuvHWIplk+8E487UM/Ydkc+hUgkxnchaYxxbUvKT9/IPu6S7z1jjTtr6M89d2j7SLrTS2LAiNX18CGdU73S93snv8hu5TL3hOJp/0+YXAlEgv4+d8KC8MssBjWJvLWFm9mwBWYghOTTOhTVyK2QRXRk2bb1cEnjHVVlvrDI7t2NoOZ5t8ggtZowRqQDSs6qscQ+6ekRLnyoDzbFJoDJ4te7+dw5VOrgbPZxycjYVrjR901VeII1Ki7oyf5w+SHUccg0sBM4AVD1d1QGa621QwJVeVL88EDHgWKGoeLeMJJlbiw+rrBRrtVpajJgxDX5YBsC1MgTNCnt2XMW7l11e+E0vh92Vm655nliFUX4ZFfeFgrFjEMGDqwmg6fsP7g8zziqi3c7ZIAxnBzoEy9AGcxZmfXqK0UyGvXRsG0XN52cj0AzLhWYyEsc/zo37kmqYpzpsbywymulp4yQNPho2cYBFjKxtZRM4RL/FIg+frb4tCBEe8v+qFNGsDQu9evLFmLsFD/ZHKQUcjyI4r2HViqI1zuDkzzvtpoap/6nPVHWa2UsVpg3vbt3CQX+DBpHfJCLx9iKT8PH5kaqAr6J/6HF5nGPAs6n+km9fZmNDXylGm4FynxZ9nISVdHcwfaeMAABAASURBVC99smBOe1fAXGULuvJN0xSOAOSOntOv3fT627jQn/oOIVP3miafYwOILA8gUkIX7rbbbsWz6Vl/Ua7Km9d0gbLkceyjps3GVT/CVLvNSR5c9lGdjAnY6yc7HvqyYiKf+tJP5pOjGca+qwWBa9M0bRMsctghLz46uuRrKnQqsqjMVmjRP+a4eUVnsM/GgXmOeBp35mXTXF3mIvEl/kewjSP2TT71rgJN0xQ6hFff+NIHNW3QVf0ttOh1tku/IdR0g/6qedQXaUf88Qt6DPlGSOmCKjcD18VFsOXmhLmCXPNsL07MjwWBwJRIrwnF21ADI1VR4MHgfZJGWVpV1jQTi6GSJvAA1LT5duXBMBEQKm1h2BiZ2g6GRPywUOV4gBAxxkEco+f8Hg8xgyQ/BWP1zaiR6QaKn0eGQujGD/ptW56hccYVaRwkM2ocxeec3ajy5Hi5tWdQsKq29UpOIMPIdZUahcvDwdNnjPGUGIvkhwVHHyh25TE6jERflvK3CCCLbPXT3fOwK6MGngfx0wkMBOMwVU+FfDCodeleeUCQpG69kE0GhhzveJdgkmMQpTHAlLw4hgbpEd8P5jCZfrBA6c4J5Bpxq3J+G6fqoEwElIH2BYEq4yqfdAHxQRTEC44E2J53lhCJFGe+kK3BeVHxiIOFdY23RczISpvNYN7RD+pBJ9q+7j9fmu3iOj7hIm5YaJqrSYn2aNcwOZ6/OqaNMx44pIQ85wVywZvYNFeXV+tlXJKpoUsgq8xkV8ctkMxhco4ZIGn6aZCM+Vif72qbu8rxcoozD5BIhBG5NsfFC+Z0lXe8QFwNs3Wkqz7f1cLb/DTu1UP9zMXqKdU/dmSkIXbyCPDhrDDvpPFuG9cIsvQa6Er211znRfccz0Mim2bJ/pWHXrCboEyBl5astGHBAtkxHGN6mAyibrFZx90wOfZAHT27H/RXP5/xZEeUrEUQPPsyM3XPlntODXZcZqrslDM3EJgS6Z0bVU4tlicCiAbPwvKsw6w9e0wPcryEMXNmb0yPSLFBIAgEgSAQBIJAD4GQ3h4guQ0CQSAIBIEgEAT+h0B+BYGFgkBI70LpybQjCASBIBAEgkAQCAJBYCgCIb1DoUnC5AhEIggEgSAQBIJAEAgC8wOBkN750U+pZRAIAkEgCMxVBFKvIBAE5gUCIb3zoptSySAQBIJAEAgCQSAIBIHpIBDSOx30Js8biSAQBIJAEAgCQSAIBIE5gEBI7xzohFQhCASBILCwEUjrgkAQCALLH4GQ3uXfB6lBEAgCQSAIBIEgEASCwJgRWO6kd8ztS/FBIAgEgSAQBIJAEAgCQaCE9GYQBIEgEASWPwKpQRAIAkEgCIwZgZDeMQOc4oNAEAgCQSAIBIEgEARGQWC8MiG948U3pQeBIBAEgkAQCAJBIAjMAQRCeudAJ6QKQSAITI5AJIJAEAgCQSAITAeBkN7poJe8QSAIBIEgEASCQBCYPQTypGkgENI7DfCSNQgEgSAQBIJAEAgCQWB+IBDSOz/6KbUMApMjEIkgEASCQBAIAkFgKAIhvUOhSUIQCAJBIAgEgSAw3xBIfYPAMARCeochk/ggEASCQBAIAkEgCASBBYNASO+C6co0ZHIEIhEEgkAQCAJBIAisqAiE9K6oPZ92B4EgEASCwIqJQFodBFZQBEJ6V9COT7ODQBAIAkEgCASBILAiIRDSuyL19uRtjUQQCAJBIAgEgSAQBBYkAiG9C7Jb06ggEASCQBBYdgSSMwgEgYWIQEjvQuzVtCkIBIEgEASCQBAIAkFgCQRCepeAY/KbSASBIBAEgkAQCAJBIAjMPwRCeudfn6XGQSAIBIHljUCeHwSCQBCYdwiE9M67LkuFg8DECFx55ZXl3//+d9l9993Lxz72sfLZz3627L///uXyyy+fOOOYUi+55JJy4IEHll122aXstNNO5etf/3o55ZRTxvS0FDvXETj66KPLD3/4w/LJT36yfOYznyn77bfftMam8X7yySeXPfbYox1fn/70p9syL7300rkOReoXBCZF4L///W/ZddddW50+qfACF4DFXnvt1eoO+uOPf/zjlFs886R3ylVIhiAQBGYSAYrhPe95T/nFL35R1l577XLwwQeX1772teW4446byceMXNZBBx1Uttlmm3LaaaeVm970pi35pbDOPffckcuI4MJB4N3vfndLUG91q1uVI488srz61a8uf/jDH5a5gWeddVb50Ic+VH784x+XtdZaqxx11FHteD/88MOXucxkDAJzBYEPfvCDZfvtt2/H9Vyp0/Kqx6te9arWiXOjG92o/Otf/yqvfOUr2wXuVOoT0jsVtCIbBOYBAhdddFG58Y1v3BLNzTbbrLz0pS8t55xzzpSVw0w1FSm5xz3uUV7xileU5zznOWWLLbYoP/vZzwpyPlPPmIvlpE6DEbDjYCxsvvnmhUH/5z//WaazILOTsMoqq7QG0Hh/+ctfXi677LLy5z//uVx11VWDK5HYIDAPEPjpT39a9t1333LHO95xHtR2/FW0K/SBD3ygPPe5zy1vetObWkfKN7/5zSk9eKUpSUc4CAxBgOE57LDD2m10W+k1/OQnPylPf/rT28E5JOtS0WeccUa7HY689RMZsVNPPbXUZx1wwAHlhBNOKBdccMESBo5hRbaOPfbYtiz14fk5++yz+0XOyr2tVnVR92EPhCEZdeWdPemkk4aJThh/hzvcofV83elOd2rlEICVV1653PnOd27vu/8gw57XDTDlgTvzzDO7ou1vZXVlHaNoExb9o77dNH2yKLo8+tGPLh//+MfLDW5wg9I0TdGvPHKIufTZDMbFiSeeWP7zn/+M9Fh9gpwjZnDRPn108cUXL5HfFjvPtbIPOeSQdh64ynvFFVcsIetGubBTnnJ5Lc4//3xJsx60xZGD8847b+iz9aU6qq+xyWuvzUMzTJDwta99rdzrXvcq2vu73/2uGKcWRTXLhRdeuHjOet6wUPvwNre5TWEI119//bYIY3SllVZqiULTNG3cuP/RlqqTuvUV5yiPOnXrQB8YU1X2mGOOaYk6Ge2v8a7GifjZCPSjseC5Aq85PTpRX5tT6k++GxC2W9/61ktU21yg38k78kQeDuYO3d4V9kyy9DY58uYe2a7cbPxWF9iow0TPMy8OPfTQdv7ToebNRPITpWn3u971rmLXjh7py7J7dAdsJgrGZj/vTN8bz8ZKvx52+U444YRW5/efaV7U+pNji8gYI/q5lkWP0pfSLI7ZMfNbnH65733vK2nkENI7MlQRnAgBhGfTTTdtjRmDVsMTn/jEYhDf4ha3mCj74jQDeftFWzn3uc992q3PxQnX/Pj5z39e3vzmNxfn9r761a+WT3ziE2XrrbdujV4laSbgj370o/Ka17xmsdynPvWp1sP4hje8oVAm1xQ39gtFbgLbzn/Sk55UvvGNbwx8JuX4+c9/vvVWaRtlx0O7zz77LCH//e9/v3z0ox8dGAateCk8z7z3ve9dbne72y1Rlpvjjz++vOhFL2r7bccddywIyRe/+MUWU/hRMuRqYJC33XbbVt5ixsq7pv3tb38rT37yk4u+422rpKSmuyIBzl7C4mY3u5moWQuMhDPO6v2FL3xh0ucycvrBmCG/2267tePsaU97WtFXVUkriDeG5+H9739/MS5h+JKXvKS8+MUvLnvuuSeRxQGJcM7aNr9yv/zlL7dei3e+853FMxcLzsIPhOO9731vefzjH1/++te/DnyiOplnb3nLWwoM3vGOd7Rzi8GqGRBm42zY2DRvzW3y5qdzecaRcWLLkr6QJvDQbrjhhmX7RXrA8xh96a7GJ4wf9KAHFXOB0Sud/xB4Moj0Xe5yl07KeH9azL71rW9tx775pA76VR+/8IUvbHc2kMNaC3g5z8xgb7TRRuXb3/72YmJw+umnt/PPPNps0U7N73//+5ptrFfE4/Wvf31x7v4rX/lK+dznPleMfXF/+ctfhj6b3t1mm21anaCfanjCE55Q/u///m+JfHSb8ownfUsvP/OZzyxvf/vbC11UhWH1y1/+sn3+zjvv3OoleW1nG39Ic5Ud99V4VZfXve515f73v//QxyFnxrLxCTtje4cddijwqZnoxGFzRLwFB1lkn25429veVm5729sWOkN8DerEDj7mMY9pz8Xvsssu5RnPeEbbB8ae+xe84AXteKT3ar5xXdmFL33pS+WBD3xgecQjHtH2l3p8+MMfbr2y0tii7vPZC5zBHHDEiZ2Urm0/+MEPyiabbNK2x3jsL3ToXmUaa4997GNlGzmE9I4MVQRHQQBxQji7YbvtthslayvDO/Dd73534Istf/rTn1pSyGtJmVASPIgbb7xxe86HV1khCOT3vve9dkvfZLKFSslSApS53+TGHdRj1113LZS8Kw/AsGfuvvvu7Yoe0VQ/E13+l73sZaWbj1dr3XXXLYPCGmussVTxiBhlQmEPIpl3vetdy1Oe8pQi7Y1vfGP5yEc+0hJqhG2fffYpcO4Wuuqqq7Z9II6CR3L9FhDZDTbYoDiridCsvfbaoheHI444omy55ZblUY96VHnqU59aVl7kfV6cOMIPBNzzusZxhGztLgAFibQZF0jVKPm8HMWAwVpeCpzh5WlAhhHGWs6vf/3rsvfeexf9JU3/IWnGpHHKA1RljW+E6HGPe1whB3PEaPdFYwABrXLjvCJW6odoMzDdtvSfi1xqx1ZbbdWODe3jedLHFrTkzUnjD1aDgjHBO0PW1TjeaBHZY7Qt1roEWl0e8pCHtC9hwo7xkx8Bg5W+WGedddqdC2UpswZp//jHP4qxvPrqq9fosV/trhib17rWtdrFtXpaYNE9CK5FjvFUK2K+2aK9znWuUyxIHfeoOx9rrrlmOz+URR84BlLzjXL91a9+Vehhzx1Fnoy5hUzCTr+qO91qfDiKpP6IGNlhAQnr6n2/kf6uvDFnEeUdA9jQdc961rNagm1xWMcTLx8ibFGz/fbbt3oJpvSSuiCEFjjdssfxm7cW0VZP7akLt/6zeC21FWFzvty8fv7zn1/U833ve99i8ete97oDdXedM3bDEH528IY3vGFh22pmOgRm7vWFOWihpZ+M+7XWWqvc/e53b7HSf5tttlkxz2bjaMRqq63WjntnbY1nfSWYv2wMPPpecmTVwo5NYSPrbs/1rne9Qjdqj2AXp+s00wccC/rGOPdsmIwaVhpVMHJBYBQEGCurt26wkhslL6PAsPHEDZL/1re+1b71jzQxGk3TFJNsww03LLe//e3bLVH5TAKk4jvf+U7r3WSQr3/965eHPexhhRJlVBl9soMCBYbgDNtWtFVJ8XpRbFD+GocIMSa8GQgDJVbTuld18RLO3e52t4IEmPRW98973vOKlT9jUOWtpLvYdn8/9KEPrWLtlTL0ljyly/PVNEtv9fJEe75ne8lMRoYYeaWMEDRxNZDn1brJTW5S9HWNr1d4xQpfAAAQAElEQVSYIT/6vEtIKGgLEApxm0VeIf1W84x6tdpHvqZizJXNgHo+Bcnoihsl8BQy0AwKbJqmaRcH97vf/Qqjw2tdy7G4QBgobudLr33ta7ceD+nGtWMPfgs8VzxgD37wgwusyVLyyA7jwBtEblDgNbKA0Z5B6eIs7HhW/R4UGFU4GmPVIz1IrsYZR7DQbnHGijn3m9/8pvAOijNmza/ueOz+Np60k6z5eM973rM99sQoWpQh3tIEi5ott9yyfQnTPS+6BZQ5754B5Jnub53zvvsyiLkL3+74k68fjKMtttiinWP9tHpvIaJP6v1EV31ifpij5LTT7sr666/f7lpJF1+DeUcf8YyZazUe8TPW6RmLoYpbTZ/syrP397//ffFxicnkpSMkFoP6TJ0RbgRNv1l06KO+t1G+bjDn5e8GHvmujC1wepy+9gx6mT5HZBybMTbJ8yxrA8J/y1veUlShPy2sLTCUwynQJvT+gZ/FLe+5373k9pZepRf73sc28Zp/pFngGYvmLEJ5TdJSF9hZ9Fq8IJp0wLOf/ex2fhtDdIBM9GYXn/q7Xi3U9L3dMPrKPVztpCLRdkiU43699dZr35Ew9+gXduvhD3+45GLs6zve9onGD6dGLbPN2PuHo4LHehjWXXHjA96Os9X4m9/85q3d5Zk3hmq8q/khHtHnQVdn8YIjcIJdNWWIq8HOBy8yewKDGj/qNaR3VKQiN1YEKBjEweTnARr0MEpYvNW0aw0UJQNB0YhrmqZQBPVenECmaZrWE9mfSNJroKCsJG1TInE13tWzEWrGmnEWNyxoCy8F4zyR4vE8Ry4Qgab5HzGlCLQNeXYd9px+PFnGn+J3ZpJiQJYopb4so8uDztB1iSgjRIEhRt085G1LWb33MWTUpSElPHM1H4LIi4SIWCw0TVMQu9nw1KgDco646oc6hsRPFihh3rdu3yE1xoByuh4U95R3t0xy7pXBePkt2AY1PrvlehZSqe94MMgNCsaJhQjPCEPXlUHieEV45xAqZXXT62/GhiG384FIIN41rX+1QLTTgJBrh/SmaQoSrP8tqsRNJSASjJ08xgAsBPeCNtgJaJqr54IjNEiv50k3Jnm8jEH3xinS7HgF4oGU2/405qUPC/DjYfYsCxblVFn1MofgZJHnvqYNusIa8ZFmJ8C1BroNzn19hMzLZ/FTZV31o/PTFlDGlbhxB2MCCUU0+s+ydV3T+2lTvadj+jjQNU3TFGRWHZRpbvgtzX0N8DKv1MecqfHdqzzmmJ0oerzfdwivnQBOC4vabt7ub32GXOkf41N9uun1t/oYR8acBU6NJ2/BIN7Cu8ZPdrXANsf1hbzGP93FMWJ8y89DioiTdc9O0amV9IqzQHCExu9BwfywuOBcQcy1o8rBmV2wGEemjeGaNuyqnuqMbHdlEGa6UejGG+PKNl+79oKOpR8s3rSzm8cnynje2RNOHn3NsdSVmex3SO9kCCV9SghYndtKtrVhS9/AnqwAZNSqHCljsIfJm8S8uLaZEANGCqHiCaUkbZcMy+sZ8jEitvOHyYmnuKyyTUgKgRdEvAnGm0TZ2Ha0khc/3aDdVu6IRbesNda4+rgCI4jEdNMm+s0LYjuOQtRmfaG+tsz6+TybgVhr0dZYVUqUH+UqjYLp5kF6nf1EQioJqukUKEPE0wVn8RQYr2PtI3VBWGyhUmxk5lOg1BlLRLrfX/12VLx58iwE+unD7o2FYWkMsL5lZG1tImRkzQPbqryyvNnO9yEG0qYTeHJ547pGSXkIqPFS54a4UQNjan7xyNoSRqARz0H564KQZxBhGiTD4PPGIibGmTHGG+5YhvE6KI84izB6xzi23Y74Gq9IEm+koy0WFwxsn6jJ3w3qKSizeial01MWrbx1PIDiBLoEEaK3KnkXLyBiFhq8pNLFjTuoA5JNXyDjxjmy4oiTeY389MdAv07Gil0G+HMM2AmZCP+a38KJ/kFwEEXxzmqqk50I3kb6mwdU+erF06/fyPaD8Yrw8pLbVXIkqZI2utFuontzxQKqn3+q98aLOUsf1PrXMuyw6WtjtMZN9WpcIr88svqlnx9BtTi1OEEg++nD7tkHeD7ykY8snAK8y8piV3lTzQnEks2brO/ZDP3vWZw3rgK9ZDEqzjwXV4PxARs7RDXOVV9b3PttHLgK7LH3d8wJY8I4wxc4lqSPGkJ6R0UqchMiQNEgQpTJ6quv3n4yy4sK3S2ZYQWYsDw1FJTtn2FyPJ/KRMacA0OCbX+ZrLZpHvCABwzLWihvq3YKj8IcKrgogeJylsqxBN4geRA93l1eKkSQB0ibF4lP+3+YWXX3jXrd8mQ4KKJRH4RgwcNLVJSugARRYP0yGDSePmfKXCkWZywZLS/SaWc3j3SG3HdVfX6MN7sGZ/CQXsa6m8eRBljyQqiLbUJeRkaiKzcffhsDyLqxOpHBZFwRMWSB8aCoa/uQCzhazNQ4yn9Uj4UykUVeDzgyAM7w8ewjCeZG93n1GctytZuhrP5YRzCRagZ/quVaNNq2ZAQtVBFg42JQOXYqLHSNGfUYJENnWADYWuZlVZbztRYbTXO1t3hQPnGMsX4y522XWqTDkUE19i3OJiO8yuGVsjB1PMk9kuJsrUUzz5cxoJ7SBASZZ868tqNU55Arssboy6de5McdzEX9YLdBu+HHOaBuCKSztP0xUOtEb9D9xoJyzAvngOl+GFS5QVcLAvrGFrpnN83V/aVfkFJzhHPhSU96UvvugSMJ5iC9PxE2FmV2Ds1Ti0DE1y4UbBExCy5jqmmuft6guo0ah6Qpk/6m/7r5jF36Gynsxk/lNyKLODqqYM718yK7xq32TEZO+3nJ63e21Zlsi0aOK55w44+DoruI6+ev9xbfxrRdRfLIuYW5sWNeWDiyMVXeVTo5Xm3jvgZjz4t4no+YkxXMQ+88WIya4wLngz6WPmoI6R0VqchNiIDJg3zysDDKlKXtQas5k4qRH1QAY+9NV5OlT5b68oweDyRjYfArH9FywJ8iNPH6edzbzjJRkEArw2HKm2wNFKoJRXkjI7apEEnkAhm09VVl59rV2Uf19eWMbuAt69eVkuNBceaY0rZlb2XPa4hI9L0pyC4yzvjwklHGNVBKlD4yU5/TNFdvhXfr4TdC4nlVbj5cKWeLHgTeGDdGBtUb4THmGTyLOXOjK8frzpPiix7ijU8LK3HuGQ3XYYEX3YJPPXjRLSbsqpgD6jXIMA4ra3nEG2P6v44DJGlYPbTPGPTi2jAZ6cim8rpBnqaZnNQwruY1A7zhhhu2X6bYYost2hc2jelhz+3GW7jTcYiaca1NvFJ0jnHDa2lu1DwWTvQVPVbnT70idIik+nfz1LzjuBrLdnx4etXbsQDjyba6Njm/Pey59IHxbm5wFlhgI5XGqZf1zIdBeWHmyw1ItkVBVy8jihwVcPIFA+9n8OjxxLta6A0qsxuHMLEPvPXqxqOpLvoDkZwtbLt1WpbfFsnGtXnOBvbL4Pl2HtoYg3k/fbJ7Y9WRIpjoOy/AmaMW1hxYk+WXzjnE283ba/xzvBgLyjSHndvu1t1ihqzF829/+9v2q0Z1/NvJMu/YkW57LBoHzXM7s+owagjpHRWpBShHcdh2GzXU7dpBUDRNUwxUA7tpmvYgPWPPq8rrhfyWAf/ZSuMNsC1IxmocCSDqnjK1YnfPi8UDw6Nj8K+66qrF+V8yVqdW8+S6ASFGeK38EbupEIKmadoX4XhrTFKT0FYMA9F9xnR/Kw9uVuyDypIuDEqbThwvE8Oi/3lvGW14MgwUjP7sl4/0MiZW2Yh/DVb5MEIgutu4/fyj3nvRCjFStxoYSHVGSGqcK+Vq62/UsqcqZ8vPJ4sQfYbAgmKYwbSIQ2YZId6NrtKuz+WJ5Um3ban+lLy2OdNInreyyg67er6jDo4F2PmwDWjh2DSTk7xhZQ6KZ5S0X7sGpXeJyqD06cTxoFkIIFUI4HTKmihv0zTtlyB4mOrYR5AQz4ny1TRePOQMThbIdA6y5are+rTKuiJu5HjA9GGdQ/VqXJhfo8wjnmhjqBuMUeNVG7rxdmZ4Y9WhH+xkIYYIN/1q4YVEWfQ3TVN45/svItUymqZpX9iiw8Q1TVMcVzAetZG3XnwN2s+TjVxbZFjwdfWydM+1qFMn/QKbrhOCB9IxkFrmsKtyLRDpbjtqFiHGU9PM3Dxpmqvbb9Gk7v26mKv9MdCXmc69McvTi2COOmb7z+MoYefofOO52te+3KB7bUZ6OaMcC1IfBJbu0HYLp6ZZEm/jwvzQp/q2G+BoQWT8qc+gZ04nbqXpZE7e+Y0AReDw+agBgZ1qi60YKVoKZ1BeE8y2DSXIcyggVmStEE0OpMa9bUeK1dkv90LTNO1H6D0HgRZXAzLA+CBjCAsSXtNGuTL0vJ7qxHONcFEMtmVGyT+qDILJwFkcdPPwBLmXTin5PZPB1jXlwkBZ0VM8tgIRYOdWtbf7PHjw5lvFI2jdNHVnhJZljHTLqb+NCV797ti0DYr8U6zdeIsmSrrmnekrEsLo266tC7BBzzCWvajHe86DZwEwSI4x8IUSGGsHTxrDwGPDU+vrF4PydePMC4YfKbQtb6GIZNcx05Wdzm9eJvOHUeuWw7CZ10hVN34mfyNZzkIaaxatM1l2tyxG1tiiX7bZZpv2u6i2dy2kGfSu7KDfsDBn6CULQobasQ1zigetnwdu9J0z0YO8VPrUrswobbbgN4b222+/Uq90Hs+aowM1ztXxLnXr18c9rxsibkHnvgZedGXRFVMdW446mK+2/mt5rhbIdpLoHfOF3hFfg3nkvLPnWfjWeFfEzja5MswBcRMFZBAedl0sNnmNOUeG2aOJyhqWBlPeUmPAQq0rZ/ya79rajZ/J385/W3DBBcmfatn0vIUJ5xCPMl1Kt3hxTrmTlafNHGjk6DxEl3PIQtz4pD+kdYPxBJvulx5qumNb7J32GD81fqauIb0zheQKXg7lxWPVh4Eipdytrvtp7g16E6MbkAtpjkqYfJSue5OTEep7RE0yk6OrPBkWW5Y8xzvssEP7bURliHeGr6+IpXUDgmeLjtcEqVAPbTRRHfqnTLvy0/ltgvt6Qr9MhlG7nHVD9qfzjEF5LRKUz9tUy7cQQmp5rpCwbj5K3RaWs2OMSDdNXS0ybMF14+f7b4SGgWZsnQes7bEgQyrqvSsjYcwwspQ+bMU7hmPXwu9BwbhGlB0zkXeQTDdOnYxtL2p5adQYtVhhLMyd/vzo5p3qb2crGW1eme54QIItcnjqplrmqPKImG3uPvEZNf+ocsiuHST9C3/6wXxwHnEyPeEZxj3Pvhc4a58jOeaRBXwXN/L6z2KTl6tPUuhLhEB+i13ysxHgTLcag/3n8R7yVMKkn+beotP4g4P7GhBTY9uCrsa5Ip0wsYC0SBCHNHEuILzu1cd1UH3UowYyw4I5p0+9L6FPBcco1NW8GYXQDSu7G4/0BMXLpQAAEABJREFUOtOsL/VrN80XPeyG8Nx342fyNy+9haFFxrKUy0Za5CGpdJ3g/RhnfNV/sjLpG0dj5K/9yT5oM8LLNnTL0LdsHVsyaG6bM9piIdHNN1O/Q3pnCsk5Ws5sVYuCQS67io9yt01ti696NGxDI6cmGcU3lfrZ1raqtCrt5kNEETIH4Wu8bXuKzXnh7nYxL4q3hZHaKtu/Urw8e4guRVm3xJw5Rk54Na2Ku23tlzGVexMcseXZZPBqXp+RYXCceatxM3n1PAsGJLaW615faaP+q/GuSLL0Lp7ieU0YLQsKhlzcfAzODRqbXW+1c40InpcXeb20Cy6Ikja7F+BlN4Eht0ir5Ie30gfqJxorDIAzlBZTsFfeRMHYJK9uPIqMqrFvO5j32GKR93KiMkZN02bb4rzd5pl8DBkvKGJv3IobRzBXGUjGcxzlK5MucMaaF9C2PgLDW2VRQQ/YGh9EvOStwfigf8wL80M83BBX/YC8i6vBWBCHqFT5mkZvqYOdKySqxo/7atwhbs679p9lgef4mYW5NMcm3HsJ1r32O67TnQ+OSrmn2+pOHVk6xyLQfIKPODizC/S6/kawec0dsWA/yNTghUG2xvN50mt8/2o++kMx+k6bLFo5FyxqnPFF7OhyRL+fd6r3+pBt4DAwL2t+Y8JiyLlmnvsaP9NX2NkVWJZFkj5yhtccc5TEbiiyyb7Z5fHCqXZMVGf6nz5wnEXfVVl9ZCxbjNc4V3ZCH3KE6RNx3eAYpXro/278TP0O6Z0pJFfwciggxpeiMQkpSl4nio0X18oPRFb+yC5F574feJQoI/G2uBgNvwWH7E1CZJBnxqePvCjktzd8vW1MjgfKVx54GihPSqlpmtI0TeFZpljJDQqUoIP1tgIZPsawEpimaQoCT8E74uDloUFldOMYNx5BxwK0m5FVvtVvxYCi8HIcEuFsJ+wYBkbFOeZRtru7z5zsNw+HF1PUCxa8E+omn7YiMpQYDw6FJp6S4umGD0XOeyLefS3Lfd9IiVvewUKJEUQoHCVQHwRe+42xugCqY5NSJgMXhoAnRR80zdVjyFi2oNJ2cvIxrDCyKwDDprlaFrFBCsh1A7yV6zuaFoCOzRjDTdN0xZb67UUj48+2OXLdNFfLG+O2po0d5MHbz/p5qQKuiTCveGf0MbIv2lxSJ4YQZuIEcxoBswiU7rweGQRfPJmZDOqtDQi88YlwI9rTfMZS2Y0B8w7ZtVBgoAk1TVMYfDgb50hSHRPSu8G3qY0pYwE5QLJqugUgfIwVJJCM+WROI290AB1V5c0rXkh6wdijx2rauK88+ryijsk4a2tcOBdsXNLhxihipR6w4N0z7t3z7uknDgK6W995YdgYp6vNB3LymR8W9nYIjNmmaQr951hJt4+9W0D3Ol7GflgAKctXJCzwyMun3H7QB/oE9s4Gd8mTumgfRwKsB83NbnkWKPSwOaJ/pakT/ajv9ak4jgNlmn8INQzYJedSnbtumqvnKdmZCsaSuvhsoLrQcfph1PJ5WjmSeHXZOjsTNS/SaRHNe2sMGL81rXvVx+yCnUFYdsezhZQ5xZbRjVWnsH/sofr7XcvTb8g2zLXHHKn4VpmZuK40E4WkjCBg5Y5o2uJDJigpyokhpVArQkgAJWBbwxZVja9Xk4uSImNS8qrVNF44RNN2rslGCTIUPDXOUFK+ZBlNW/bKGBQQS2WR7YemaQqvAKVJ6Q5K10ZHOZCMfnr/ntK1COAFYFh9GsZKlsdDG6q8lTaPIGIvzTYnRTSoDjXPsl4pHy8dOFdqu4+yqdu4TdMUnk5kAP713Jz68NggAM4fU3CeTymR8wIMrBEJ8XMpMLYWSPrCokU99bF+QSIpX/XVR9Lg4p5hdz8s8AiSg6dyjcNBsgw17wnZGih2WPEI8tgiXo4R1PRhVwsS5EIdGfW+HCKMrCEVg9KrvD7XfsRSmertGBIPtkUMzKos42XHhCdHujlpfphjVWYmrxYhxpfzheqFXFkMz+QzlMUzi6Dw/jHO4rqBwbflbjEyKJ0sclrHjftuPR31MV8QCIsEhMQ8Q7y0C56VSMlrgWzhjhgimPpI/GwEBNILZc42884aFwiJOW+R0z27TSfRD3VMOwNKxqLdwhLx9ZlCZKer+7VH+7R9UHCeHTbaa2FpYec7shYBSBJ8zCWLCHaE3KDA+aKOjlHQVX0Zup/eY0f0TT+9e0+3OUbkym6oN3JpHtihof/I25FzHAYBRN5hQNezUb5mQGamg7Fk90Wd7PggimzfqM8xxuQ1twfhwJFFl8BqkEfWcywK9Y9yzAPYiBfsVtCJxpAFtnktni0xDuBlQStOMHfoHWXhB8o296XNZAjpnUk0V+CybFUwtFbgDAkSynNQt8QqNCaGdISYoqjx9crDYgVOxiezTLya5sqQm+Be2iHDo+AeeZAumMxIhPRBQVpXXp5ucAaNwRpGQihmXhxt6eYb9Hu77bYrg+pgkdDfjuJR4YUgr+2U5qAypxunXRS45wi8OLWfmqYpvOPivfShTp7HIIkTfDKoGjPeGp5A8YKVOvlxBNuvzs1OdauQ0eGtUL9+0Jaq0JFY6b7yof71XtygUEkfQoSEDpIRZwxUHJUr8Bzra4TKCxviRgnGprkzaMFY8/PcIFT1ftCVkUPI1K8ffDMVZjWfPubJYozIGi/63zyoMjN5Rb7h4lmCYx8TkZxlfbZFsu8c679hZdBH9NqwdERPHWtg6KusOpsPdCHPJbyM3SrrihBU+W6bnaesc7Kmj3q1m8UL3+3DUfMit8ivutHD5k2fONJd+kRblAs/2/vi7QZoszlkId80//NwcmYgmsoeFHgdu+MaEYcPXUiezre4Zms8d1hgIzgm6Oem+d/zu/JsBJw8oxvf/21x7Nn9oI1sgLlR8yiLw0AbpbN/fR1fZWfiCn87UbVuiP4gmzrsWeprzOmXYTL0BEfMsHItkOrzXbuOIIsLC0qLF/rRvefQL2RrECdwHDgiWeMtpvSltJkMIb0ziWbKCgJBYGwIMOIWOK5je8gKXHCavjAQsKCyYOsSyIXRsrQiCEwfgZDe6WOYEoJAEAgCQSAIBIEgEATmOAIjkN453oJULwgEgSAQBIJAEAgCQSAITIJASO8kACU5CASBINAikH+CQBAIAkFgXiMQ0juvuy+VDwJBIAgEgSAQBILA7CEwn58U0jufey91DwJBIAgEgSAQBIJAEBgJgZDekWCKUBAIApMjEIkgEASCQBAIAnMXgZDeuds3qVkQCAJBIAgEgSAw3xBIfecsAiG9c7ZrUrEgEASCQBAIAkEgCASBmUIgpHemkEw5QWByBCIRBIJAEAgCQSAILCcEQnqXE/B5bBAIAkEgCASBFROBtDoILB8EQnqXD+55ahAIAkEgCASBIBAEgsAsIhDSO4tg51GTIxCJIBAEgkAQCAJBIAiMA4GQ3nGgmjKDQBAIAkEgCCw7AskZBILAGBAI6R0DqCkyCASBIBAEgkAQCAJBYG4hENI7t/pj8tpEIggEgSAQBIJAEAgCQWDKCIT0ThmyZAgCQSAIBIHljUCeHwSCQBCYKgIhvVNFLPJBIAgEgSAQBIJAEAgC8w6BBUh6510fpMJBIAgEgSAQBIJAEAgCY0YgpHfMAKf4IBAEgsByQSAPDQJBIAgEgSUQCOldAo7cBIEgEASCQBAIAkEgCCwUBLrtCOntopHfQSAIBIEgEASCQBAIAgsSgZDeBdmtaVQQCAKTIxCJIBAEgkAQWJEQCOldkXo7bQ0CQSAIBIEgEASCQBeBFeh3SO8K1NlpahAIAkEgCASBIBAEVlQEQnpX1J5Pu4PA5AhEIggEgSAQBILAgkEgpHfBdGUaEgSCQBAIAkEgCMw8AilxoSAQ0rtQejLtCAJBIAgEgSAQBIJAEBiKQEjvUGiSEAQmR2B5SJx11lnlQx/6ULnDHe5QvvSlL02rCldccUX5xCc+Ue5617uWlVZaqay33nplv/32m1aZyRwEgkAQCAJBYC4iENI7F3sldQoCQxD485//XF7+8peX613veuWggw4qL3rRi4ZIjha9zz77tMT5s5/9bDnllFPKne50p7L11luX//znP6MVEKkgEASCQCnBIAjMCwRCeudFN6WSQaCUE088sWyzzTZlo402aonvDW94w2nDwlu8ww47lIc+9KHlVre6Vdl8883LxRdfXM4999xpl50CgkAQCAJBIAjMJQRCeudSbyyQuiBMn/70p8sXv/jFUkZs0yGHHFLe+MY3toTusY99bHnf+95X/v3vfy+V23b8j3/84/Lc5z63lX3KU55Svvvd75YLLrhgKdnZiPj5z3/e1vv0008f+Dj1/d73vlfUE1l91ateVf75z3+WZflPO0899dTWG/vhD3+4fPKTn2y9s92y3vnOd7a4eNaw8OxnP7v1Esu39tprl80228zPNnz/+98vd7zjHcvtb3/79j7/BIEgEASCQBBYKAiE9C6Unpwj7Tj00EPL4x73uPLKV76y+D1Zta666qqyxx57lCc+8Ynl+te/fvnNb35TEOZf//rX5TGPecxS2V/60peWbbfdtjzvec8rv/zlL8tWW23Vhp122qlceumlS8mPK+LYY48tT37ykwuC/qc//alccsklAx+12267lTe84Q1lyy23LLvsskvZd999y7Oe9axyxBFHLJb/6U9/WpqmGRiue93rFkSU8Le//e1y3nnnFdistdZaZa+99ir3vve9lziK8LWvfa2svPLKxXNhaQHCc1vvb37zm5cjjzyyDPIS77jjjsXxife///3Fcz0zIQgEgZlBIKUEgSCw/BEI6V3+fbAgavDf//638D5ut912rSfyRje60UjtOuecc8p73vOe8ohHPKK89rWvbfPwPiK2Z5xxRnnLW97Sxvln1113LV//+tdbz+qjHvWoltw98pGPbPN9/vOfn9SDesIJJ5TTTjtNUQPDRRddVHiceWcHCiyKlIZAvv3tb29f+loUNfT/Aw88sLzkJS9pz91uuummrff0O9/5Tks6naG98MIL27yPf/zjC/I/KCDTT33qU1s5/zzoQQ9q8dpiiy3Kxz72scLDjPxLO/nkkwvM4LnGGmsU9//4xz/KbW5zm+KezMMe9rCC+N7ylrd02waLha985SutxxyBd+ShTcg/QSAIBIEgEAQWEAIhvcu9MxdGBRCn+973vgWp83LVTW9605Eaxuv417/+tSWQXaJ8//vfvyjjW9/61mIvKsJ77Wtfu3hOLZxX8wEPeEB7BhXJrPH9K4L5jne8oz0Te/zxx/eTWw/qxz/+8ZagIpJLCVwTgZgikR/5yEfaIxjXRA+8fPWrX22J+cYbb7w4Hfl0fhYZRVAXJ4zw48Y3vnFBzKso4qo+NQ4h56WFHRnPuNa1rrUEXk94whOWOA8sP9L8s5/9rLz73e9uvwghb0IQCAJBIAgEgYWGQEjvQuvR5dSeNddcszz84Q9vv2AfqBYAABAASURBVCowlSpU4ofM+mRWzXuTm9ykXOc612k9lyeddFIbXb20ZNuIa/65wQ1uUFZdddUJj1PI41ztT37yk/KmN72pfSnsmuzteeCdd965CL5coKya1r8i2bzLXvrqp/Xv//KXv7SfAYNNTUNC73znO7ceZZ8eq/GjXHl8EVnlOrLguMRqq63W4i6/5/iyg9+Cowow3WCDDdy2Ye211y68zu3Non+OX7QA4DFWNm/7lVdeWX74wx+Www47bFFq/g8Cs4hAHhUEgkAQGDMCK425/BQfBKaFAE+kLf5RCqkez0GySC+yt+eeexZnaN/61reWM888s/COOjbhaAZPr/O2q6yyyqAiphTnzC9Cj3Ty7tbMTdOUW9/61gXh5R2v8aNcX/ayl5XXve517Utxzj8j8HvvvXdBogfl/9WvflWQ7Hve856Dkts4nmFlaLdzvEj9m9/85tbzXfJfEAgCQSAIBIEFhMB8IL0LCO40pY/AQx7ykPYMsJeujjnmmPZs69lnn92+pIU0kkfEXLfccsvCE7n77ruX888/v1x++eXtuVV5fVcWaSM3UXAUAsn9/e9/X5w//sIXvlC8wIX8eZluorxzIc0ZZ55vOPziF78od7/73QdWC+n20tv6669fVl999YEyIj/3uc+1mCqvBi/Z1SMSZBKCQBAIAkEgCCwEBEJ6F0IvLmMb/DECn7gaNRxwwAHL+KTh2XgsP/CBD7THGJBQ34z1BYK//e1v7VleRxd4RpXwnOc8p7z4xS8uSK8vIuy0007F58uOPvro1mO7zjrrEJsw8Lx6cQx59FUEL8z5/JkwCmmesPA5lAgTX27wwt8cqlaqMi0EkjkIBIEgEASmg0BI73TQm+d5vTjmfOqooZLPmWy27Xck1NcDnKdVF58q8/IXwut3/bzWzW52s/bLBb7UYDt+ww03LPI+8IEPLGTvda97jVQ1HmLeUs9Ggg8++OD2KwgjZR5RqJ5J5j097rjjlsrlJbRVZuAYxVIFXxNx+OGHt0cofK3hmqhcgkAQCAJBIAjMfwSm0YKQ3mmAN9+zIpNI0ahhlJe3lgUTL6ytu+665cEPfnD7l8H8cQSkzTEH51i7ZSLqzqiq833uc5+CPHq5y0t0t7vd7bqiA387w7vLLru0L635HrA/LuG7t/WM78BMyxC52mqrtZ8Gcya5+4czPF/bfAGCl3sZip40i7PCRx11VPuCnsXDpBkiEASCQBAIAkFgBUAgpHcF6OS51ETndJFMnypDAAfVDWHz18ee+cxnFmdwB8nUuN/97nftH2twPIEnuMYPuvpsGS+xl9bqGV5nV53x/cMf/tCe7XVWeFDeZYnz4hyv8h//+MfF2b2Up33OMt/iFrdYHD+TP3xyzZleC4GZLHcelJUqBoEgEASCQBAYikBI71BokrAsCNjO90cgkEdHCPpfVPC5Ld5HXlaf3eo+wxlUfxzBi2VrrbXWEn+YoiuHLHuGPxLhzxX7ooG/Aue4Qleu+9tLXc4AOzPsk2XOBzvD63iDvEiwPxf8rne9qz0W0M077Hf9rJe2+hpDX84fkOCV9q1hL4ch3T4Hhvhvvvnmhde6n2e69zzLnuXIBg/6dMtL/iAQBIJAEJhvCKS+wxAI6R2GTOKnjAAyybvoqAASuNdeexVndJ/xjGeU/ffff8LyHDPYaqut2hfTvHzl5brb3va2S+W57LLL2qMJPqt14oknFn8kwlcdJjsqgAwiqYhvXx759Q3fj370o8VRCbJLPfiaCKTei3SIO+IqmtcaiXbkYp999hHVBsdB/IEKX094/vOf32LBy+05ziG3QjP8j/PDr3jFK4pFge/0wmmGH5HigkAQCAJBIAjMSwRCeudlt83NSn/wgx8sPgXm02O8sf7EMM/tt7/97VL/QAKvKlKJfHr5rLZkk002Kd/85jeLLzkgk87qNk1TkxdffW93m222af8csS8weHltlBfC/DUzX4XgfR0kzyvqk2W+besvwS1+YO8Hz/Bmm21WyCHR2sKD68sWjlp4ua6bZb311ivf+MY3Cg/3vvvuWxyl0FbP68rN1G9/fIKnF/485zzY3bLzOwgEgSAQBILAiopASO+K2vNpdxAIAkEgCASBFROBtHoFRSCkdwXt+DQ7CASBIBAEgkAQCAIrEgIhvStSb6etkyMQiSAQBIJAEAgCQWBBIhDSuyC7NY0KAkEgCASBILDsCCRnEFiICIT0LsReTZuCQBAIAkEgCASBIBAElkAgpHcJOHIzOQKRCAJBIAgEgSAQBILA/EMgpHf+9VlqHASCQBAIAssbgTw/CASBeYdASO+867JUOAgEgSAQBIJAEAgCQWCqCIT0ThWxyeUjEQSCQBAIAkEgCASBIDDHEAjpnWMdkuoEgSAQBBYGAmlFEAgCQWBuIRDSO7f6I7UJAkEgCASBIBAEgkAQGAMCy4X0jqEdKTIIBIEgEASCQBAIAkEgCAxFIKR3KDRJCAJBIAiMFYEUHgSCQBAIArOIQEjvLIKdRwWBIBAEgkAQCAJBIAh0EZi93yG9s4d1nhQEgkAQCAJBIAgEgSCwnBAI6V1OwOexQSAITI5AJIJAEAgCQSAIzBQCIb0zhWTKCQJBIAgEgSAQBILAzCOQEmcIgZDeGQIyxQSBIBAEgkAQCAJBIAjMXQRCeudu36RmQWByBCIRBIJAEAgCQSAIjIRASO9IMEUoCASBIBAEgkAQmKsIpF5BYBQEQnpHQSkyQSAIBIEgEASCQBAIAvMagZDeed19qfzkCEQiCASBIBAEgkAQCAKlhPRmFASBIBAEgkAQWOgIpH1BIAiE9GYMBIEgEASCQBAIAkEgCCx8BOLpXfh9PFkLkx4EgkAQCAJBIAgEgQWPQEjvgu/iNDAIBIEgEAQmRyASQSAILHQEQnoXeg+nfUEgCASBIBAEgkAQCAI50zvKGIjM3EHgqquuKpdeemm54IILyvnnn18uvvjicuWVV86dCqYmQSAIBIEgEASCwJxEIJ7eOdktqdQwBP7617+WV7ziFeXZz352efzjH18e/ehHl7333nuYeOKDQBCYOQRSUhAIAkFgXiMQ0juvu2/Fq/yvfvWrcp3rXKd88YtfLN/97ndL0zTlM5/5TOv5XfHQSIuDQBAIAkEgCASBURGYGdI76tMiFwSmicCLXvSissMOO5Sb3/zm5Za3vGVZd911y2WXXVaue93rTrPkZA8CQSAIBIEgMBiBAw88sLzkJS8pv/zlLwcLDIg95phjynOf+9zyu9/9rrVTA0QSNcsIhPTOMuAL+XEvfOELy7Wuda023PCGNyyrrrpqWW211dpjCHvsscdSk/5zn/tcufa1r916a1dZZZWy1157tfCceeaZraJQVtM05V73ulfZf//927TVV1+93OIWtyjO9h599NFlzz33LJtttllZeeWV2/T8EwSWJwJ5dhAIAgsLAe+Q7LrrruWlL31peehDH1oe9ahHLdHAiy66qPziF78od7/73cupp566RNod7nCHssUWW5R3vvOd5VOf+lT7DsoSArmZdQRWmvUn5oELFoGdd965rLfeeuUe97hH2Xfffcs555xTDj744LLWWmuVrbbaquy3335LtF2cs7k3vvGNy4c+9KGy0UYbtek3velNy7vf/e6yzjrrlOtf//pt2gYbbNCm1X8OP/zw8qpXvao92/vMZz6zRucaBIJAEAgCQWDGENhll13aI3Qf+9jHWmdMLdiL1L/97W/LO97xjtYOHXLIITVpiat3Tz75yU+WH//4x2XHHXcsSPISAgvzZs62aqU5W7NUbFYQOO6448rPf/7zcvnllw983iWXXNKmn3baaQPTu5E3uMENWm+uowe3uc1t2qQ111yzPO1pTys8s4O2hRxLuN3tblce8pCHtGd1yzX/XXHFFe1XGe5617uWhz3sYdfEXn05+eSTywc+8IGWYCPH17ve9a5OyL9BIAgEgSAQBGYIAU4btmbLLbcs97///dtdSUWzl3YvvWPCw9u3UWS6gR173eteVz7+8Y+Xn/3sZ92k/J5lBEJ6Zxnwufa4r371q2XrrbcuP/nJTwqi2a/fe9/73vK2t72tHHnkkf2kpe6PP/74cuyxx7ae3Zvc5CaL0x1hQG5tEy2OvOYHBXCrW92q3P72t78m5uqLs1A+S2YryYtrV8eWgoRbLfMGv+lNbyqORdS0XOcBAqliEAgCQWCeIPCWt7ylPa73lKc8pb3Waq+00kplww03LNtuu23ZfPPNW5tX04ZdN95449ZR88EPfrCcffbZw8QSP2YEQnrHDPBcL/71r399uctd7lK22Wab9kgCj6w6ezns7W9/e/nEJz5RXv3qV5cHP/jBoicMf/7zn9uVsFUtpUDYN3QdRTjppJPKfe5zH1GLwxFHHFHEr7HGGuVmN7vZ4ng/DjjggPZ4xCMf+Ui3i8N3vvOd8sc//rF4oQ3hPeWUU8ob3/jGwvu7WCg/gkAQCAJBIAhMAwGOF7bmyU9+cvvSdLco9u3Wt751cTSvGz/Rb/bqZS97WTnxxBML+zaRbNLGh0BI7/iwnRclO5LgrBJCuuWWW7Zvpp5xxhnt8QGfBNtpp53K85///JHa4hu6vLL3vve9W3lneikN3mQvufW3gLwN62U1CuRHP/pRqeH73/9++fWvf92+nHa/+92vLav+8/vf/744OoGQq9fLX/7yVo5CqTK5BoEgEASCQBCYDgJ/+tOf2p3Fvg2aTpn3ve99Wy+vd16mU07yLjsCIb3Ljt2CyekN0/e9733tC2g+ycLr67ySN04R4VEa6igCgusIw5e+9KXi/NIrX/nK9gWAJzzhCWX77bdfyptbie1tb3vbYlVdwz/+8Y/2OAVl4ysQ3ed//vOfL7vvvvsSQd0dd+jKzd/fqXkQCAJBIAgsbwQc13N2l32cqbrc6U53ar/gwNs7U2WmnKkhENI7NbwWrLTJ6I88mOQ8vN44dY5p1AY7puBlt/XXX789KmFFi9SeddZZ5TWveU2xFdQtyxusf/vb39ozuby2r33ta0sNT3rSk9rzU15u6+bJ7yAQBIJAEFhBEEgzg8AYEAjpHQOo87FIZ3h9VsUBe2dsv/KVrxTHFeoZ38na5NzueeedV5x/Qnx9RsxLaI4jKKef3zd2Pesxj3nMEl9tIGcVLN3bsu4TgkAQCAJBIAgEgSAwXQRCeqeL4ALI7+ytz7J873vfK5/+9KfbD2074/uCF7yg7LPPPpO20Mtq/niEcrovnjnWgEz//e9/X6oM3zQkz6PcTeRpPuyww9o/QLH22mt3k+rvXINAEAgCQSAIzAoCbNJMPYg9nKmyUs6yIRDSu2y4LZhcPgHm24E+Wbb99tu3L605w+Sc7D3vec/2D0BMduj+3HPPLb7E4A9J+GZhBedud7tb+/1fb6p2J7tPoyHJ8tWX3moeckiyL0BM5c3Ymj/XIBAEgsCKgUBaOU4EHMnzorWdx5l6jk96etnbZzrGs7T6AAAGoUlEQVRnqsyUMzUEQnqnhteCk37Pe95TvvWtb7UvnnXP8Drjy+t75zvfuU1z/nZQ4x1/QGqFG93oRsWLbFXujne8Y3uWFyE22Wu834i0FfSFF15Yo9vroYceWnzwm/e4jcg/QSAIBIEgEARmGYEHPehBxfflHdGb6NE+m8lukfnLX/7iMjT84Q9/KKuttlp54AMfOFQmCeNFIKR3vPgul9Kn8lDe2O2226484xnPKP6IRDev1ehuu+1WNt1009L9YxNdmfPPP7/4ysOpp55a/N5ggw0WJyvPGd9//etf7cttlMPFF19cPvKRjxTHG5SJaNc/fHHUUUeVRz/60e0Z34MOOqg4Y7y4sPwIAkEgCASBIDBLCPh+vZ3LPffcs/1mfP+xCK4/quSlbe+tsGc+o+kvkvpykeN73Tx2OL/xjW8U6f0dzq5cfo8XgZDe8eI750tHdp/3vOcNrafv+L75zW8u66yzzkAZ3t3f/va35cwzz2yDF9C6gjvvvHMb7y+v2S7yPV1fiajyJ5xwQuFVlmfddddtZWuaIxbiE4JAEAgCy4BAsgSBaSGw4447tp8Y++EPf9ge1esW5kVrnzWr9qpeTz/99PKpT32qrLrqql3x9tvzjvX5Y0r9P8a0hGBuxopASO9Y4U3hQSAIBIEgEASCwHxEALH1QrevGfljSo7zLUs7OIP8EainPe1p5alPfeqyFJE8M4TAikl6Zwi8FBMEgkAQCAJBIAgsXAR8P95XhrbddtvC4zvVlu69995l6623Lr6I5B2a/h9cmmp5kZ8eAiG908MvuYNAEAgC8xaBVDwIBIGJEXBMwZEEn/Xk8fWi9cQ5/pfqyw/vfe97268g+SNMzvP+LzW/lgcCIb3LA/U8MwgEgSAQBIJAEJg3CNzvfvcre+yxR9l4441HrvOaa67ZnuXdZJNN2he0R84YwbEhMIT0ju15KTgIBIEgEASCQBAIAkEgCMw6AiG9sw55HhgEgsC8QSAVDQJBIAgEgQWDQEjvgunKNCQIBIEgEASCQBAIAjOPwEIpMaR3ofRk2hEEgkAQCAJBIAgEgSAwFIGQ3qHQJCEIBIHJEYhEEAgCQSAIBIH5gUBI7/zop9QyCASBIBAEgkAQmKsIpF7zAoGQ3nnRTalkEAgCQSAIBIEgEASCwHQQCOmdDnrJGwQmRyASQSAIBIEgEASCwBxAIKR3DnRCqhAEgkAQCAJBYGEjkNYFgeWPQEjv8u+D1CAIBIEgEASCQBAIAkFgzAiE9I4Z4BQ/OQKRCAJBIAgEgSAQBILAuBEI6R03wik/CASBIBAEgsDkCEQiCASBMSMQ0jtmgFN8EAgCQSAIBIEgEASCwPJHIKR3+ffB5DWIRBAIAkEgCASBIBAEgsC0EAjpnRZ8yRwEgkAQCAKzhUCeEwSCQBCYDgIhvdNBL3mDQBAIAkEgCASBIBAE5gUCC4T0zgusU8kgEASCQBAIAkEgCASB5YRASO9yAj6PDQJBIAjMOAIpMAgEgSAQBIYiENI7FJokBIEgEASCQBAIAkEgCMw3BIbVN6R3GDKJDwJBIAgEgSAQBIJAEFgwCIT0LpiuTEOCQBCYHIFIBIEgEASCwIqKQEjvitrzaXcQCAJBIAgEgSCwYiKwgrY6pHcF7fg0OwgEgSAQBIJAEAgCKxICIb0rUm+nrUFgcgQiEQSCQBAIAkFgQSIQ0rsguzWNCgJBIAgEgSAQBJYdgeRciAiE9C7EXk2bgkAQCAJBIAgEgSAQBJZAIKR3CThyEwQmRyASQSAIBIEgEASCwPxDIKR3/vVZahwEgkAQCAJBYHkjkOcHgXmHQEjvvOuyVDgIBIEgEASCQBAIAkFgqgiE9E4VschPjkAkgkAQCAJBIAgEgSAwxxAI6Z1jHZLqBIEgEASCwMJAIK0IAkFgbiEQ0ju3+iO1CQJBIAgEgSAQBIJAEBgDAiG9YwB18iIjEQSCQBAIAkEgCASBIDCbCIT0zibaeVYQCAJBIAj8D4H8CgJBIAjMIgIhvbMIdh4VBIJAEAgCQSAIBIEgsHwQmKukd/mgkacGgSAQBIJAEAgCQSAILEgEQnoXZLemUUEgCCwMBNKKIBAEgkAQmCkEQnpnCsmUEwSCQBAIAkEgCASBIDDzCMxQiSG9MwRkigkCQSAIBIEgEASCQBCYuwiE9M7dvknNgkAQmByBSASBIBAEgkAQGAmBkN6RYIpQEAgCQSAIBIEgEATmKgKp1ygIhPSOglJkgkAQCAJBIAgEgSAQBOY1Av8PAAD//1zei9YAAAAGSURBVAMAUebwTXRtcysAAAAASUVORK5CYII=\" width=\"701\" height=\"207\"\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical Modeling and Predictive Analytics\u003c/h2\u003e \u003cp\u003eMonthly aggregated data (Feb 2021-Dec 2023; n\u0026thinsp;=\u0026thinsp;34 observations) were analyzed. Given the limited number of time points relative to the potential predictors, modeling strategies prioritized parsimony and biological plausibility. To explore the nonlinear relationship between climatic drivers and poultry health, Spearman rank correlation (ρ) was applied to concurrent data and time-lagged variables (1, 2, and 3 months). Spearman\u0026rsquo;s rank correlation was chosen because the datasets are nonlinear and nonnormal (Zar \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). For each month, the total values for each condemnation cause were divided by the total number of slaughters in that month and multiplied by 100 to obtain percentage values, ensuring that correlations reflected condemnation proportions rather than total numbers. Additionally, because the effects of climatic variables on various aspects of poultry production may not be immediate (Kumar et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), heatmaps accounting for time lags of 1, 2, and 3 months were produced. Correlation coefficients with p-values less than 0.05 were considered statistically significant. All heatmaps were created using the R package corrplot (Wei and Simko \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo quantify the effects of climatic variables on the total condemnation rate and each of the 12 condemnation causes, as dependent variables, multiple linear regression models were initially fitted using R software version 4.3.3 (R Core Team \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The dependent variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(Y\\)\u003c/span\u003e\u003c/span\u003e, representing the condemnation rate for each cause, was modelled (Eq.\u0026nbsp;2) as a function of the concurrent and lagged (1-month) climatic variables: precipitation (mm, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{1}\\)\u003c/span\u003e\u003c/span\u003e), mean temperature (\u0026deg;C, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{2}\\)\u003c/span\u003e\u003c/span\u003e), mean humidity (%, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{3}\\)\u003c/span\u003e\u003c/span\u003e), heat index (a composite measure of temperature and humidity, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{4}\\)\u003c/span\u003e\u003c/span\u003e), the precipitation lag-1 (mm, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{5}\\)\u003c/span\u003e\u003c/span\u003e), mean temperature lag-1 (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{6}\\)\u003c/span\u003e\u003c/span\u003e, \u0026deg;C), mean humidity lag-1 (%, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{7}\\)\u003c/span\u003e\u003c/span\u003e), and heat index lag-1 (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{8}\\)\u003c/span\u003e\u003c/span\u003e). These variables were selected based on their relevance to slaughterhouse condemnations and prior Spearman correlation analyses. The maximum and minimum temperatures and humidities were excluded because they were highly correlated with their respective means, thereby reducing multicollinearity. Month and year were included as categorical control variables to account for seasonality and temporal trends, respectively. April was selected as the reference month because it is a transition season, with intermediate climatic conditions, and 2021 was selected as the reference year because it was the first year of analysis.\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$Y={\\beta}_{0}+\\sum_{\\text{i}=1}^{8}{\\beta}_{\\text{i}}{X}_{\\text{i}}+\\sum_{\\text{i}=1}^{11}{\\alpha}_{\\text{i}}{\\text{M}\\text{o}\\text{n}\\text{t}\\text{h}}_{\\text{i}}+\\sum_{\\text{i}=1}^{2}{\\gamma}_{\\text{i}}{\\text{Y}\\text{e}\\text{a}\\text{r}}_{\\text{i}}+ϵ\\left(2\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta}_{0}\\)\u003c/span\u003e\u003c/span\u003e is the intercept, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta}_{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e (i\u0026thinsp;=\u0026thinsp;1 to 8) are coefficients for the climatic variables, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\alpha}_{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e (i\u0026thinsp;=\u0026thinsp;1 to 11) are coefficients for the month levels, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\gamma}_{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e (i\u0026thinsp;=\u0026thinsp;1 to 2) are coefficients for the year levels, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(ϵ\\)\u003c/span\u003e\u003c/span\u003e is the residual error.\u003c/p\u003e \u003cp\u003eTo optimize model fit and select the most relevant predictors, stepwise regression was performed using the Akaike Information Criterion (AIC) with the stepAIC function from the MASS package (Venables and Ripley \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Predictors with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered significant, while those with p\u0026thinsp;\u0026lt;\u0026thinsp;0.1 were reported as marginally significant to capture potential trends relevant to slaughterhouse conditions. Model diagnostics included tests for normality of residuals (Shapiro-Wilk test), homoscedasticity (Breusch-Pagan test, using the lmtest package; Zeileis and Hothorn \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and multicollinearity (Variance Inflation Factor, VIF, using the car package; Fox and Weisberg \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Complete diagnostic results, including Shapiro-Wilk p-values, Breusch-Pagan statistics, and full VIF tables for all 13 models (TC\u0026thinsp;+\u0026thinsp;12 causes), are reported in Tables S3-S8. Moderate multicollinearity was observed in some stepwise models (e.g., VIF\u0026thinsp;\u0026gt;\u0026thinsp;5 for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{2}\\)\u003c/span\u003e\u003c/span\u003e up to 22.92 in total condemnation (TC) model; GVIF\u003csup\u003e(1/(2df))\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;4.5 in several; see Tables S3-S6). To address this, a robustness check using ridge regression (Zhang and Politis \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) confirmed consistent effect directions and significance for key predictors. Predictors with high VIFs were retained because of their biological relevance to poultry health, such as interactions between temperature and humidity (Nawab et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Post hoc power analysis (G*Power 3.1, Faul et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) confirmed\u0026thinsp;\u0026gt;\u0026thinsp;80% power for key predictors (e.g., lagged precipitation in arthritis (AR)/cellulitis (CE) models: n\u0026thinsp;=\u0026thinsp;34, effect size f\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.15, α\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eFor inflammatory lesions, the linear model violated assumptions (Shapiro-Wilk p\u0026thinsp;=\u0026thinsp;0.0769, Breusch-Pagan p\u0026thinsp;=\u0026thinsp;0.001, adjusted R\u003csup\u003e2\u003c/sup\u003e = \u0026minus;\u0026thinsp;0.471 in the base model), leading to the adoption of a generalized linear model (GLM) with quasibinomial distribution to account for the proportional nature of the data, heteroscedasticity, and potential non-normality. The GLM included the heat index, lag-1 heat index, and year, with a dispersion parameter estimated to account for overdispersion. Results were summarized using regression coefficients (β), standard errors, p-values, adjusted R\u003csup\u003e2\u003c/sup\u003e for linear models, or deviance reduction and dispersion parameters for the GLM. Detailed regression tables for all models are provided in Supplementary Tables (S3-S6).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Condemnation Patterns in the Representative Subtropical Hub\u003c/h2\u003e \u003cp\u003eBetween February 2021 and December 2023, the total condemnation rate (TC) in the intensive production hub of Santa Catarina, serving as a sentinel for humid subtropical regions, increased significantly, rising from an average of 13.1% in 2021 to 15.5% in 2023. The evolution of these rates is illustrated in a ridgeline plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), which displays a unimodal distribution in 2021 with low variability, transitioning to a bimodal distribution in 2022 and 2023, with seasonal peaks consistently appearing in the May-June window.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnalysis of the 12 primary causes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) revealed that gastrointestinal contamination (GC, 5.0%) and skin lesions (SL, 3.5%) were the dominant drivers of rejection. Other significant contributors included arthritis (AR, 1.3\u0026ndash;2.3%), airsacculitis (AI, 0.2\u0026ndash;1.4%), processing failures (PF, 0.7\u0026ndash;0.9%), and cellulitis (CE, ~\u0026thinsp;0.7%). Contamination and skin-related rejections remain the primary technological bottlenecks, consistent with findings from other high-density production hubs in Southern Brazil (Kanabata et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Muchon et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Descriptive statistics for annual production and condemnation rates are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \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\u003eDescriptive statistics for selected condemnation causes and the number of slaughters\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAnimals Slaughtered (Million)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e68.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCondemnation Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1424\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1647\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGastrointestinal Contamination Proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0535\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0527\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0548\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSkin Lesions Proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eArthritis Proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0236\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Environmental Dynamics and Time-Lagged Correlations\u003c/h2\u003e \u003cp\u003eThe behavior of climatic variables during the study period, including significant surges in precipitation and high relative humidity, is displayed in time-series plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Spearman rank correlation analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) identified that the influence of the subtropical environment on poultry health is often characterized by significant time lags. While concurrent temperature showed a weak positive correlation with TC (ρ\u0026thinsp;=\u0026thinsp;0.24), lagged relative humidity at 2 months exhibited a much stronger positive association (ρ\u0026thinsp;=\u0026thinsp;0.52, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as shown in the supplementary heatmaps (Figs. S1-S3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePathology-specific correlations further highlighted the role of seasonal stressors in Cfa climates:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAirsacculitis (AI): Positively correlated with mean, maximum, and minimum temperatures (ρ\u0026thinsp;=\u0026thinsp;0.22\u0026ndash;0.24, p\u0026thinsp;=\u0026thinsp;0.02) without lag (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and at a 1-month lag (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAscites (AS): Strongly associated with winter conditions, showing a negative correlation with temperature range without lag (ρ = \u0026minus;\u0026thinsp;0.55, p\u0026thinsp;=\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eArthritis (AR) and Cellulitis (CE): Demonstrated delayed responses to environmental moisture, with AR showing positive correlations with precipitation and humidity at 1 to 3-month lags (Figs. S1-S3).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Predictive Modeling of Climatic Stressors\u003c/h2\u003e \u003cp\u003eStepwise multiple linear regression and Generalized Linear Models (GLM) quantified the magnitude of environmental drivers while controlling for temporal effects (see results in Tables S4-S6). Ridge regression confirmed consistent effect directions for key predictors.\u003c/p\u003e \u003cp\u003eThe model for Ascites (AS) demonstrated exceptional robustness (adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.975), driven by the negative effects of mean temperature (β = \u0026minus;\u0026thinsp;0.021) and heat index (β = \u0026minus;\u0026thinsp;0.008), confirming the cold-stress axis typical of subtropical winters. For inflammatory lesions (IL), the quasibinomial GLM successfully addressed overdispersion and heteroscedasticity, identifying the lagged heat index (β = \u0026minus;\u0026thinsp;0.096) as a significant environmental predictor. This suggests that warmer conditions in the month prior to slaughter mitigate immune-mediated pathologies.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.1. The Subtropical Paradigm and Environmental Dynamics\u003c/h2\u003e \u003cp\u003eThe observed total condemnation rates in this study are higher than those reported for previous decades in Brazilian industrial poultry clusters (Muchon et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), reflecting the cumulative impact of production intensification and the evolving sensitivity of Federal Inspection Service (SIF) protocols. The increase in broiler carcass condemnation rates from 13.1% in 2021 to 15.5% in 2023 underscores a growing challenge for intensive poultry systems in humid subtropical regions (Kpomasse et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The transition to a bimodal distribution in 2022 and 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), with consistent peaks in the May-June window, identifies a seasonal vulnerability tied to the climatic characteristics of K\u0026ouml;ppen-Geiger Cfa and Cfb zones (Alvares et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These agro-ecological zones, characterized by high relative humidity and significant thermal amplitude, mirror production conditions in the Southeastern United States, Southern China, and Eastern Australia, making these findings globally representative (Peel et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Thobe et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile global broiler condemnation rates are often reported around 1.04% for total rejection in some regions, the high rates observed here (reflecting the sum of partial and total rejections) highlight the sensitivity of high-performance genetic strains to environmental stressors in the subtropics (Salines et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Belintani et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The significant \u0026ldquo;year effects\u0026rdquo; identified in the regression models for 2022 and 2023 suggest that, beyond climate, operational factors such as refined inspection protocols or changes in slaughter-line technology are influencing the data trends.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Delayed Environmental Effects on Health Causes\u003c/h2\u003e \u003cp\u003eA novel contribution of this study is the identification of the temporal dimension of poultry rejections. Gastrointestinal contamination (GC, 5.0%), the leading cause of rejection, exhibited strengthened correlations with temperature at 2- and 3-month lags (ρ\u0026thinsp;=\u0026thinsp;0.62\u0026ndash;0.63, p\u0026thinsp;=\u0026thinsp;0.02; Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Unlike previous studies focusing on slaughter-day weather, this suggests that environmental conditions during the early rearing phases influence the microbial load or intestinal integrity of the birds at the end of the cycle (Rouger et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor inflammatory lesions (IL), the use of a Generalized Linear Model (GLM) with a quasibinomial distribution was essential to handle the overdispersion of proportional data (Table S6). The identification of the lagged heat index (β = \u0026minus;\u0026thinsp;0.096, p\u0026thinsp;=\u0026thinsp;0.051) as a predictor suggests that warmer conditions in the month prior to slaughter may mitigate cold-induced immune stress and reduce the subsequent metabolic demand (Bohler et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.3. The Moisture-Litter-Lesion Axis\u003c/h2\u003e \u003cp\u003eArthritis (AR) and cellulitis (CE) were significantly predicted by lagged precipitation (β\u0026thinsp;=\u0026thinsp;0.002) and mean humidity (β = \u0026minus;\u0026thinsp;0.038 to \u0026minus;\u0026thinsp;0.027; Table S4). In humid subtropical agro-ecologies, heavy rainfall surges lead to \u0026ldquo;moist litter\u0026rdquo; or caking, which increases ammonia levels and facilitates the entry of pathogens like \u003cem\u003eMycoplasma\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e into the joints and subcutaneous tissues. The delay of 1\u0026ndash;3 months between high moisture events and carcass rejection confirms that litter quality early in the flock\u0026rsquo;s life dictates final carcass quality.\u003c/p\u003e \u003cp\u003eSimilarly, skin lesions (SL) were negatively correlated with temperature range (ρ = \u0026minus;\u0026thinsp;0.66) and positively with humidity (ρ\u0026thinsp;=\u0026thinsp;0.31\u0026ndash;0.38; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These results align with findings from high-rainfall regions in Southeast Asia, where high stocking densities combined with sustained humidity exacerbate contact dermatitis (Kang et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Metabolic Stress and Thermoregulation\u003c/h2\u003e \u003cp\u003eAscites (AS) showed an exceptionally robust fit (adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.975), driven primarily by cold stress (negative effects of mean temperature and heat index; Table S5) (Wideman et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In the Southern Hemisphere winter, low temperatures increase the metabolic demand for oxygen to maintain thermogenesis (Kumar et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Moreira et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In rapidly growing broilers, this leads to pulmonary arterial hypertension and abdominal fluid accumulation, a pattern also documented in temperate-subtropical transition zones worldwide (Wideman et al. 2113; Belintani et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAirsacculitis (AI) peaked at 1.4% in 2023, showing a positive correlation with concurrent temperature (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This indicates that warmer conditions may exacerbate the effects of respiratory pathogens, possibly through increased dust levels or poor air quality during periods of low ventilation aimed at heat conservation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Economic and Sustainability Implications\u003c/h2\u003e \u003cp\u003eWith an estimated annual financial loss of US\u003cspan\u003e$\u003c/span\u003e 150,000 per processing facility, carcass rejections represent a significant \u0026ldquo;leakage\u0026rdquo; in the protein value chain (Salines et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Azizpour and Amirajam \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Reducing these losses directly contributes to the United Nations Sustainable Development Goals, specifically Zero Hunger (SDG 2) and Responsible Consumption and Production (SDG 12), by decreasing food waste and improving the environmental footprint per kilogram of meat produced (McManus et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Limitations and Future Directions\u003c/h2\u003e \u003cp\u003eReliance on meteorological data from a single station may limit generalizability to mountainous microclimates within the region. Additionally, the model did not include farm-level variables such as stocking density, vaccination protocols, or specific genetic lineages, like Ross 308 or Hubbard, which are known to mediate environmental sensitivity.\u003c/p\u003e \u003cp\u003eFuture research should expand the geographic scope by incorporating grid-based climatic data and utilize machine learning algorithms, such as random forest or ARIMA models, to improve predictive accuracy for seasonal peaks. Including One Health indicators, such as the phylogenetic profiling of \u003cem\u003eE. coli\u003c/em\u003e in condemned carcasses, could further link environmental management with public health safety.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.7. Conclusion\u003c/h2\u003e \u003cp\u003eThis study demonstrates that broiler carcass condemnation patterns are influenced by both concurrent climatic conditions and environmental factors from earlier production phases. Specifically, cold stress increased ascites rates (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while lagged precipitation/humidity drove inflammatory and joint lesions (p\u0026thinsp;\u0026le;\u0026thinsp;0.05). Given this ecological/regional study design, findings represent associations rather than causation. Nevertheless, results provide actionable insights for anticipating seasonal risks and optimizing management in humid subtropical poultry systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure Statement\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003cp\u003eEthical Compliance\u003c/p\u003e \u003cp\u003e Compliance with ethical standards was strictly maintained. The manuscript does not contain clinical studies or direct experimentation with human or animal subjects. All data were retrieved from official secondary records provided by governmental sanitary inspection services, ensuring anonymity and adherence to international guidelines for epidemiological reporting.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was funded by Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior - CAPES (ASL, Financial Code 001) and Funda\u0026ccedil;\u0026atilde;o de Apoio \u0026agrave; Pesquisa e Inova\u0026ccedil;\u0026atilde;o do Estado de Santa Catarina - FAPESC (GFSB for the grant and ACG for project number 2025TR1577).\u003c/p\u003e\u003ch2\u003eAuthors Contributions\u003c/h2\u003e \u003cp\u003eAll authors contributed to equally to the study and to the final version of the manuscript. Moreover, all authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors express their gratitude to Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior - CAPES (ASL, Financial Code 001) and Funda\u0026ccedil;\u0026atilde;o de Apoio \u0026agrave; Pesquisa e Inova\u0026ccedil;\u0026atilde;o do Estado de Santa Catarina - FAPESC (GFSB for the grant and ACG for project number 2025TR1577).\u003c/p\u003e\u003ch2\u003eData Availability Statement\u003c/h2\u003e \u003cp\u003eThe data that support the findings of this study are available from the corresponding author, WSR, upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlvares CA, Stape JL, Sentelhas PC, Gon\u0026ccedil;alves JLM, Sparovek G (2013) K\u0026ouml;ppen\u0026rsquo;s climate classification map for Brazil. Meteorol Z 22(6):711\u0026ndash;728. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1127/0941-2948/2013/0507\u003c/span\u003e\u003cspan address=\"10.1127/0941-2948/2013/0507\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzizpour A, Amirajam Z (2024) Causes for carcass condemnations of slaughtered poultry in the industrial slaughterhouse of Namin, Ardabil province, Iran. Iran J Vet Sci Technol 16:1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.22067/IJVST.2024.82675.1260\u003c/span\u003e\u003cspan address=\"10.22067/IJVST.2024.82675.1260\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBelintani RT, Garcia RG, Gil JLRS, de Alencar N\u0026auml;\u0026auml;s I, Gandra ERS, de Cassia Komiyama C., Caldara FR (2019) Broiler carcass condemnation pattern during processing. Rev Bras Zootec 48:e20180046. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/rbz4820180046\u003c/span\u003e\u003cspan address=\"10.1590/rbz4820180046\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBohler MW, Chowdhury VS, Cline MA, Gilbert ER (2021) Heat stress response in birds: a review of the neural components. Biology 10:1095. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/biology10111095\u003c/span\u003e\u003cspan address=\"10.3390/biology10111095\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuzdugan SN, Chang YM, Huntington B, Rushton J, Guitian J, Alarcon P, Blake DP (2020) Identification of production chain risk factors for slaughter condemnation of broiler chickens. Prev Vet Med 181:105036. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.prevetmed.2020.105036\u003c/span\u003e\u003cspan address=\"10.1016/j.prevetmed.2020.105036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarvalho FES, Salle FO, Borges KA, Carvalho KBM, Furian TQ, Salle CTP (2025) Carcass condemnation prediction using artificial neural networks in poultry slaughterhouses. Res Vet Sci 196:105884. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.rvsc.2025.105884\u003c/span\u003e\u003cspan address=\"10.1016/j.rvsc.2025.105884\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChaiban C, Robinson TP, F\u0026egrave;vre EM, Ogola J, Akoko J., Gilbert M, Vanwambeke SO (2020) Early intensification of backyard poultry systems in the tropics: a case study. Animals 14(11):2387\u0026ndash;2396. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S175173112000110X\u003c/span\u003e\u003cspan address=\"10.1017/S175173112000110X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFaul F, Erdfelder E, Lang A-G, Buchner A (2007) G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39(2):175\u0026ndash;191. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/BF03193146\u003c/span\u003e\u003cspan address=\"10.3758/BF03193146\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFox J, Weisberg S (2019) An R Companion to Applied Regression. 3rd Edition. Sage.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHort\u0026ecirc;ncio MC, Costa LRM, Souza MVP, Freitas WD, Fonseca BB, Silva MJB, Cossi MVC (2022) Time series evaluation of condemnation at poultry slaughterhouses enable to export in Southeastern Brazil (2009\u0026ndash;2019): a tool for optimizing resources in the poultry production chain. BMC Vet Res 18:427. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12917-022-03521-z\u003c/span\u003e\u003cspan address=\"10.1186/s12917-022-03521-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu JY, Cheng HW (2021) Warm perches: a novel approach for reducing cold stress effect on production, plasma hormones, and immunity in laying hens. Poult Sci 100(8):101294. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.psj.2021.101294\u003c/span\u003e\u003cspan address=\"10.1016/j.psj.2021.101294\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanabata BT, Souza FL, Biz G, Pescim RR, Soares AL (2023) Relationship between pre-slaughter factors and major causes of carcass condemnation in a broiler slaughterhouse under federal inspection. Braz J Poult Sci 25:1\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/1806-9061-2022-1669\u003c/span\u003e\u003cspan address=\"10.1590/1806-9061-2022-1669\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKang S, Kim DH, Lee S, Lee T, Lee KW, Chang HH, Moon B, Ayasan T, Chi YH (2020) An acute, rather than progressive, increase in temperature-humidity index has severe effects on mortality in laying hens. Front Vet Sci 7:568093. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fvets.2020.568093\u003c/span\u003e\u003cspan address=\"10.3389/fvets.2020.568093\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarlsson L, Keeling L, R\u0026ouml;\u0026ouml;s E (2025) What is a better chicken? Exploring trade-offs between animal warfare and greenhouse gas emissions in higher-welfare broiler systems. Sustain Prod Consump 55:203\u0026ndash;216. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.spc.2025.02.015\u003c/span\u003e\u003cspan address=\"10.1016/j.spc.2025.02.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKpomasse CC, Oke OE, Houndonougbo FM, Tona K (2021) Broiler production challenges in the tropics: A review. Vet Med Sci 7(3):831\u0026ndash;842. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/vms3.435\u003c/span\u003e\u003cspan address=\"10.1002/vms3.435\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar M, Ratwan P, Dahiya SP, Nehra AK (2021) Climate change and heat stress: impact on production, reproduction and growth performance of poultry and its mitigation using genetic strategies. J Therm Biol 97:102867. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jtherbio.2021.102867\u003c/span\u003e\u003cspan address=\"10.1016/j.jtherbio.2021.102867\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu L, Ren M, Ren K, Jin Y, Yan M (2020) Heat stress impacts on broiler performance: a systematic review and meta-analysis. Poult Sci 99(11):6205\u0026ndash;6211. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.psj.2020.08.019\u003c/span\u003e\u003cspan address=\"10.1016/j.psj.2020.08.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMAPA, 2017. Ministry of Agriculture, Livestock and Food Supply. Decree No. 9,013, of March 29, 2017. Regulamento de Inspe\u0026ccedil;\u0026atilde;o Industrial e Sanit\u0026aacute;ria de Produtos de Origem Animal (RIISPOA). Di\u0026aacute;rio Oficial da Uni\u0026atilde;o, Bras\u0026iacute;lia, Brazil.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcManus C, Louren\u0026ccedil;o-Silva J, Paim TP, Oliveira F., Giannoni-Guzm\u0026aacute;n MA (2023) Tropical Animal Health and Production: a 55-year bibliographic analysis setting the course for a globalized international reference journal. Trop Anim Health Prod 55:160. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11250-023-03577-5\u003c/span\u003e\u003cspan address=\"10.1007/s11250-023-03577-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeteyake HT, Bilalissi A, Oke OE, Voemesse K, Tona K (2020) Effect of thermal manipulation during incubation and heat challenge during the early juvenile stage on production parameters of broilers reared under a tropical climate. Eur Poult Sci 84:1\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1399/eps.2020.318\u003c/span\u003e\u003cspan address=\"10.1399/eps.2020.318\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoreira LM, Sousa LS, Guam\u0026aacute;n CAG, Vieira MC, Santini MB, Cardoso AR, Leme FOP, Lara LJC, Ara\u0026uacute;jo ICS (2024) Effects of cold stress on physiologic metabolism in the initial phase and performance of broiler rearing. J Therm Biol 119:103773. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jtherbio.2023.103773\u003c/span\u003e\u003cspan address=\"10.1016/j.jtherbio.2023.103773\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMottet A, Tempio G (2017) Global poultry production: current state and future outlook and challenges. Worlds Poult Sci J 73(2):245\u0026ndash;256. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0043933917000071\u003c/span\u003e\u003cspan address=\"10.1017/S0043933917000071\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuchon JL, Garcia RG, Gandra ERS, Assun\u0026ccedil;\u0026atilde;o ASA, Komiyama CM, Caldara FR, N\u0026auml;\u0026auml;s IA, Santos RA (2019) Origin of broiler carcass condemnations. Rev Bras Zootec 48:e20180249. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/rbz4820180249\u003c/span\u003e\u003cspan address=\"10.1590/rbz4820180249\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNawab A, Ibtisham F, Li G, Kieser B, Wu J, Liu W, Zhao Y, Nawab Y, Li K, Xiao M, An L (2018) Heat stress in poultry production: Mitigation strategies to overcome the future challenges facing the global poultry industry. J Therm Biol 78:131\u0026ndash;139. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jtherbio.2018.08.010\u003c/span\u003e\u003cspan address=\"10.1016/j.jtherbio.2018.08.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNawaz AH, Amoah K, Leng QY, Zheng JH, Zhang WL, Zhang L (2021) Poultry response to heat stress: Its physiological, metabolic, and genetic implications on meat production and quality including strategies to improve broiler production in a warming world. Front Vet Sci 8:699081. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fvets.2021.699081\u003c/span\u003e\u003cspan address=\"10.3389/fvets.2021.699081\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeel MC, Finlayson BL, McMahon TA (2007) Updated world map of the K\u0026ouml;ppen-Geiger climate classification. Hydrol Earth Syst Sci 11(5):1633\u0026ndash;1644. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/hess-11-1633-2007\u003c/span\u003e\u003cspan address=\"10.5194/hess-11-1633-2007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePirompud P, Sivapirunthep P, Punyapornwithaya V, Chaosap C (2023) Preslaughter handling factors affecting dead on arrival, condemnations, and bruising in broiler chickens raised without an antibiotic program. Poult Sci 102(8):102828. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.psj.2023.102828\u003c/span\u003e\u003cspan address=\"10.1016/j.psj.2023.102828\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePirompud P, Sivapirunthep P, Punyapornwithaya V, Chaosap C (2024) Machine learning predictive modeling for condemnation risk assessment in antibiotic-free raised broilers. Poult Sci 103(12):104270. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.psj.2024.104270\u003c/span\u003e\u003cspan address=\"10.1016/j.psj.2024.104270\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR Core Team (2024) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.R-project.org/\u003c/span\u003e\u003cspan address=\"https://www.R-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRouger A, Tresse O, Zagorec M (2017) Bacterial contaminants of poultry meat: sources, species, and dynamics. Microorganisms 5:50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/microorganisms5030050\u003c/span\u003e\u003cspan address=\"10.3390/microorganisms5030050\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalines M, Allain V, Roul H, Magras C, Le Bouquin S (2017) Rates of and reasons for condemnation of poultry carcases: harmonised methodology at the slaughterhouse. Vet Rec 180(21):516. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/vr.104000\u003c/span\u003e\u003cspan address=\"10.1136/vr.104000\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSteadman RG (1979) The assessment of sultriness. Part I: A temperature-humidity index based on human physiology and clothing science. J Appl Meteorol 18(7):861\u0026ndash;873. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/1520-0450(1979)018%3C0861:TAOSPI%3E2.0.CO;2\u003c/span\u003e\u003cspan address=\"10.1175/1520-0450(1979)018%3C0861:TAOSPI%3E2.0.CO;2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThobe P, Chibanda C, Almadani MI, Koch S (2025) Chicken meat production in global comparison \u0026ndash; production systems and economics. Stud Agric Econ 127:220\u0026ndash;227. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7896/j.3313\u003c/span\u003e\u003cspan address=\"10.7896/j.3313\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVenables WN, Ripley BD (2022) Modern Applied Statistics with S. 4th ed. Springer, New York. ISBN: 0-387-95457-0\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei T, Simko V (2024) R package \u0026lsquo;corrplot\u0026rsquo;: Visualization of a correlation matrix (version 0.95). Available from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/taiyun/corrplot\u003c/span\u003e\u003cspan address=\"https://github.com/taiyun/corrplot\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWideman RF, Rhoads DD, Erf GF, Anthony NB (2013) Pulmonary arterial hypertension (ascites syndrome) in broilers: A review. Poult Sci 92(1):64\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3382/ps.2012-02745\u003c/span\u003e\u003cspan address=\"10.3382/ps.2012-02745\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZar JH (2010) Biostatistical Analysis, 5th Edition. Prentice Hall.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeileis A, Hothorn T (2022) Diagnostic checking in regression relationships. R News 2(3):7\u0026ndash;10\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Politis, DN (2022) Ridge regression revisited: debiasing, thresholding and bootstrap. Ann Stat 50(3):1401\u0026ndash;1422. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1214/21-AOS2156\u003c/span\u003e\u003cspan address=\"10.1214/21-AOS2156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"carcass condemnation, broiler production, climatic variability, lagged effects, poultry health","lastPublishedDoi":"10.21203/rs.3.rs-9003534/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9003534/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntensive poultry production in humid subtropical agro-ecologies faces unique environmental challenges that compromise carcass quality, welfare, and food security. While climatic influences are recognized, the temporal dimensions of these effects remains largely underexplored. This study quantified the immediate and time-lagged (1\u0026ndash;3 months) influences of climatic variables on 12 causes of broiler carcass condemnation in a representative subtropical hub. Longitudinal data (2021\u0026ndash;2023) from federally inspected slaughterhouses in Santa Catarina, Brazil, a global sentinel for K\u0026ouml;ppen Cfa and Cfb climate zones, were analyzed using Spearman rank correlation and advanced regression models, including Generalized Linear Models (GLM) with a quasibinomial distribution. Total condemnation rates rose from 13.1% in 2021 to 15.5% in 2023, dominated by gastrointestinal contamination (5.0%) and skin lesions (3.5%). Regression analysis revealed that lagged precipitation was a significant predictor for arthritis and cellulitis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas higher temperatures and heat index reduced rejections for ascites and skin lesions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). A quasibinomial GLM identified lagged heat index (β = \u0026minus;\u0026thinsp;0.096, p\u0026thinsp;=\u0026thinsp;0.051) as a critical driver for inflammatory lesions. These findings demonstrate that avian health in intensive systems is governed by a temporal environmental paradigm where conditions during early rearing phases dictate final carcass quality. The established predictive models offer an extrapolatable blueprint for seasonal management across global humid subtropical belts to mitigate economic leakages and enhance production sustainability.\u003c/p\u003e","manuscriptTitle":"Environmental Drivers of Broiler Carcass Condemnation in Humid Subtropical Regions: A Predictive Model Incorporating Lagged Climatic Effects","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-15 09:29:30","doi":"10.21203/rs.3.rs-9003534/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-03-13T23:06:49+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-11T12:48:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-05T03:58:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Animal Health and Production","date":"2026-03-02T06:57:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1ec671f0-af1f-4884-9f66-a0b53f3fd871","owner":[],"postedDate":"March 15th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T14:11:11+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-15 09:29:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9003534","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9003534","identity":"rs-9003534","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}