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Temperature and Relative Humidity Drive Leaf Rust and Stripe Rust Incidence and Severity in Wheat Across Major Wheat-Growing Districts of Punjab, Pakistan

A 2024–2025 study across major wheat-growing districts in Punjab, Pakistan, determined that rising temperatures are the primary driver of leaf and stripe rust incidence and severity, while relative humidity had minimal impact, underscoring the need for temperature-based forecasting and resistant cultivars like Fareed-06 for effective disease management.

Original authors: Adil Zia, Muhammad Usman, Safdar Ali, Muhammad Kamran, Sajid Aleem Khan, Muhammad Ehetisham-Ul-Haq, Usama Ahmad, Shehla Riaz, Huma Abbas

Published 2026-08-05

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CC BY 4.0

Original authors: Adil Zia, Muhammad Usman, Safdar Ali, Muhammad Kamran, Sajid Aleem Khan, Muhammad Ehetisham-Ul-Haq, Usama Ahmad, Shehla Riaz, Huma Abbas

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the world of farming as a giant, open-air kitchen where the most important ingredient is wheat. This golden grain feeds billions of people, acting as the foundation for bread, pasta, and countless other foods that keep the global population going. But in this kitchen, there are invisible chefs trying to ruin the meal: tiny, microscopic fungi called rusts. Specifically, there are two troublemakers known as leaf rust and stripe rust. They don't cook; they infect. They land on wheat leaves, turn them brown or yellow with tiny pustules, and steal the plant's energy, causing the harvest to shrink.

For farmers, knowing when these fungal chefs are going to strike is a matter of survival. Usually, they look at the weather to guess. Two big weather factors have always been the suspects: temperature (how hot or cold it is) and relative humidity (how much water vapor is hanging in the air). Think of temperature as the thermostat that turns the fungi's engines on or off, and humidity as the water supply they need to drink to grow. The big question scientists have been asking is: which one is the real boss? Is it the heat that wakes the rust up, or is it the moisture that lets it spread? Understanding this helps farmers decide when to spray medicine on their crops or which types of wheat to plant so they don't get sick.

This new study, conducted across the major wheat-growing districts of Punjab in Pakistan, decided to play detective with real-world data from the 2024–2025 growing season. The researchers, led by a team from the University of Agriculture Faisalabad, set out to see exactly how temperature and humidity drive the spread of leaf rust and stripe rust. They didn't just guess; they went into 20 different wheat fields across eight districts, checking the plants at three critical stages of their growth, from when they are just sprouting to when they are filling out their grains. They looked at three popular wheat varieties: Akbar-19, MH-21, and Fareed-06.

Using a mathematical tool called multiple linear regression (which is like a super-accurate calculator that figures out how much one thing changes when another thing changes), the team crunched the numbers. The results were surprisingly clear. Temperature turned out to be the undisputed captain of the ship. The data showed that for every single 1°C increase in temperature, the amount of disease (both how many plants got sick and how sick they got) jumped significantly. In some districts, a tiny 1°C rise caused disease levels to shoot up by as much as 12.7 percentage points. It was a strong, consistent relationship: hotter weather meant more rust.

On the other hand, relative humidity was mostly a bystander. Despite the common belief that moisture is essential for these fungi, the study found that humidity had almost no significant effect on the disease in most of the districts they surveyed. The numbers showed that humidity wasn't the driver; it was the temperature pulling the strings. The researchers also discovered that not all wheat varieties reacted the same way. The variety named Akbar-19 was the most sensitive, acting like a canary in a coal mine that screamed "danger" at the slightest temperature change. In contrast, Fareed-06 was much tougher, showing lower levels of disease even when the weather got hot.

The study concludes that while both factors matter in theory, in the real-world conditions of Punjab, temperature is the main engine driving these rust epidemics. The authors suggest that this means farmers and scientists should focus on building models that predict disease based on heat, rather than just looking for rain or humidity. They also emphasize that planting resistant varieties like Fareed-06 is a smart move. While the study didn't claim to have solved the problem forever, it provided a very clear map of how heat is currently fueling these fungal outbreaks, offering a vital clue for managing wheat crops in a warming world.

Technical Summary: Temperature and Relative Humidity Drive Leaf Rust and Stripe Rust Incidence and Severity in Wheat Across Major Wheat-Growing Districts of Punjab, Pakistan

Problem Statement
Wheat (Triticum aestivum L.) is the principal staple crop in Pakistan, with the Punjab province contributing approximately 75% of the national production. However, wheat productivity is increasingly threatened by biotic stresses, specifically leaf rust (Puccinia triticina) and stripe rust (Puccinia striiformis f. sp. tritici). These fungal diseases can cause yield losses of up to 40% in susceptible cultivars under favorable conditions. While previous research has focused on pathogen diversity, host resistance, and fungicide efficacy, there is a limited understanding of how specific climatic factors—particularly temperature and relative humidity—quantitatively influence disease incidence and severity across the diverse agro-climatic zones of Punjab. Furthermore, the rapid evolution of pathogen races and the shifting climate necessitate region-specific data to improve disease forecasting and management strategies.

Methodology
The study was conducted during the 2024–2025 Rabi cropping season (November 2024 to April 2025) across eight major wheat-growing districts in Punjab, representing Northern (Mandi Bahauddin, Kasur), Central (Faisalabad, Toba Tek Singh), and Southern (Lodhran, Bahawalpur, Bahawalnagar, Sadiqabad/Rahim Yar Khan) agro-climatic zones.

Sampling Design: A systematic random sampling approach was employed, surveying 20 wheat fields per district (160 fields total). Fields were selected with a minimum 5 km separation to ensure independence.
Growth Stages: Assessments were conducted at three critical phenological stages: Tillering (GS 20–29), Stem elongation to heading (GS 30–59), and Flowering to grain filling (GS 60–79).
Cultivars: The survey included commercially cultivated varieties: Akbar-19, MH-21, and Fareed-06.
Disease Assessment: Disease incidence (percentage of infected plants) and severity (percentage of leaf area covered by pustules) were measured using the Modified Cobb Scale and standard CIMMYT protocols.
Environmental Data: Daily mean temperature and relative humidity data were obtained from the nearest Automatic Weather Stations (AWS) of the Pakistan Meteorological Department.
Statistical Analysis: Multiple linear regression models were used to quantify the relationship between climatic variables (Temperature, $T$ ; Relative Humidity, $RH$) and disease parameters ( $Y$ ). The model structure was $Y = \beta_0 + \beta_1T + \beta_2RH + \varepsilon$ . Model robustness was evaluated using $R^2$ , $P$ -values, and Variance Inflation Factor (VIF) to check for multicollinearity.

Key Results

District-Level Analysis (Leaf Rust):
- Temperature: A statistically significant positive correlation was observed between temperature and leaf rust incidence and severity across all eight districts. Regression coefficients ( $\beta$ ) for temperature ranged from 7.15 to 12.61 for incidence and 3.48 to 7.78 for severity. This indicates that for every 1°C increase in temperature, disease incidence increased by approximately 4.3–12.7 percentage points, and severity increased by 3.5–7.8%, depending on the district.
- Relative Humidity: Relative humidity showed no statistically significant effect on leaf rust incidence or severity in any of the district-level models ( $P > 0.05$ ).
- Model Performance: Models for Kasur, Toba Tek Singh, and Faisalabad demonstrated the highest explanatory power ( $R^2$ up to 74.43% for incidence).
District-Level Analysis (Stripe Rust):
- Temperature: Temperature was identified as the primary driver for stripe rust incidence and severity. Significant positive associations were found in most districts, with $\beta$ values for incidence ranging from 4.29 to 12.70.
- Relative Humidity: Similar to leaf rust, relative humidity had a negligible and statistically insignificant impact on stripe rust development in the district-level models.
- Model Performance: Explanatory power ( $R^2$ ) ranged from 48.59% to 69.72%, with Mandi Bahauddin showing the highest correlation for incidence.
Cultivar-Specific Analysis:
- Susceptibility Gradient: Among the three cultivars, Akbar-19 exhibited the highest sensitivity to climatic variables, showing the largest regression coefficients for both temperature and humidity regarding both incidence and severity. MH-21 showed intermediate sensitivity, while Fareed-06 demonstrated the lowest coefficients, indicating greater stability and tolerance to environmental fluctuations.
- Model Fit: For stripe rust, the regression models explained a high proportion of variance (up to 88.69% for Akbar-19 incidence), whereas leaf rust models explained moderate variance (approx. 50–58%).

Key Contributions and Claims
The paper claims to be the first comprehensive district-scale assessment in Punjab that simultaneously quantifies the influence of temperature and relative humidity on both leaf and stripe rust using multiple linear regression. The primary contributions include:

Identification of the Primary Driver: The study definitively establishes temperature as the dominant climatic factor driving wheat rust epidemics in Punjab, while finding relative humidity to be insignificant under the prevailing semi-arid conditions.
Regional Variability: The research highlights significant spatial heterogeneity in disease response to temperature, with districts like Kasur and Toba Tek Singh showing higher sensitivity than southern districts like Rahim Yar Khan.
Cultivar Performance: The study provides empirical evidence ranking the susceptibility of major commercial cultivars, identifying Akbar-19 as the most vulnerable and Fareed-06 as the most resilient to temperature-driven disease pressure.

Significance
The authors assert that these findings provide a scientific basis for integrating temperature-based forecasting models into routine wheat disease surveillance systems. By identifying temperature as the key predictor, the study supports the development of early warning systems to optimize fungicide application and guide the deployment of resistant cultivars. The results are particularly relevant for climate-smart disease management, suggesting that as global temperatures rise, the frequency and severity of rust epidemics in Punjab are likely to increase, necessitating a shift toward durable resistance strategies and climate-adaptive management protocols. The study concludes that while resistance genes are vital, their deployment must be informed by local climatic drivers to ensure sustainable wheat production.

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