Predicting germination and emergence patterns of Leptochloa chinensis using population based threshold models

Abstract

Background Leptochloa chinensis, a widespread weed in rice fields, can cause up to 40% crop loss and thrives in both dry and flooded conditions. Managing this weed ecologically is a major challenge. One promising approach is using population-based threshold models to predict when and where weed seed will emerge, helping farmers to control its spread more effectively.

Objective This study focused on predicting the germination and emergence behavior of L. chinensis seeds in rice-wheat cropping systems under various conditions.

Methods The seeds were exposed to different environmental conditions. The experiments spanned a wide range of temperatures, water potentials, light and soil depths.

Results Highest germination percentage was observed at temperatures between 25 and 30 °C, and at a water potential of 0 to -0.3 MPa. The base and ceiling temperatures recorded for L. chinensis seeds was 12.7 and 43.6 °C while the base water potential was -0.41 MPa. Light was not essential for germination but continuous darkness can hinder the process. Seeds exposed to 24 hours of darkness tended to have lower germination rates compared to those exposed to 12 hours of light. Similarly, greatest emergence was recorded when seeds were sown on the soil surface, with a decrease in emergence as the planting depth increased, and no emergence was observed at a depth of 5 cm.

Conclusion The models used in this study reliably predicted the germination and emergence patterns of L. chinensis across different environmental conditions, offering a valuable tool for enhancing weed management strategies in rice fields under changing climate.

1.Introduction

A major limitation of rice-wheat cropping system is weed infestations which greatly reduce productivity of this system by reducing crop yield and grain quality. If left unmanaged, weed infestations can lead to crop yield losses of up to 80% (Nawaz et al., 2019). In rice specifically, weeds and the region’s climate can result in yield losses of up to 46% (Guleria et al., 2018). Weeds are a major consideration for the effective management of all land and water resources, but their impact is greatest on agriculture (Singh et al., 2015).

Chinese sprangletop (Leptochloa chinensis), a C₄ grass native to tropical Asia, poses a significant threat to direct-seeded rice cultivation worldwide. The exceptional resilience of the plant is attributed to its ability to thrive in conditions of both waterlogging and drought (Chauhan, David, 2011). In water-scarce fields, weeds can compete with crops for available water, leading to water stress in the crops. The shift to direct-seeded rice systems creates a favourable environment for weed growth, as the absence of continuous flooding reduces natural suppression. Overreliance on herbicides further exacerbates the issue by selecting for herbicide-resistant weed species, leading to increased infestations (Chauhan, Opena, 2012). Additionally, the sheer volume of seeds it produces ensures its persistence in fields, compounding management difficulties for farmers. The combination of these traits has solidified its status as a significant global weed, hindering food security and impacting rice yields (Vila et al., 2021).

Seed germination is an influential component of the life cycle behaviour of a plant. It is controlled by dormancy and various environmental factors among which temperature, moisture, and light play vital roles (Bewley et al., 2013). Reduced and unpredictable emergence of seedlings maybe linked with seed dormancy, which is directly linked with environmental conditions (McCormick et al., 2009). The foremost factor for regulating seed dormancy in non-dormant seeds is temperature for annual weed seeds of irrigated areas by the start of its growth cycle (Pedroso et al., 2019). Light serves as a crucial environmental signal for seeds, allowing them to sense disturbances and potential opportunities for growth. Seeds often react to the red-to-far-red (R/FR) ratio, which changes based on surrounding vegetation and light conditions. High R/FR ratios indicate an open environment with more sunlight, potentially signifying a suitable location for germination (Finch-Savage et al., 2005).

Understanding how weeds germinate and interact with crops can greatly improve the effectiveness of weed management practices. Knowing when weeds and crops emerge is crucial for estimating the impact of weeds on crop yield. Population-based models offer insights into the germination patterns of weed seeds across various environments (Afzal et al., 2022). These models not only describe individual seed behaviour but also help in understanding differences in germination timing among different weed species, which significantly influences their subsequent growth and competitiveness (Anwar et al., 2021). These models, collectively referred to as “population-based threshold models” (PBT), include hydro-time (HT), thermal time (TT), and hydrothermal time (HTT) models.

Predicting how populations and species will respond to changing climate is essential for understanding their future adaptations to climate change. PBT serve as valuable tools for unravelling these complex responses and can be used to forecast the overall life cycle of a species across diverse ecological settings (Bradford, Pedro, 2022). These models aim to provide valuable insights that can be utilized to manage weeds more effectively under shifting climatic conditions. This study was undertaken to develop models to predict the seed germination and emergence patterns of L. chinensis, a common weed species in rice-wheat cropping systems.

2.Material and Methods 2.1 Experimental location and material

This study was conducted within the controlled environment of the Seed Physiology Lab, Department of Agronomy at University of Agriculture Faisalabad, Pakistan (UAF). Seeds of L. chinensis were collected from approximately 50 plants during their natural dispersal period, which occurred in late September 2020, from a rice field located in Faisalabad. Following collection, cleaning procedures were employed to remove glumes and light seeds. The cleaned seeds samples were than pooled and were stored in glass jars under dry conditions at room temperature (approximately 25 °C), maintaining a moisture content of 12% until the initiation of the experiment, which commenced 20 days after seed collection. To quantify the initial dormancy level of the seed groups of 50 seeds in three replications were exposed to a germination test (section 1.2). Seeds exhibiting more than 40% germination were identified as non-dormant and were used in the experiments.

2.2 Germination test protocols

L. chinensis seeds were germinated using a completely randomized design with three replications. In each trial, 50 seeds were placed in a 9 cm Petri dish lined with Whatman filter paper, with each Petri dish representing a single replicate. Five milliliters of distilled water or other solutions (different water potentials) were added to each dish and then sealed with parafilm to prevent moisture loss. Germination was defined by the emergence of radicle or coleoptile growth, approaching a size of 1 mm throughout the initial 4 days of the experiment, daily assessments and removal of germinated seeds were executed, followed by a reduced frequency every 2 to 3 days thereafter until day 14. All the parameters related to germination were calculated using standard procedures and protocols (Chauhan, 2008).

2.3 Temperature

Seed germination was evaluated under six constant temperatures (20, 25, 30, 35, and 40 ⁰C), at 12h light using a locally manufactured thermogradient table. This apparatus facilitated the maintenance of each temperature within various chambers concurrently during the germination study. The study was repeated twice.

2.4 Water potential and temperature

A preliminary experiment was conducted using six water potential levels (ranging from 0 to -1 MPa) and four temperature treatments (20, 25, 30, and 35 °C) with a photoperiod of 12 h light and 12 hr dark. Based on the results, four water potential treatments were selected: 0 (distilled water), -0.3, -0.6, and -0.9 MPa, at temperatures of 25 and 30°C. For water potential treatments, seeds were germinated using various concentrations of polyethylene glycol (PEG 400) with distilled water in accordance with the formulations derived by Micheal (1983). Approximately 23.58, 39.53 and 52.12 ml PEG was added in 476.41, 460.46 and 447.87 ml of water to get the desired water potentials. The calibration of these water potentials was executed utilizing a Wescor Vapro osmometer (Wescor Inc., Logan, Utah, USA).

2.5 Light and temperature

To assess the light effect on germination, seeds were placed in growth chambers at five temperatures (20, 25, 30, 35 and 40 ^oC), under complete darkness or 12h light. To incubate in darkness, the dishes were wrapped in two layers of aluminum foil. Germination counts were performed in a dark room using a dark green light for the dark treatment. The study was repeated twice.

2.6 Soil Depth

The experiment was conducted in plastic pots with three replications for every treatment filled with a particular quantity of silty loam soil collected from a local field in Faisalabad. To ensure that the soil was free from any pre-existing L. chinensis seeds or other contaminants, it was oven-dried at high temperatures prior to the experiment. Twenty- five seeds were placed on the soil surface in each pot. The pots were then filled with the same type of soil to achieve burial depths of 0, 1, 3, and 5 cm. Irrigation was carried out using a sprayer, and the pots were placed in a growth chamber (SANYO Japan, MIR-254) maintained at a constant temperature of 30 °C and a photoperiod of 12 hours of light and 12 hours of darkness. Seedlings were considered emerged once the cotyledons became visible on the soil surface. Emergence was recorded every 24 h over a period of 15 d. The study was repeated twice.

2.7 Statistical analysis

Temperature and water potential data were analyzed using population-based threshold models to understand seed germination dynamics. Thermal time, expressed in degree days or hours, was utilized to relate temperature to germination time. The simplest description of germination in response to temperature has two components, one for temperatures between T_b and T_o (sub-optimal region) (Equations 1 and 2) and another for temperatures between T_o and T_c (supra-optimal region) (Equations 3 and 4) (Bradford, 1995).

Germination in response to temperature within the sub-optimal region was modeled using the thermal time equation:

[Formula Omitted. Please see PDF.]

T_b is the minimum temperature for germination, while tg is the germination time which varies among seeds within a population. When germination rates (1/tg) are plotted against time, the lines corresponding to different fractions of the population show variations in slope but shared a common intercept at T_b. The reciprocals of these slopes related to θT (g), as demonstrated by the following equation

[Formula Omitted. Please see PDF.]

GRg denotes the germination rate (GR) for fraction g within the range from the base temperature to the optimal temperatures. This equation is usually effective in describing the germination rates of a seed population across diverse temperatures.

The above Equations 1 and 2 predict that germination time decreases with increasing (T – T_b) until an optimum temperature (T_o) is reached. In the supra-optimal region (between T₀ and the ceiling temperature T_c), the model was adapted to account for the slowdown in germination as temperatures approach (T_c) which was measured using the following equations:

[Formula Omitted. Please see PDF.]

Or

[Formula Omitted. Please see PDF.]

In the supra-optimal temperature range, the ceiling temperature (Tc) changes depending on the percentage of seeds germinating (Tc (g)). However, the thermal time (θT) stays constant for all seeds, even though it’s different from the thermal time specific to each germination fraction (θT (g)).

To determine the thermal time for different germination stages, a repeated probit regression analysis was used as suggested by Boddy et al. (2013). This involves applying a specific mathematical formula, represented by the following equation:

[Formula Omitted. Please see PDF.]

The Probit (g) represents the transformed germination percentage, θT (50) is the thermal time at which 50% of the seeds germinate, σθT indicates the variability in germination times among seeds in the population.

The germination response to varying water potentials (ψ) and sub-optimal temperatures was assessed using the hydrothermal time model (°C hours), as described by Gummerson (1986) and Bradford (1995). The hydrothermal time constant (θHT) for sub-optimal temperatures was calculated using the following equation:

[Formula Omitted. Please see PDF.]

The model assumes both the base water potential for germination (Ψb (g)) and the base temperature (T_b) remain constant and independent of temperature and water potential (Ψ), respectively. While these assumptions simplify calculations, they might not always hold true. Both Ψb (g) and T_b can exhibit variability in response to various environmental factors (Bradford, 2002).

Mean values were compared utilizing Tukey’s test (HSD) with a significance level set at p < 0.05 to determine whether the parameters varied across different temperatures, water potentials, light and soil depths. Statistical analyses were performed using R software, graphs were prepared using Microsoft Excel (2013) and PBT models were fitted to the data using packages available at (https://pbtmodels.shinyapps.io/pbtm-app/). All the experiments were repeated twice.

3.Results and Discussion 3.1 Temperature

Thermal time (TT) models were used to examine the germination behavior of L. chinensis seeds at sub-optimal (20–30 °C) and supra-optimal (30–40 °C) temperatures. The θT (50) value, representing the thermal time needed for 50% germination, increased with temperature variations in both models (Table 1). At sub-optimal temperatures, the highest germination rate was at 30 °C, decreasing as the temperature dropped to 20 °C (Figure 1a). Under supra-optimal conditions, germination rates declined as the temperature increased from 30 °C (Figure 1b). This trend was reflected in the standard deviation of the TT model, which showed a modest increase at sub-optimal temperatures but a significant rise at supra-optimal temperatures (Table 1). The base temperature for L. chinensis was determined to be 12.7 °C, and the ceiling temperature was 43.6 °C. Both models showed a strong correlation between temperature and germination, with R² values of 0.91 and 0.94 (Table 1). These results highlight the temperature sensitivity of L. chinensis seeds and validate the effectiveness of TT models in predicting temperature-dependent germination responses.

[Image omitted; see PDF]

The findings of this study match with Driver et al. (2020) who reported Leptochloa fusca, a species closely related to L. chinensis exhibits unique emergence characteristics compared to other weed species. Specifically, it has a base temperature of 14.6 °C and requires a greater accumulation of growing degree days (GDD) to achieve initial emergence. Interestingly, this species experiences an initial emergence delay of approximately 64 GDD relative to other species. This insight emphasizes the importance of not relying on a single application of herbicide, as it allows for effective management of multiple weed species at various growth stages. Notably, PBT models suggest that herbicide application on the day of seeding can effectively control a majority of weeds (Driver et al., 2020). While some late-emerging weeds might evade control from this early application, this approach provides a strong foundation for managing weed populations in rice fields (Driver et al., 2024). Fluctuating temperatures can impact seed germination, but this effect varies depending on the plant species and dormancy level of the seeds (Rezaei-Manesh et al., 2023). Seeds with low dormancy, are generally more sensitive to temperature fluctuations. Among environmental factors, temperature plays a key role in natural germination, influencing both a seed’s ability to germinate and the speed of germination in non-dormant seeds (Batlla, Benech-Arnold, 2015). Temperature functions as a critical regulator of seed germination, determining both the timing of sprouting and the specific seeds that will germinate under given environmental conditions (Klupczyńska, Pawłowski, 2021). Each plant species has a unique temperature range for successful germination, defined by minimum, optimal, and maximum temperatures (Golmohammadzadeh et al., 2022; Krichen et al., 2023).

3.2 Temperature and water potential

The effectiveness of the Hydrothermal Time (HTT) model was determined in this study to describe the germination behaviour of L. chinensis seeds under various temperatures and water potentials. The model successfully normalized germination data, creating unified curves for analysis (Figure 1c). Importantly, the HTT model revealed that temperature and water potential have interchangeable, additive effects on L. chinensis germination. This effect means different combinations of these factors can produce similar germination rates if their overall impact is equivalent. The HTT model’s strong fit (R²) and all other parameters described in Table 1 provide valuable quantitative insights into how the seeds respond to these environmental factors. The observed temperature-dependent trends in θH and ψb values further contribute to our understanding of the nuanced response of seeds to varying environmental conditions, providing valuable insights for seed germination modelling and agricultural practices for this species.

The findings of present study on moisture stress are consistent with Chauhan and Johnson (2008), who observed a delay in L. chinensis germination with increasing moisture stress. Seed germination was inhibited by 50% at -0.1 MPa (6.3 days) and -0.2 MPa (5.6 days) solution concentrations compared to the control (4.8 days). These results support the concept that most seeds readily germinate under moist conditions, while those in drier environments may exhibit dormancy until favorable moisture availability triggers germination. Likewise, the ability of this weed species to germinate at low osmotic potentials implies a potential competitive advantage over crops more susceptible to drought stress like rice (Chauhan, 2016).

3.3 Temperature and light

When the seeds were given light, they had more germination compared to those receiving only darkness. Also, as the temperature increased from 30 °C, the germination of L. chinensis decreased. The greatest germination of 92% was recorded at 30°, when the seeds were exposed to continuous light. In light and darkness more germination was observed when the seeds were exposed to light as compared to those which do not receive light at all. The lowest germination of 19% was recorded at 20° when there was no light exposure (Figure 2). Populations that flourish under light conditions can be better managed by planting a denser ground cover. A robust vegetation cover helps reduce the germination and growth of weeds. A good coverage of native species tends to keep soil temperature lower, which reduces chances of seed germination (Lamego et al., 2024).

[Image omitted; see PDF]

3.4 Soil Depth

The seeds of L. chinensis were buried at various soil depths to determine the effect of dark and light on emergence in field. There was a significant variation in the emergence patterns of L. chinensis seeds with the increase in the soil depth. Maximum emergence fraction was obtained at soil depth of 0 and 1 cm and decline linearly with increase in soil depth to 5 cm (Figure 4). Deeply buried seeds, especially small ones, struggle to emerge due to limited energy reserves. Fluctuating temperatures act as a signal for seeds near the surface, promoting successful emergence (Humphries et al., 2018). The decrease in seedling emergence might be attributed to the exhaustion of seed reserves. Also, oxygen deficiency and limitation of gas diffusion are among the factors that may reduce the emergence percentage and rate at greater depths (Wang et al., 2019).

[Image omitted; see PDF]

4.Conclusions

L. chinensis seeds have an optimal germination temperature range of 25 to 30 °C, with higher germination rates observed under light conditions, though light is not strictly necessary. Additionally, L. chinensis demonstrated moderate tolerance to water stress. This study investigated the emergence and germination characteristics of L. chinensis seeds breaking new ground in understanding the ecology of a key rice weed. Prior to this study, knowledge about its emergence and germination behaviour in rice fields was limited. The models applied here provide a valuable forecasting tool for rice growers and agricultural consultants. These insights are crucial for developing tailored management programs to control this weed and enhance rice production.

Acknowledgements

We thank Dr. Kent J. Bradford and Pedro Bello from University of California, Davis, USA for providing accesses to the models used for data analysis and the opportunity for collaboration of scientific exchange.

Funding

This research was supported by the Higher Education Commission of Pakistan through the Indigenous 5000 PhD Fellowship Program and the Seed Physiology Lab, Department of Agronomy, University of Agriculture, Faisalabad, Pakistan.

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