ABSTRACT
Background
Several equine conditions are associated with and exacerbated by increased high‐sugar grass intake. Knowing how climatic and biotic factors affect sugar content in grasses is important for decision‐making by those involved in the management of equines.
Objectives
(1) To characterise equine owners’ knowledge and perceptions of the factors affecting sugar content in grasses to inform in the management of grasses and equines. (2) To identify associations between pre‐existing horse‐related experience and level of knowledge about equine nutrition and health conditions.
Methods
A questionnaire was developed and distributed online to characterise the perceptions of those involved in the management of equines and their knowledge of the environmental factors known to impact grass non‐structural carbohydrate (NSC) levels, describing also the extent to which these factors associated with participants’ level of experience in equine management.
Results
194 self‐declared equine owners or responsible for equines completed the survey. Our results indicate that participants were relatively well informed regarding only some of the environmental factors known to affect sugar content in grasses, and less so in relation to how the presence of fungi, overgrazing/rotational stocking might influence NSC, indicating a significant gap in knowledge. The level of previous experience with equines was not associated with more accurate knowledge, highlighting the need for facilitating more knowledge exchange activities between stakeholders and the scientific community.
Conclusions
We suggest that enhancing the dissemination of the effects of plant‐fungal interactions and rotational stocking on NSC within the equine community may further improve their understanding around NSC content in grasses and its management, as fungi could be used to manage grass establishment and growth in paddocks and the grass sugar content.
Keywords: equine nutrition, fungi, laminitis, management, sugar content

1. Introduction
In horse diets, grass can constitute between 50% and 100% of the total diet in a dry matter basis and provides the nutrients and non‐structural carbohydrates (NSC) that the animals need to function correctly (Virkajärvi et al. 2012). There are several diseases of horses known to be associated and exacerbated by high/increased high‐sugar grass intake (reviewed by Secombe and Lester 2012). For example, laminitis is one of the most common diseases of horses, naturally affecting between 1.5% and 34% of them depending on the study (Wylie et al. 2011). Laminitis is a painful and debilitating condition of the hoof that has major impacts on the welfare of the animal and can lead to euthanasia (Hopster and van Eps 2019). Laminitis has a complex multifactorial origin not yet completely understood. Several diet‐related factors are suggested to predispose to laminitis, including a high sugar intake due to the NSC overload (Pollitt et al. 2003; van Eps and Pollitt 2006).
Plants use CO2 from the atmosphere to obtain carbon and use most of it for their metabolism (i.e., respiration) and to build their biomass (cellulose, lignin). The rest of this carbon is in the form of NSC, which include soluble sugars such as glucose, fructose and sucrose, starch and fructans (Jensen et al. 2014). NSC support plant metabolism at night or when photosynthesis is not sufficient to meet the plant's demands (Smith and Stitt 2007). The dynamics of NSC are complex and usually interpreted based on the idea that once the plant's current carbon energy requirements are covered by current and recent photosynthates, any excess carbon production accumulates within the non‐reproductive tissues such as leaves and roots (Barbehenn et al. 2004; Martínez‐Vilalta et al. 2016). The main storage compounds used differ between plants and significant differences are observed between cool‐season grasses (or C3 grasses) and warm‐season (or C4) grasses. Cool‐season grasses use mainly fructans as the storage compound (Miller et al. 2001). During cool weather, these grasses can accumulate large amounts of fructans mainly in cell vacuoles of the stems (Gallagher et al. 2007) that they can convert to simple sugars when needed, for example under hot or dry conditions when they are not able to photosynthesise. C4 grasses on the other hand, are adapted to hot, dry weather and generally accumulate starch within chloroplasts on the leaves which is not transposable within the plant and they go dormant after frost (Moore and Hatfield 1994). Because of these physiological differences, C3 grasses generally have higher NSC than C4 (Chatterton et al. 1989; DeBoer et al. 2017).
The environmental factors affecting NSC content in grasses are relatively well established in the scientific literature (Watts and Chatterton 2004) and include temperature (Chatterton et al. 1989; Espevig et al. 2011), light intensity (Comont et al. 2013), and soil water (Rogers et al. 2019) and nutrient content (Conaghan et al. 2012). Therefore, the amount of NSC in grasses may vary daily (being highest in late afternoon compared to the morning (Pelletier et al. 2009; Pelletier et al. 2010; Kagan et al. 2011; Morin et al. 2012), seasonally (being highest during early spring and autumn [Kagan et al. 2011; Jensen et al. 2014]), and even between grass cultivars (Jensen et al. 2014). However, common perceptions on the factors affecting sugar content in grasses may not always align with the available scientific evidence. Therefore, this study aimed to characterise equine owners’ knowledge and perceptions of the factors affecting sugar content in grasses to identify gaps in current knowledge and inform in the management of grasses and equines. Because horse owner's experience and level of knowledge about equine nutrition and health conditions may affect how equines are managed (Gerber et al. 2011), we also aimed to identify associations between knowledge with the level of experience with equines.
2. Materials and Methods
2.1. Ethical Approval
This research study received a favourable ethical opinion by the University of Lincoln Research Ethics Committee (Reference: UoL2022_10485). All participants were fully briefed on the study and provided informed consent. Participation was anonymous and participants could withdraw from the study at any time.
2.2. Methods
A cross‐sectional study design was used to develop a questionnaire using JISC online surveys software (JISC, 2022) designed to take around 20 min. The survey included questions on demographics, management of equines and paddocks, and knowledge on nine environmental factors known to affect sugar content in grasses (Table 1, and Table S1 for the full questionnaire).
TABLE 1.
Survey items.
| Topic | Question (Answer) |
|---|---|
| Demographics | Where are you located? Open‐ended. |
| How many equines do you currently own/loan? Open‐ended. | |
| In total, how many equines have you owned/loaned? Open‐ended. | |
| Management | Have you ever tested your paddock grass for sugar? Yes / No. |
| Do your horses have a grass susceptible/grass intolerant condition? This could include issues with weight gain. Yes / No. If Yes, please state which conditions. | |
| Do you currently know what grass species are in your grazing paddocks? Yes / No. If Yes, please state. | |
| Knowledge (correct answers bolded) | Of these changes in environmental conditions, tick all that you think will increase sugar grass levels: rain / sun / frost / drought / decreased temperature / increased temperature / overgrazed/stressed grass / regularly rotated grass pasture / fungi presence . |
| Do you think that frost would increase or decrease grass sugar levels? Increase / Decrease / I don't know. | |
| Do you think that the presence of fungi in soil or on the plant would affect the grass sugar levels within grass? Yes / No / I don't know. | |
| What time of the day do you think the grass sugar is highest? Morning (8am – 12pm), Afternoon (12pm – 4pm) , Evening (4pm – 8 pm), Night (9pm – 12am). |
Anyone above 18 years of age, English‐speaking, who self‐declared as an equine owner or responsible for the management of equines was eligible to participate in the survey, and no incentives were provided. The questionnaire was distributed through the authors social media accounts and emails and was live from 17 November 2022 until 1 February 2023. A total of 221 people completed the survey: 27 self‐declared as non‐equine owners/responsible for equines and were therefore excluded in the final analysis.
2.3. Data Analysis
All data were analysed using R v4.3.1 (R Core Team 2023). The minimum number of participants needed to detect medium size differences in the data (N = 117) was calculated by using ‘pwr.chis.test’ function in the ’pwr’ package (Champely 2020), with a significance level of < 0.05, power (i.e., true positive probability) > 0.8 and an effect size of w = 0.3.
Based on the numbers of respondents on how many equines owned/were or have been responsible for, the level of horse‐related experience was classified in four broad categories: Beginner (less than 5 equines, 18.0% of answers), Intermediate (between 6 and 10 equines, 38.1% of answers), Advanced (between 11 and 100 equines, 34.0% of answers), and Expert (more than 101 equines, 9.8% of answers). This was an arbitrary cut‐off which probably does not truly reflect someone's level of experience with equines, as it would be very challenging to estimate or quantify the total level of involvement, focus of responsibility, etc. within the equine industry. Data were analysed using Chi‐square tests used to determine differences between responses. The package ‘vdc’ was used to analyse the association between answers with the level of experience using the ‘assocstats’ function (Meyer et al. 2024). Cramer's V was calculated to estimate the strength of the association between answers and level of experience.
3. Results
Overall, there were 194 valid responses to the questionnaire. The respondents were mainly UK‐based (88.1%), however there were also responses from Spain, Canada, United States, Australia, New Zealand, Sweden, and The Netherlands. Participants reported to have had experience with 1 to more than 1000 equines. A large proportion of responses showed that participants have had experience managing a grass‐susceptible equine condition (89.7%), being laminitis (112 participants), equine metabolic syndrome (76 participants), and seasonal weight gain (65 participants) the 3 most commonly conditions reported. Only 25.3% of participants declared to know the grass species present in their grazing paddocks (see Table S2 for a list of the species mentioned) and only 6.2% had had their paddocks analysed to measure sugar content.
3.1. Knowledge on Factors Increasing Sugar Content in Grass
When asked about what time of the day the sugar content was highest, almost half of the participants (48%) answered during the morning, followed by afternoon (34%), evening (14%) and night (4%; Figure 1A). No significant association between the answers received and the level of equine experience was detected (X 2 9 = 4.85, P = 0.84; Figure 1B).
FIGURE 1.

(A) Total number of answers received to the question “What time of day do you think the grass sugar is highest?” (B) Proportion of answers received by each time of the day depending on the level of Experience. According to the scientific evidence, late afternoon is when the highest level is measured, so afternoon and evening were both correct answers.
Participants were asked to indicate which of nine given factors they thought would increase sugar content, with the expectation that participants should identify all of them. Overall, participants selected 4 factors on average, and only 10 participants selected all the factors. Frost was the factor most well‐known (81% of participants identified it), followed by sun (72%) and overgrazing/stressed grass (60%). Opposite to this, rotational stocking and fungi were only correctly identified by 12% of participants (Figure 2). There were no significant associations between the level of experience with any of the answers (Table 2).
FIGURE 2.

(A) Proportion of participants correctly identifying (blue bars) or not (pink bars) environmental factors known to increase sugar content in grass according to the scientific evidence. Factors are shown in decreasing order of correctly being identified.
TABLE 2.
Results of the relationships between identifying several factors known to affect sugar content in grasses and level of equine experience using Pearson X 2 and Cramer's V.
| df | Pearson X 2 | p‐value | Cramer's V | |
|---|---|---|---|---|
| Time of day | 9 | 4.92 | 0.84 | 0.092 |
| Frost | 6 | 3.17 | 0.78 | 0.091 |
| Sun | 3 | 1.61 | 0.65 | 0.091 |
| Overgrazing | 3 | 2.46 | 0.48 | 0.113 |
| Rain | 3 | 1.20 | 0.75 | 0.079 |
| Dec. temperature | 3 | 6.93 | 0.07 | 0.189 |
| Inc. temperature | 3 | 1.88 | 0.59 | 0.099 |
| Drought | 3 | 1.37 | 0.71 | 0.084 |
| Rotational stocking | 3 | 2.09 | 0.55 | 0.104 |
| Fungi | 6 | 7.42 | 0.28 | 0.138 |
Below, we present a more detailed analysis for the top and bottom factors identified by the participants and the association with their level of expertise. The differences between the level of expertise for the rest of the factors are shown as Supporting Information (Figure S1).
3.2. Knowledge on the Effect of Frost on Grass Sugar Levels
Frost was correctly identified by 81% of the participants taking the survey. When asked whether frost would increase or decrease grass sugar levels, a significantly large number of participants (87%) thought that frost would increase sugar content (X 2 2 = 270.29, P < 0.001; Figure 3A). There was no statistically significant association between the answers being correct with the level of experience (X 2 6 = 3.95, P = 0.68), even though the number of participants that were not sure about the effect of frost on sugar content increased with decreasing level of experience (Figure 3B).
FIGURE 3.

(A) Total number of answers received to the question ‘Do you think that the frost would increase or decrease grass sugar levels?’. (B) Proportion of answers received depending on the level of Experience. The effect of frost on sugar content depends on the timing of measurement after frost, and the severity and duration of the cold period. The correct answers were increase and decrease. NA indicates that an answer was not available from one participant.
3.3. Knowledge on the Effect of Rotational Stocking on Grass Sugar Levels
The effect of rotational stocking was only identified by 12% of the participants taking the survey and most of them (87%) thought that rotational stocking would not affect sugar content (Figure 4A). There was no statistically significant association between the answers being correct with the level of experience (X 2 3 = 2.09, P = 0.55), even though participants with most experience were better at correctly identifying the correct answer (Figure 4B).
FIGURE 4.

(A) Total number of answers received to the question ‘Do you think that regularly rotating grass pasture would increase grass sugar levels?’. (B) Proportion of answers received depending on the level of Experience.
3.4. Knowledge on the Effect of Fungi on Grass Sugar Levels
The majority of respondents (74%) answered that they didn't know whether the presence of fungi in soil or on the plant would affect the sugar levels within grass (X 2 2 = 154.93, P < 0.001; Figure 5A). Even though there was numerical variation in the proportion of answers depending on the level of experience, no significant association was detected (X 2 6 = 8.32, P = 0.621; Figure 5B).
FIGURE 5.

(A) Total number of answers received to the question “Do you think that the presence of fungi in soil or on the plant would affect the sugar levels within grass?”. (B) Proportion of answers received depending on the level of Experience. Depending on the fungus, NSC are expected to increase/decrease.
4. Discussion
In this study, the perceptions of equine owners/people responsible for equines regarding the environmental factors affecting the content of sugar in grass were investigated. Our results indicate that the equine community is relatively well informed regarding some climatic factors known to affect sugar content in grasses such as frost, but much less so in relation to how the presence of fungi or rotational stocking might influence NSC. Moreover, our analysis indicates that the level of previous experience with equines is not associated with more correct knowledge about the environmental factors affecting sugar content in grasses.
The annual dynamics of NSC are well established for perennial grasses which show the highest pool of sugars in late summer or autumn in response to slow growth and leaf senescence due to seasonal drops in temperature and light (Longland and Byrd 2006; Kagan et al. 2011; Morin et al. 2012; Jensen et al. 2014; Benot et al. 2019). Daily dynamics of NSC are also well described in the scientific literature, with a peak sugar content found after midday/late afternoon during the grass growing period in spring, with concentrations tending to rise during the morning and declining overnight (Pelletier et al. 2010; Kagan et al. 2011; Morin et al. 2012; Weinert‐Nelson et al. 2022). The same patterns in increased daily concentrations of NSC are reported for non‐grasses forage species such as alfalfa (Morin et al. 2011) or red clover (Owens et al. 1999). For these reasons, morning grazing and/or restricted grazing are suggested as best practices for metabolic challenged horses (Watts 2004; EEG Equine Endocrinology Group 2024), which were expected to be known by the survey participants.
Regardless of the level of previous experience with equines, participants were relatively unaware of the effects of fungi on sugar content, which 74% of respondents indicating that they did not know what the effect could be. Grass species are usually colonised by symbiotic fungal endophytes that grow within the plant tissues either producing positive or negative effects for the plants (Sanchez Marquez et al. 2012). For example, many endophytes such as Epichloë spp provide grasses with increased tolerance to abiotic stresses such as drought due to the production of alkaloids and can also produce toxins which can be detrimental for herbivores consuming these grasses (Riet‐Correa et al. 2013). Moreover, grasses, like most other plants, are usually colonised by arbuscular mycorrhizal fungi in their roots. In this relationship, the mycorrhizal fungi provide water and nutrients derived from the soil to the plant in exchange of sugars, which usually translates into enhanced photosynthesis and thus growth and performance (Smith and Read 2010). These fungal associations are generally regarded as mutualistic for the host plant even though the net outcome depends on other factors such as the amount of nutrients in the soil, so the interactions range in fact from being parasitic to mutualistic (Johnson et al. 2008). In terms of sugar content, both endophytic and mycorrhizal fungi depend on the plant's carbohydrates, but also may increase plant photosynthetic capacity and the amount of NSC produced (Cheplink and Cho 2003; Hill et al. 1996; Nagabhyru et al. 2013). Thus, it can be predicted that the effect of these two types of fungi on plant's sugar content may be positive, negative, or neutral. Moreover, in terms of forage management, symbiotic fungal endophytes can be beneficial as they can provide better defence against pests, but they can also modify plant community composition by direct allelopathic effects (Franzluebbers and Hill 2005) as well as indirectly through plant‐soil feedbacks (Cripps et al. 2013), highlighting the need for more studies.
Finally, participants were also relatively unaware of the effects of rotational stocking and overgrazing on NSC. Equines commonly overgraze on preferred grasses, which positively correlates with NSC concentrations (Allen et al. 2013). Besides the potential long‐term impacts for forage composition and persistence (Martinson et al. 2015), overgrazing affects photosynthesis and carbon allocation, by changing source organs to sinks during regrowth (Martínez‐Vilalta et al. 2016; Zhang et al. 2021). It is relatively well established in the scientific literature that carbohydrates stored in the tiller bases of grasses are rapidly mobilised following grazing (Morvan‐Betrand et al. 2001), and conversion of stored NSC provides energy to support the growth of new organs (Martínez‐Vilalta et al. 2016). However, to the authors’ knowledge, research on equine pasture management is relatively scarce compared to other livestock species, highlighting the need to disseminate and consider the effects of rotational stocking for equine management (but see Weinert and Williams 2018; Williams et al. 2020).
5. Conclusion
According to our results, the survey's participants appeared to be relatively misinformed of the environmental factors affecting the content of NSC of the grasses they might be feeding to their equines and few of them regularly tested their paddocks. A limitation of the study is that the findings relate to self‐declared equine owners or responsible for equines, with a classification of their level of experience simply based on how many equines participants declared to have been associated with. This classification does not comprehensively include the participants’ total level of involvement, focus of responsibility, etc. within the equine industry, and thus, was arbitrary. Nevertheless, disseminating the well‐established effects of plant‐fungal interactions or information on grazing management within the equine community would be useful, as it seems to be relatively ‘invisible’ to the average owner or people responsible for an equine.
Author Contributions
Isabel Moaby: conceptualisation, methodology, investigation, data curation, writing – original draft preparation. Alex Aitken: conceptualisation, methodology, writing – reviewing and editing. Sandra Varga: conceptualisation, methodology, formal analysis, visualisation, writing – reviewing and editing.
Funding
The authors have nothing to report.
Ethics Statement
This research study received a favourable ethical opinion by the University of Lincoln Research Ethics Committee (Reference: UoL2022_10485).
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Supplementary material: The dataset analysed in this study is available in the FigShare repository, DOI: https://doi.org/10.6084/m9.figshare.25585491.
Supporting Table 1: Full online questionnaire used for the study.
Supporting Table 2: List of the grass species (common names given by the participants with their corresponding scientific names) that the participants listed as being present in their paddocks.
Supporting Figure 1: Proportion of answers received depending on the level of Experience for the different factors known to increase sugar content in grass according to the scientific evidence.
Acknowledgements
The authors thank Beth Ventura for providing comments on a previous draft and one anonymous reviewer for useful suggestions.
Moaby, I. , Aitken A., and Varga S.. 2026. “Scientific Evidence and Common Perceptions of Factors Affecting Sugar Content in Pasture Grass: Is There a Link With Pre‐existing Horse‐Related Experience?.” Veterinary Medicine and Science 12, no. 1: e70778. 10.1002/vms3.70778
Data Availability Statement
The dataset analysed in this study is available in the FigShare repository, https://doi.org/10.6084/m9.figshare.25585491.
References
- Allen, E. , Sheaffer C., and Martinson K.. 2013. “Forage Nutritive Value and Preference of Cool‐season Grasses Under Horse Grazing.” Agronomy Journal 105: 679–684. 10.2134/agronj2012.0300. [DOI] [Google Scholar]
- Barbehenn, R. V. , Chen Z., Karowe D. N., and Spickard A.. 2004. “C3 Grasses Have Higher Nutritional Quality Than C4 grasses Under Ambient and Elevated Atmospheric CO2.” Global Change Biology 10: 1565–1575. 10.1111/j.1365-2486.2004.00833.x. [DOI] [Google Scholar]
- Benot, M.‐L. , Morvan‐Bertrand A., Mony C., et al. 2019. “Grazing Intensity Modulates Carbohydrates Storage Pattern in Five Grass Species From Temperate Grasslands.” Acta Oecologica 95: 108–115. 10.1016/j.actao.2018.11.005. [DOI] [Google Scholar]
- Champely, S. 2020. “Pwr: Basic Functions for Power Analysis.” R package version 1.3‐0, https://github.com/heliosdrm/pwr.
- Chatterton, N. J. , Harrison P. A., Bennett J. H., and Asay K. H.. 1989. “Carbohydrate Partitioning in 185 Accessions of Gramineae Grown Under Warm and Cool Temperature.” Journal of Plant Physiology 134: 169–179. 10.1016/S0176-1617(89)80051-3. [DOI] [Google Scholar]
- Cheplick, G. P. , and Cho R.. 2003. “Interactive Effects of Fungal Endophyte Infection and Host Genotype on Growth and Storage in Lolium perenne .” New Phytologist 158: 183–191. https://www.jstor.org/stable/1514091. [Google Scholar]
- Comont, D. , Winters A., Gomez L. D., McQueen‐Mason S. J., and Gwynn‐Jones D.. 2013. “Latitudinal Variation in Ambient UV‐B Radiation Is an Important Determinant of Lolium perenne Forage Production, Quality, and Digestibility.” Journal of Experimental Botany 64: 2193–2204. 10.1093/jxb/ert077. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Conaghan, P. , O'Kiely P., Halling M. A., O'Mara F. P., and Nesheim L.. 2012. “Yield and Quality Response of Perennial Ryegrass Selected for High Concentration of Water‐soluble Carbohydrate to Nitrogen Application Rate.” Crop Science 52: 2839–2851. 10.2135/cropsci2012.02.0100. [DOI] [Google Scholar]
- Cripps, M. G. , Edwards G. R., and McKenzie S. L.. 2013. “Grass Species and Their Fungal Symbionts Affect Subsequent Forage Growth.” Basic and Applied Ecology 14: 225–234. 10.1016/j.baae.2013.01.008. [DOI] [Google Scholar]
- DeBoer, M. L. , Sheaffer C. C., Grev A. M., et al. 2017. “Yield, Nutritive Value, and Preference of Annual Warm‐Season Grasses Grazed by Horses.” Agronomy Journal 109: 2136–2148. 10.2134/agronj2017.02.0099. [DOI] [Google Scholar]
- Equine Endocrinology Group . 2024. “Recommendations for the Diagnosis and Managements of Equine Metabolic Syndrome (EMS) and Insulin Dysregulation.” https://equineendocrinologygroup.org.
- Espevig, T. , DaCosta M., Hoffman L., et al. 2011. “Freezing Tolerance and Carbohydrate Changes of Two Agrostis Species During Cold Acclimation.” Crop Science 51: 1188–1197. 10.2135/cropsci2010.07.0415. [DOI] [Google Scholar]
- Franzluebbers, A. J. , and Hill N. S.. 2005. “Soil Carbon, Nitrogen, and Ergot Alkaloids With Short‐ and Long‐Term Exposure to Endophyte‐Infected and Endophyte‐Free Tall Fescue.” Soil Science Society of America Journal 69: 404–412. 10.2136/sssaj2005.0404. [DOI] [Google Scholar]
- Gallagher, J. A. , Cairns A. J., and Turner L. B.. 2007. “Fructan in Temperate Forage Grasses: Agronomy, Physiology, and Molecular biology.” In Recent Advances in Fructooligosaccharides Research, edited by Shiomi N. Benkeblia N., and Onodera S., 15–46. Research Signpost. [Google Scholar]
- Gerber, V. , Schott H. C. II, and Robinson N. E.. 2011. “Owner Assessment in Judging the Efficacy of Airway Disease Treatment.” Equine Veterinary Journal 43, no. 2: 153–158. https://www.10.1111/j.2042‐3306.2010.00156.x. [DOI] [PubMed] [Google Scholar]
- Hill, N. S. , Pachon J. G., and Bacon C. W.. 1996. “ Acremonium coenophialum‐Mediated Short‐ and Long‐Term Drought Acclimation in Tall Fescue.” Crop Science 36: 665–672. 10.2135/cropsci1996.0011183X003600030025x. [DOI] [Google Scholar]
- Hopster, K. , and van Eps A. W.. 2019. “Pain Management for Laminitis in the Horse.” Equine Veterinary Education 31: 384–392. 10.1111/eve.12910. [DOI] [Google Scholar]
- Jensen, K. B. , Harrison P., Chatterton N. J., Bushman B. S., and Creech J. E.. 2014. “Seasonal Trends in Nonstructural Carbohydrates in Cool‐ and Warm‐Season Grasses.” Crop Science 54: 2328–2340. 10.2135/cropsci2013.07.0465. [DOI] [Google Scholar]
- Johnson, N. C. , Graham J. H., and Smith F. A.. 2008. “Functioning of Mycorrhizal Associations Along the Mutualism‐Parasitism Continuum.” New Phytologist 135: 575–585. https://doi.org.10.1046/j.1469‐8137.1997.00729.x. [Google Scholar]
- Kagan, I. A. , Kirch B. H., Thatcher C. D., et al. 2011. “Seasonal and Diurnal Variation in Simple Sugar and Fructan Composition of Orchardgrass Pasture and Hay in the Piedmont Region of the United States.” Journal of Equine Veterinary Science 31: 488–497. https://10.1016/j.jevs.2011.03.004. [Google Scholar]
- Longland, A. C. , and Byrd B. M.. 2006. “Pasture Nonstructral Carbohydrates and Equine Laminitis.” Journal of Nutrition 136: 2099S–2102S. 10.1093/jn/136.7.2099S. [DOI] [PubMed] [Google Scholar]
- Martínez‐Vilalta, J. , Sala A., Asensio D., et al. 2016. “Dynamics of Non‐Structural Carbohydrates in Terrestrial Plants: A Global Synthesis.” Ecological Monographs 86: 495–516. 10.1002/ecm.1231. [DOI] [Google Scholar]
- Martinson, K. L. , Wells M. S., and Sheaffer C. C.. 2015. “Horse Preference, Forage Yield and Species Persistence of Twelve Perennial Cool‐Season Grass Mixtures Under Horse Grazing.” Journal of Equine Veterinary Science 36: 19–25. https://soi.org/10.1016/j.jevs.2015.10.003. [Google Scholar]
- Meyer, D. , Zeileis A., Hornik K., and Friendly M.. 2024. “vcd: Visualizing Categorical Data.” R Package Version 1 4–13. https://CRAN.R‐project.org/package=vcd. [Google Scholar]
- Miller, L. A. , Moorby J. M., Davies D. R., et al. 2001. “Increased Concentration of Water‐Soluble Carbohydrates in Perennial Rye‐grass (Lolium perenne L.): Milk Production From Late‐Lactation Dairy Cows.” Grass Forage Science 56: 383–394. 10.1046/j.1365-2494.2001.00288.x. [DOI] [Google Scholar]
- Moore, K. J. , and Hatfield R. D.. 1994. “Carbohydrates and Forage quality.” In Forage Quality, Evaluation, and Utilization, edited by Fahey G. C. Jr., Collins M. C., Mertens D. R., and Moser L. E., 229–280. ASA‐CSSA‐SSSA. [Google Scholar]
- Morin, C. , Bélanger G., Tremblay G. F., et al. 2011. “Diurnal Variations of Nonstructural Carbohydrates and Nutritive Value in Alfalfa.” Crop Science 51: 1297–1306. 10.2135/cropsci2010.07.0406. [DOI] [Google Scholar]
- Morin, C. , Tremblay G. F., Bertrand A., et al. 2012. “Short Communication: Diurnal Variations of Nonstructural Carbohydrates and Nutritive Value in Timothy.” Canadian Journal of Plant Sciences 92: 883–887. 10.4141/cjps2011-272. [DOI] [Google Scholar]
- Morvan‐Bertrand, A. , Boucaud J., Le Saos J., and Prud'homme M. P.. 2001. “Roles of the Fructans From Leaf Sheaths and From the Elongating Leaf Bases in the Regrowth Following Defoliation of Lolium perenne L.” Planta 213: 109–120. 10.1007/s004250000478. [DOI] [PubMed] [Google Scholar]
- Nagabhyru, P. , Dinkins R., Wood C., Bacon C., and Schardl C.. 2013. “Tall Fescue Endophyte Effects on Tolerance to Water‐Deficit Stress.” BMC Plant Biology 13: 127. 10.1186/1471-2229-13-127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Owens, V. N. , Albrecht K. A., Muck R. E., and Duke S. H.. 1999. “Protein Degradation and Fermentation Characteristics of Red Clover and Alfalfa Silage Harvested With Varying Levels of Total Nonstructural Carbohydrates.” Crop Science 39: 1873–1880. 10.2135/cropsci1999.3961873x. [DOI] [Google Scholar]
- Pelletier, S. , Tremblay G. F., Lafrenière C., et al. 2009. “Nonstructural Carbohydrate Concentrations in Timothy as Affected by N Fertilization, Stage of Development, and Time of Cutting.” Agronomy Journal 101: 13721380. 10.2134/agronj2009.0125. [DOI] [Google Scholar]
- Pelletier, S. , Tremblay G. F., Bélanger G., et al. 2010. “Forage Nonstructural Carbohydrates and Nutritive Value as Affected by Time of Cutting and Species.” Agronomy Journal 102: 13881398. 10.2134/agronj2010.0158. [DOI] [Google Scholar]
- Pollitt, C. C. , Kyaw‐Tanner M., French K. R., van Eps A. W., Hendrikz J. K., and Daradka M.. 2003. Equine Laminitis. 49th Annual Convention of the American Association of Equine Practioners, New Orleans, LA. [Google Scholar]
- R Core Team . 2023. “R: a Language and Environment for Statistical Computing.” In R Foundation for Statistical Computing, Vienna, Austria. [Google Scholar]
- Riet‐Correa, F. , Rivero R., Odriozola E., et al. 2013. “Mycotoxicoses of Ruminants and Horses.” Journal of Veterinary Diagnostic Investigation 25: 692–708. https://10.1177/1040638713504572. [DOI] [PubMed] [Google Scholar]
- Rogers, M. E. , Lawson A. R., and Kelly K. B.. 2019. “Summer Production and Survival of Perennial Ryegrass (Lolium perenne) and Tall Fescue (Festuca arundinacea) Genotypes in Northern Victoria Under Differing Irrigation Management.” Crop Pasture Science 70: 1163–1174. 10.1071/CP18542. [DOI] [Google Scholar]
- Sanchez Marquez, S. , Bills G. F., Herrero N., and Zabalgogeazcoa I.. 2012. “Non‐Systemic Fungal Endophytes of Grasses.” Fungal Ecology 5: 289–297. 10.1016/j.funeco.2010.12.001. [DOI] [Google Scholar]
- Secombe, C. J. , and Lester G. D.. 2012. “The Role of Diet in the Prevention and Management of Several Equine Diseases.” Animal Feed Science and Technology 173: 86–101. 10.1016/j.anifeedsci.2011.12.017. [DOI] [Google Scholar]
- Smith, A. M. , and Stitt M.. 2007. “Coordination of Carbon Supply and Plant Growth.” Plant, Cell & Environment 30: 1126–1149. 10.1111/j.1365-3040.2007.01708.x. [DOI] [PubMed] [Google Scholar]
- Smith, S. E. , and Read D.. 2010. Mycorrhizal Symbiosis. Academic Press. 10.1016/B978-0-12-370526-6.X5001-6. [DOI] [Google Scholar]
- van Eps, A. W. , and Pollitt C. C.. 2006. “Equine Laminitis Induced With Oligofructose.” Equine Veterinary Journal 38: 203–208. 10.2746/042516406776866327. [DOI] [PubMed] [Google Scholar]
- Virkajärvi, P. , Saarijärvi K., Rinne M., and Saastamoinen M.. 2012. “Grass Physiology and Its Relation to Nutritive Value in Feeding horses.” In Forages and Grazing in Horse Nutrition, edited by Saastamoinen M., Fradinho M. J., Santos A. S., and Miraglia N., 17–43. Wageningen Academic Publishers. 10.3920/978-90-8686-755-4_1. [DOI] [Google Scholar]
- Watts, K. A. , and Chatterton N. J.. 2004. “A Review of Factors Affecting Carbohydrate Levels in Forage.” Journal of Equine Veterinary Science 24: 84–96. [Google Scholar]
- Weinert, J. R. , and Williams C. A.. 2018. “Recovery of Pasture Forage Production Following Winter Rest in Continuous and Rotational Horse Grazing Systems.” Journal Equine Veterinary Science 70: 32–37. 10.1016/j.jevs.2018.06.017. [DOI] [Google Scholar]
- Weinert‐Nelson, J. R. , Biddle A. S., and Williams C. A.. 2022. “Fecal Microbiome of Horses Transitioning Between Warm‐Season and Cool‐Season Grass Pasture Within Integrated Rotational Grazing Systems.” Anmal Microbiome 4: 41. 10.1186/s42523-022-00192-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Williams, C. A. , Kenny L. B., Weinert J. R., Sullivan K., Meyer W., and Robson M. G.. 2020. “Effects of 27 mo of Rotational vs. continuous Grazing on Horse and Pasture Condition.” Translational Animal Science 4: txaa084. 10.1093/tas/txaa084. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wylie, C. E. , Collins S. N., Verheyen K. L. P., and Newton J. R.. 2011. “Frequency of Equine Laminitis: a Systematic Review With Quality Appraisal of Published Evidence.” Veterinary Journal 189: 248–256. 10.1016/j.tvjl.2011.04.014. [DOI] [PubMed] [Google Scholar]
- Zhang, Z. , Gong J., Li X., et al. 2021. “Underlying Mechanism on Source‐Sink Carbon Balance of Grazed Perennial Grass During Regrowth: Insights Into Optimal Grazing Regimes of Restoration of Degraded Grasslands in a Temperate Steppe.” Journal of Environmental Management 277: 111439. 10.1016/j.jenvman.2020.111439. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary material: The dataset analysed in this study is available in the FigShare repository, DOI: https://doi.org/10.6084/m9.figshare.25585491.
Supporting Table 1: Full online questionnaire used for the study.
Supporting Table 2: List of the grass species (common names given by the participants with their corresponding scientific names) that the participants listed as being present in their paddocks.
Supporting Figure 1: Proportion of answers received depending on the level of Experience for the different factors known to increase sugar content in grass according to the scientific evidence.
Data Availability Statement
The dataset analysed in this study is available in the FigShare repository, https://doi.org/10.6084/m9.figshare.25585491.
