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Article

Contained Ensiling of High-Lipid Perennial Ryegrass: Fermentation Quality, Fatty Acid Retention, and Storage Stability †

by
Somrutai Winichayakul
1,*,
Ashley Prentice
1,
Philip Anderson
1,
Tracey Crowther
1,
Hong Xue
1,
Xiuying Zou
1,
Michele Reid
1,
Kim A. Richardson
1,
Dorothy Maher
1,
Richard W. Scott
1,
Luke J. Cooney
2,
Arjan Jonker
1,
Jakob Kleinmans
3 and
Nicholas J. Roberts
1
1
Resilient Agriculture, AgResearch Group, Bioeconomy Science Institute, Palmerston North 4442, New Zealand
2
Ag Emissions Centre, Tennent Drive, Palmerston North 4442, New Zealand
3
Nutriassist Ltd., 27 Heemskerck Place, Nelson 7010, New Zealand
*
Author to whom correspondence should be addressed.
†
One sentence summary: This study establishes a reproducible, contained workflow for producing and ensiling high-lipid genetically modified ryegrass that preserves elevated lipid content and compositional stability of fatty acids in long-term storage to enable subsequent animal-based evaluation under regulatory constraints.
Agriculture 2026, 16(3), 358; https://doi.org/10.3390/agriculture16030358
Submission received: 8 January 2026 / Revised: 29 January 2026 / Accepted: 31 January 2026 / Published: 2 February 2026
(This article belongs to the Special Issue Silage Preparation, Processing and Efficient Utilization—2nd Edition)
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Abstract

Genetically modified (GM) forage crops engineered to accumulate elevated levels of lipids offer potential benefits for ruminant nutrition and greenhouse gas mitigation. However, robust and reproducible workflows for producing, harvesting, and preserving GM forage biomass under containment remain a critical bottleneck, particularly where regulatory constraints preclude field-scale evaluation. Here, we describe a controlled-environment workflow for the repeated cultivation, harvesting, and ensiling of GM high-metabolizable-energy (HME) perennial ryegrass and corresponding null controls. Plants were grown under greenhouse containment, subjected to multiple regrowth cycles, and harvested biomass was wilted and ensiled using small-scale laboratory silos. Silage fermentation characteristics, total lipid content, and fatty acid (FA) composition were assessed following short- and long-term storage. Over 16 months, approximately 130 kg dry matter (DM) of each genotype was produced across multiple harvests and ensiling batches. Seasonal variation strongly influenced herbage composition, with water-soluble carbohydrate concentrations 4–5-fold higher in spring–summer than autumn–winter. Following ensiling, HME silage consistently retained elevated FA content compared with null controls (4.85% vs. 2.75% DM) and higher gross energy (18.1 vs. 17.5 MJ kg−1 DM). FA profiling indicated that major FA classes in HME were preserved across storage durations. After 342 days of storage, HME silage maintained 76% higher FA content, 4% greater DM digestibility, and 0.3–0.8 MJ kg−1 DM higher metabolizable energy. Both genotypes exhibited good fermentation quality, with pH consistently below 4.1 and adequate lactic acid production. This study does not evaluate animal performance or methane mitigation outcomes but establishes a practical and reproducible methodology for generating characterized GM silage material under containment suitable for subsequent in vivo studies, addressing a key translational gap between GM forage development and animal-based evaluation.

1. Introduction

Genetically modified (GM) plants with high-metabolizable energy (HME) represent a major advance in plant nutritional improvement [1,2,3,4]. In perennial ryegrass (Lolium perenne L.), this trait was designed to increase potential metabolizable energy (ME) via increased lipid-derived gross energy (GE), rather than directly measuring ME, and results in foliar fatty acid (FA) content up to 80% higher than conventional cultivars, corresponding to approximately 1 MJ kg−1 dry matter (DM) higher GE. This increase in foliar lipid content is achieved by enhanced triacylglycerol biosynthesis via overexpression of diacylglycerol acyltransferase 1, together with reduced lipid turnover associated with stabilization of lipid droplets by an engineered cysteine-oleosin [4]. Field validation studies in the United States have demonstrated that HME ryegrass can maintain elevated leaf FA and GE under repeated defoliation and agronomic conditions representative of managed perennial pasture systems [5], supporting its potential to improve forage energy density.
Elevated lipid content in forages has also been proposed as a strategy to influence rumen fermentation and potentially reduce enteric methane (CH4) emissions. Dietary lipids are known to affect methanogenesis through multiple mechanisms, including shifts in rumen microbial populations and hydrogen utilization; however, these effects are dose-dependent and strongly influenced by diet composition and intake context [6]. Based on prediction equations and in vitro evidence, increased FA content in HME ryegrass has been hypothesized to reduce enteric CH4 emissions; however, empirical in vivo validation of CH4 mitigation by HME ryegrass remains limited [7]. Translating increased GE into ME and validating any mitigation potential requires in vivo animal studies, as intake regulation, rumen adaptation, and digestibility can substantially influence outcomes [8,9].
In New Zealand (NZ), AgResearch maintains world-class infrastructure for CH4 measurement in ruminants, including sheep and cattle respiration chambers. However, GM organisms are regulated under the Hazardous Substances and New Organisms Act 1996, which requires that GM forage for research purposes be produced under physical containment [10]. These regulatory constraints present practical challenges for generating sufficient quantities of high-quality GM forage material while preserving key compositional traits required for animal evaluation.
Herbage utilization methods strongly influence forage composition and downstream animal responses. While fresh forage offers immediate nutrient availability, ensiling provides storage stability and enables accumulation of biomass across multiple harvests. Alternative preservation methods such as freezing or haymaking are impractical or undesirable for high-lipid forages under containment due to scale limitations and increased lipid oxidation [11,12,13]. Ensiling therefore represents the most practical and containment-compatible approach for preserving HME ryegrass biomass for animal studies, and previous work indicates that a substantial proportion of FA can be retained during this process [7].
Thus, this study focuses on methodological development by establishing a reproducible, containment-compatible workflow for producing, ensiling, and storing GM HME ryegrass suitable for downstream animal-based evaluation, rather than testing agronomic or nutritional treatment effects. This enables controlled animal studies to be conducted in compliance with regulatory requirements while acknowledging inherent environmental variability.
The present study addresses this gap by developing and evaluating a contained greenhouse-based workflow for the repeated cultivation, harvesting, and ensiling of GM HME ryegrass. Specifically, we aimed to: (i) establish a reproducible method for producing silage from GM ryegrass grown under containment; (ii) assess the retention and compositional stability of total lipids and FA classes following short- and long-term ensiling; and (iii) generate characterized silage material suitable for subsequent animal feeding and CH4 mitigation studies. This study is intentionally methodological in scope and does not evaluate animal performance or CH4 emissions but provides a practical framework to support the translational evaluation of GM forage crops from plant biotechnology to animal-based research.

2. Materials and Methods

The experiment complied with law and regulations concerning the use of GM materials in research in NZ, administered by the NZ Ministry of Primary Industries. The material was grown in the AgResearch Grasslands Research Centre, greenhouse containment facilities (40°22′49.4″ S 175°36′52.1″ E) in the period from August 2022 to April 2024.

2.1. Experimental Design and Replication

Plants grown in individual pots constituted the biological experimental units for plant growth and herbage composition measurements. Repeated harvests from the same plants were treated as temporal observations and not as independent biological replicates. For all silage-related analyses, individual laboratory silos constituted the experimental units. Harvested material from multiple plants within a harvest was homogenized prior to ensiling, and each silo was treated as an independent analytical replicate.

2.2. Plant Materials and Growth Conditions

From August 2022, the plants used in this experiment were germinated from populations of T4 homozygous HME and T4 null seed on trays filled with Daltons® Seed Mix in a controlled environment room, maintained at 22 °C, humidity at 65–70%, and a light intensity of 500–1000 µmol m−2 s−1 with a 10 h photoperiod. After two weeks, the seedlings were supplied with a standard soluble fertilizer solution (Yates™ Thrive, DuluxGroup Pty Limited, Gracefield, New Zealand), consisting of 1 g/L at a rate of 200 mL/tray (30 × 45 cm2, 100 seedlings). Subsequently, the 4-week-old seedlings were transplanted into 1.2 L plastic planter bags filled with Daltons® Premium Potting Mix and grown on tables (40 pots/m2) in a containment greenhouse. The tables were lined with a 5 mm thick absorbance sheet for capillary irrigation.
Following three weeks of propagation, the first harvest was conducted (October 2022); this included all material 5–6 cm above the soil surface. Following the harvest, the plants were fertilized with a solution of 1.5 g/L Yates™ Thrive All Purpose Soluble Fertilizer at the rate of 15 L per 200 pots, applied by watering can and administered the day after harvesting. Subsequent harvests occurred at 3-week intervals by cutting foliage to a stubble height of 5–6 cm, culminating with the seventh harvest.
Following the seventh harvest, a 2–3-week gap was implemented for greenhouse sanitation (Table 1) prior to replacement with a new set of plants. This schedule ensured optimal growth conditions and systematic maintenance throughout the cultivation process.
It has to be noted that plants were initially established in 1.2 L pots and subsequently transferred to 1.8 L pots (from March 2023) to prevent root restriction during later growth stages. Pot size was consistent within each greenhouse round and was treated as a fixed factor in statistical analyses. Therefore, any variation associated with pot size is captured by the greenhouse round random effect in the model.

2.3. Greenhouse Space and Irrigation System

Two greenhouses (A and B) were utilized to grow HME and null ryegrass. The genotypes were cultivated on alternating tables to minimize environmental variations such as light, temperature, and airflow. Greenhouse A provided a total table area of 100 m2. The first section (40 m2) operated for 16 months (October 2022 to January 2024), accommodating 800 HME ryegrass plants and 800 null plants. The second section (60 m2) operated for 9 months (May 2023 onward), accommodating 1200 HME ryegrass plants and 1200 null plants. Greenhouse B operated for 14 months (December 2022 to January 2024), providing 40 m2 table area for 800 HME ryegrass plants and 800 null plants.
To optimize growth conditions for each greenhouse, the irrigation system was adjusted based on growing seasons. During summer months (December–February), cultivation tables were irrigated twice daily using 40 min intervals with an automated capillary system. The irrigation regime was reduced to 30 min once daily during winter months (June–August). During spring (September–November) and autumn (March–May), irrigation was adjusted to 20 min twice daily. Irrigation volumes were determined empirically to avoid visible water stress and maintain consistent plant growth, rather than being adjusted based on direct measurements of substrate moisture or plant water status.

2.4. Fertilization

Given that this material will be fed to animals, it is important not to supply excess N, as this would lead to “luxury consumption” by the plant, resulting in excessive nitrate levels in the leaves [15], which can be toxic to the animal consuming it. Our fertilizer regime using a solution of 1.5 g/L Yates™ Thrive (DuluxGroup Pty Limited, New Zealand) at a rate of 15 L per 200 pots, at 3-week intervals, was designed to provide the 190 kg N ha−1 y−1 allowable limit plus replace the N removed at each harvest, ensuing uniform nitrogen availability and assimilation across genotypes during vegetative growth [16]. Fertilizer inputs were applied at a consistent rate per plant throughout the experiment and were not adjusted over time. Foliar total nitrogen content, measured at each harvest, declined progressively over subsequent harvests within a round, indicating a gradual decrease in nutrient availability that may contribute to observed compositional changes. As root biomass accumulated over time, the amount of liquid fertilizer received per plant effectively decreased with successive applications, which likely contributed to reduced plant growth at later harvests.

2.5. Pest Management

Powdery mildew, aphids, thrips, and sciarid fly do not typically create issues under field conditions. However, in greenhouse environments, which are characterized by high humidity, limited air circulation, and consistently moderate temperatures, they can become problematic, resulting in major challenges when cultivating ryegrass indoors [17]. We modified the spatial arrangement to improve airflow along benches, reducing powdery mildew incidence. Electric fans were installed to accelerate airflow, effectively reducing powdery mildew infestation. Table 1 provides a list of insecticides and fungicides that are registered for use on pasture and forage crops in NZ and were used by us during the course of producing the ensiled materials. All chemical applications were conducted by approved handlers in accordance with regulations [14].
Between plant replacement cycles (after completion of the seventh harvest), cultivation tables were thoroughly cleaned one week before filling new propagation pots. Since many aphids and sciarid flies likely originate from soil and drainage systems, drains were bleached and soil treated with diflubenzuron (Table 1) prior to planting.

2.6. Ensiling Processes

The herbage material of each genotype was thoroughly mixed and manually cut into lengths ranging from 2 to 5 cm. Fresh harvests underwent subsampling and immediate freezing in liquid nitrogen, followed by storage at −80 °C for subsequent chemical analysis. The remaining material was wilted overnight at 20−22 °C, reducing the weight to approximately 50% of fresh weight, equivalent to roughly 30% DM. To promote silage fermentation, the wilted material was inoculated with a LAB solution (Ecosyl MTD/1 inoculant, Ecosyl Products Inc., Byron, IL, USA; 1.54 × 1011 cfu/g) at a recommended application rate of 106 CFUs per gram of wilted material.
Table sugar was added at 50 g kg−1 wilted fresh weight to standardize fermentation in small-scale laboratory silos, including both HME and null material. This approach was used to minimize confounding effects arising from seasonal and developmental variability in endogenous water-soluble carbohydrate (WSC) concentrations of greenhouse-grown ryegrass. Accordingly, the ensiling system was designed to support comparative assessment of genotype effects under a controlled fermentation environment, rather than to simulate commercial ensiling practice. While this addition may affect the absolute concentrations of fermentation end-products, it was applied uniformly and therefore does not confound comparisons between HME and null silage. Both LAB and sugar solutions were uniformly mixed with the wilted ryegrass. About 50 g of the completed premixed material underwent subsampling, vacuum packing, and was subsequently used for chemical analysis at 50–80 days of silage fermentation (unless otherwise indicated). The remaining material (5–20 kg, depending on season and harvest number) was placed into a vacuum bag (100–120 μm thickness), from which air was evacuated using a vacuum sealer (RHVS1, Russell Hobbs, Failsworth, UK). The vacuum process was repeated with a second outer bag. Silage packets were stored in a dimly lit environment at room temperature for a minimum of 30 days [7] and could be preserved for up to 2 years [18].
While many laboratory-scale silage studies employ buckets or fixed-volume vessels to simulate on-farm conditions [19,20], Johnson et al. [21] demonstrated that vacuum-packed polythene bags provide a cost-effective and flexible method for ensiling forage, allowing higher throughput and more consistent packing compared to fixed-volume vessels. This approach has been widely adopted in silage research due to its advantages in handling small sample sizes and controlling fermentation conditions. We selected vacuum bags because they accommodated variable harvest yields, allowed efficient air removal (minimizing potential spoilage at exposed surfaces), and enabled visual inspection of silage without disrupting the sample. Furthermore, it was possible to subsample and re-vacuum, enabling the material to be maintained until use in animal feeding trials. This method ensured consistent preservation while maintaining experimental control over storage conditions.
A total of 56 silage batches were produced (28 HME and 28 null).
For general chemical analysis of silage (Table 2), subsamples from 12 HME silage batches and 12 null silage batches were randomly selected (8 from Glasshouse A and 4 from Glasshouse B) and sampled between 50 and 80 days after ensiling (DAS). Independent selection for this analysis did not account for sequential harvests or seasonal effects and was intended to provide a representative snapshot of silage quality across containment facilities.
For long-term storage stability analyses (Table 3), silos were randomly selected across greenhouse facilities, sequential harvests, and seasons. To maintain paired comparisons, when an HME silo was selected, the corresponding null-genotype silo produced on the same day and under identical ensiling conditions was selected as its matched pair. Each selected silo was subsampled at 52 DAS, re-vacuum sealed, and subsequently resampled at 342 DAS, such that measurements at both time points were obtained from the same silo batches.

2.7. Chemical Analyses

Chemical analyses were conducted on silage material sampled at defined storage intervals, as described in Section 2.6, with each silo representing one analytical replicate. Depending on the intended analysis, silage subsamples were snap-frozen in liquid nitrogen and stored at −80 °C or over-dried at 65 °C for a minimum of 3 days and then stored at room temperature.
Silage DM was determined by weighing prior to and again after the oven-drying process. For freeze-dried samples, silages were subjected to a 3-day freeze-drying process and stored at −80 °C until subsequent analysis.
FA and total carbon and N were analyzed from the oven-dried samples after they were powdered. The determination of FA employed the fatty acid methyl ester analysis (FAMEs) technique and quantification via GC-FID [25,26]. The FAMEs analysis was tailored to only quantify the C16–C18 lipids since we had previously shown that these account for 98.5% of leaf lipids that are influenced by HME [4].
Total carbon and total N were determined using an elemental analyzer (Vario Max Cube, Elementar, Hesse, Germany). Crude protein was subsequently calculated on the assumption that the average N content of proteins is 16% (i.e., N × 6.25). Additional analyses, such as neutral detergent fiber (NDF, Tecator Fibertec, AOAC 2002.04), GE (bomb calorimeter), and in vitro enzymatic dry matter digestibility (DMD) [24], were conducted on freeze-dried and powdered material by the accredited nutrition laboratory at Massey University (Palmerston North, New Zealand).
Predicted ME was estimated from the equation ME1 (MJ/kg DM) = 0.153 × DMD (%) − 1.057, as reported by Auldist et al. [22], and ME2 (MJ/kg DM) = GE × DMD (kg/kg DM) × 0.82, where 0.82 represents a typical digestible energy-to-ME conversion factor [23].
WSC were extracted and quantified from 25 mg DM samples of freeze-dried plant material using the method described by Parsons et al. [27]. The soluble extract contained fructose, glucose, sucrose and fructans of a low degree of polymerization, referred to as the low molecular weight fraction (LMW). Fructans of a high molecular weight fraction (HMW) were extracted by twice mixing the remaining insoluble residue with 1 mL of water and centrifugation (13,000 rpm, 15 min), then removing the supernatant. WSCs were analyzed in LMW and HMW fractions using the anthrone method [28]. LMW were calibrated against a series of known concentrations of sucrose, and HMW were calibrated using inulin standards. All samples and standards were determined as a mean value of duplicate assays.
NH4+–N extraction involved using approximately 20 mg of freeze-dried sample homogenized with 0.5 mL of 0.1 M HCl and 0.25 mL of chloroform, as outlined by Hachiya and Okamoto [29], without any modifications. The determination of ammonium followed the method detailed by Bräutigam et al. [30].
Volatile FAs (VFAs) were extracted from 5 g of fresh silage in 50 mL of deionized water by blending to create a slurry, followed by incubation in a closed container with shaking at 130 rpm at room temperature for 1 h. The extract was filtered through a 100 μm mesh and stored at −80 °C until analysis. VFA concentrations were determined using GC-MS following an established method described by Ghidotti et al. [31].
Lactic acid (LA) was determined in approximately 100 mg of fresh silage that was ground to fine powder while maintaining the sample in liquid nitrogen. One milliliter of deionized water was added and homogenized until the mixture formed a slurry. The slurry was transferred to an ice-cold 2 mL Eppendorf tube and centrifuged at 14,000 × g at 4 °C for 5 min. The resulting 25 μL soluble fraction was then used in a reaction mix with FeCl3 solution, as demonstrated by Borshchevskaya et al. [32].
Silage pH was determined using a calibrated pH meter (Accumet™, AE150, Fisher Scientific, Auckland, New Zealand) from a subsample of 15 g of fresh silage homogenized with 50 mL of deionized water, as described by Cherney and Cherney [33]. The homogenized plant material (fresh herbage or silage) was filtered, and the water extract was weighed, transferred into a plastic vessel with a magnetic stirrer and titrated to pH 3.0 with 0.1 M HCl to release the bicarbonate ion as carbon dioxide. The water extract was then titrated up to pH 6.0 with 0.1 M NaOH. From this, the buffering capacity (BC) was calculated using the Milliequivalents of NaOH required to raise the pH of the water extract from 4.0 (±0.02) to 6.0 (±0.03) after correction for the titration value of a water blank [34]. The BC and pH values of samples were determined as a mean of duplicate assays.

2.8. Statistical Analysis

Data were analyzed using linear mixed-effects models implemented in R (version 4.5.1) using the lme4 and lmerTest packages and/or one-way analysis of variance (ANOVA), with genotype as the main effect. Where applicable, genotype and storage duration were treated as fixed effects. Season was treated as either a fixed or random effect depending on the analysis, reflecting whether seasonal differences were of direct interest or served to capture environmental variation across greenhouse rounds. Pot (plant), greenhouse round, and silo were included as random effects as appropriate to account for repeated measures and the hierarchical experimental structure [35,36]. Therefore, repeated harvests from the same plants were treated as temporal observations rather than independent biological replicates. Model assumptions were evaluated by inspection of residual plots. Estimated marginal means were calculated using the emmeans package, with Tukey adjustment applied for multiple comparisons, with significance assessed at p < 0.05. Error bars and ranges given are standard error of the mean.

3. Results

3.1. Seasonal Effects on Biomass Production Under Containment

Foliage from HME ryegrass and corresponding nulls was hand harvested from two containment greenhouse facilities, with a combined cultivated area of 140 m2. Figure 1 presents the herbage yield of HME and null ryegrass across seven consecutive harvests with a three-week regrowth interval, comparing results between spring–summer and autumn–winter growing seasons. No significant difference in yield (kg DM) per harvest was observed between the two genotypes in either greenhouse.
Higher biomass accumulation was observed during the spring–summer period compared with the autumn–winter period (p < 0.01). During the spring–summer cultivation period of 2022–2023, in both greenhouses, a notable decline in herbage growth rate was observed after the third harvests (Figure 1). As anticipated, the autumn–winter season showed reduced but stable herbage yields, indicating the grass’s ability to maintain production in controlled greenhouse conditions, even under suboptimal irradiance.

3.2. Herbage FA Content

Herbage FA contents in null plants remained stable across seven consecutive harvests with a three-week regrowth interval, showing no significant differences between spring–summer and autumn–winter growing seasons (Figure 1, green lines). However, herbage FA contents in HME plants decreased by approximately 0.5% of DM from the first to seventh harvest (Figure 1, gold dashed lines).

3.3. Seasonal Effects on Herbage Composition Prior to Ensiling

Fresh herbage DM content—approximately 10–15% DM for both HME and null ryegrass—did not significantly differ between genotypes.
In this study, BC was numerically lower in fresh HME herbage (576 ± 23.2 mmoles/kg DM) compared to null herbage (586 ± 28.0 mmoles/kg DM).
Ryegrass herbage was harvested in the morning, specifically between 9 and 10:30 am. WSC content during this period was relatively low in autumn–winter, with greater accumulation of high-molecular-weight WSCs across both genotypes (Figure 2).

3.4. Effect of Sugar Supplementation on Ensiling

Table sugar was added at 5% of wilted weight to all batches, compensating for seasonal variation in WSC levels and ensuring complete fermentation across all ryegrass material. To evaluate the impact of WSC levels on silage fermentation, an experiment was conducted where null and HME herbage were supplemented with sugar concentrations ranging from 0% to 5% of DM. As shown in Figure 3, increasing sugar levels resulted in a gradual increase in LA content (after 30 days of silage fermentation)—from ~10.5% to 16.5% DM—in both genotypes. HME silage showed numerically higher LA production across all sugar concentrations. Analysis of variance revealed that sugar supplementation rate had a highly significant effect (p < 0.001) on LA production, whereas genotype effect (p = 0.064), and genotype × sugar interaction (p = 0.845) were not significant.

3.5. Silage Production and Energy Quality Improvements

While both ryegrass genotypes achieved similar total silage yield (138 kg DM for null vs. 131 kg DM for HME), DM content (~30%), crude protein, N content and silage pH value (~4–4.2), the analysis revealed several significant genotype-specific differences (Table 2).
FA content was averaged from 12 randomly selected silage batches (50–80 days after silo packing). The FA content was significantly higher in the HME genotype than the null (4.85% vs. 2.75% DM, p < 0.001), representing a 76% increase (Table 2). Calculation details are provided in the footer of Table 2. Carbon content was also slightly, but significantly, elevated in HME (43.3% vs. 42.5% DM, p < 0.05). GE was also significantly greater (18.1 vs. 17.5 MJ/kg DM, p < 0.001). Differences in DMD and NDF were, however, not statistically significant. Both predicted ME improvements were numerically higher in HME silage, although the predicted ME did not differ significantly between HME and null silage (p = 0.7035 for predicted ME1 and p = 0.0581 for predicted ME2, Table 2).

3.6. Fermentation Characteristics

The acetic acid (HAc) content was significantly lower in HME silage (0.83% DM) compared to null silage (1.58% DM; p < 0.001) (Table 2). This value in HME silage falls slightly below the typical range for HAc concentrations in grass forage (1–3%) [37]. Butyric acid in both silages was within the expected range of 0.1–0.5% DM, and no other VFAs were detected in the silage of either genotype.
LA levels and pH did not differ significantly between genotypes. Other fermentation and compositional parameters, including BC and NH4+–N, also showed no significant differences between the two genotypes (Table 2).

3.7. Silage Quality After Long-Term Storage

Storage duration influenced silage fermentation and composition (Table 3). DM content remained relatively stable over time, and pH values across all storage periods stayed within the optimal range for both genotypes, consistently below 4.1.
HME silage maintained significantly higher FA levels than null silage at both 52 and 342 DAS, with a stable difference of 2.1–2.4% DM (Table 3). HME silage contained 5.75% FA compared to 3.59% in null silage; after 342 DAS, the difference was 5.17% vs. 2.80% DM. The FA loss between 52 and 342 DAS was statistically significant (p < 0.01).
FA composition was significantly affected by genotype and storage duration. At 52 DAS, HME silage had higher proportions of C18:1 (8.90% vs. 0.72%) and C18:2 (21.0% vs. 6.97%) and lower proportions of C16:0 (11.2% vs. 14.8%) and C18:3 (55.6% vs. 74.0%) compared with null silage. By 342 DAS, null silage showed increased C16:0, C16:1, and C18:0 and reduced C18:3, while HME silage maintained a relatively stable FA profile with enrichment of C18:1 and C18:2.
GE was significantly higher in HME compared to the null at both storage intervals (Table 3). DMD increased significantly in HME compared to null after prolonged storage, resulting in higher predicted ME for HME silage (10.8–11.6 MJ/kg DM) than null silage (10.5–10.8 MJ/kg DM; p < 0.05).
HAc levels were consistently lower in HME silage across storage periods. BC declined over time in both silages, from ~775–838 mmol/kg DM at 52 days to ~404–417 mmol/kg DM after 342 days. LA content declined from 16.2% to 10.8% DM in null silage and from 16.9% to 11.7% DM in HME silage.

4. Discussion

4.1. Feasibility of Producing GM Ryegrass Silage Under Containment

This study demonstrates the practical feasibility of producing and ensiling GM HME perennial ryegrass under physical containment over an extended production period. Despite regulatory constraints that preclude field cultivation, repeated greenhouse-based production cycles generated sufficient biomass to support ensiling, compositional characterization, and downstream material requirements. Unlike field-grown ryegrass, plants cultivated in controlled environments are subject to conditions that may affect key fermentation parameters such as DM, BC, and WSC levels. BC describes how resistant forage is to pH change, and forages with higher BC require more acid production (and thus more WSC) to achieve preservation pH [37]. Additionally, harvesting in the morning, especially during autumn–winter when sunrise is delayed, may limit WSC accumulation and influence fermentation potential [25]. Silage quality was considered acceptable, as indicated by pH values within the target range, high LA concentrations, and VFA profiles consistent with successful fermentation. This quality was achieved consistently across genotypes and storage durations, indicating that containment-compatible ensiling protocols can preserve forage material suitable for subsequent animal-based studies.
The capacity to accumulate biomass across multiple harvests and greenhouse rounds is particularly relevant for jurisdictions operating under strict GM containment regulations [10]. By enabling the production and preservation of GM forage material in a compact and stable format, the workflow presented here addresses a key translational barrier between plant biotechnology development and animal evaluation [38,39,40]. Few studies have progressed genetically modified forage traits beyond molecular or agronomic assessment to controlled animal evaluation, particularly under containment conditions [2]. Although GM crops such as herbicide-tolerant maize and soybean have been evaluated in animal feeding studies for safety and nutritional equivalence, the literature on transgenic forage plants evaluated in livestock feeding experiments remains limited [2,41]. This relative paucity of controlled trials reinforces the translational significance and novelty of the present study.
Nevertheless, it is important to note that these results demonstrate technical feasibility, fermentation performance, and compositional stability of HME ryegrass during ensiling and extended storage; they do not fully simulate commercial field production systems. Under field conditions, environmental variability may result in greater or lesser responses in traits such as biomass production, WSC accumulation, and FA content, which could in turn influence fermentation dynamics and nutritional outcomes [18,37].

4.2. Seasonal Variation, Pot Limitation, and Repeated Harvesting Effects

The decline in biomass production across seven sequential harvests, including reduced tillering rate, suggests increasing constraints on water and nutrient availability as roots approached pot capacity [42]. Increasing pot volume partially alleviated these constraints; however, further increases were logistically impractical, and pot depth may also have contributed to growth limitation [43]. These constraints are inherent to long-term greenhouse cultivation and were accounted for statistically as temporal, not independent, observations. Additionally, the higher biomass observed during the spring–summer period may reflect more favorable growing conditions, including higher temperatures and longer daylight hours; however, these factors were not directly tested in the present study [44].
The progressive decline in herbage FA concentrations in HME is likely attributable to reaching its pot capacity limit faster than the null plants, consistent with the higher relative root growth rates previously reported for HME ryegrass under standard irradiance [23]. The confined vessel volume used in this study likely imposed limitations on root development, with potential downstream effects on nutrient acquisition, particularly nitrogen uptake [42,43]. Restricted nitrogen availability can influence carbon–nitrogen balance and may constrain lipid biosynthesis, especially in genotypes with elevated carbon demand such as HME lines. In fact, FA accumulation in ryegrass has been shown to respond positively to nitrogen supply [45], given the increased metabolic investment in FA synthesis in HME plants. Together, these findings indicate that pot volume represents a practical constraint in contained HME production rather than a limitation of the genetic trait itself.
Future studies could mitigate these constraints through optimized fertigation strategies, more frequent nutrient replenishment, or the use of soilless cultivation systems to better sustain nutrient availability and root function. Such approaches would allow clearer separation of genotype-driven metabolic effects from artefacts associated with physical root confinement [46,47].

4.3. Seasonal Effects on Water-Soluble Carbohydrates and Ensiling Outcomes

Ryegrass foliage exhibits pronounced diurnal and seasonal fluctuations in non-structural carbohydrates, predominantly WSC, driven by irradiance and temperature [48]. In this study, ryegrass herbage was harvested in the morning (9–10:30 am) to maximize leaf FA content [23], but this timing coincided with relatively low WSC concentrations during autumn–winter, especially under delayed sunrise conditions.
Seasonal differences in WSC content (approximately 50 g kg−1 DM in autumn–winter versus 200–250 g kg−1 DM in spring–summer) have important implications for silage fermentation. WSC availability is a primary determinant of LA production and pH decline during ensiling [49,50,51]. In low-WSC conditions, sugar supplementation or microbial inoculation can improve fermentation outcomes and reduce the risk of spoilage [52,53]. The similar response of both genotypes to sugar supplementation observed here is consistent with previous studies demonstrating substrate-driven enhancement of LAB activity [54,55].
High moisture content and low sugar content can also promote the growth of undesirable microorganisms early in the ensiling process, leading to compromised fermentation quality [54]. It should be noted that the addition of table sugar to promote fermentation complicates direct interpretation of GE and ME differences between genotypes, as the sugar contributed to the overall energy content of both silages. Comparisons of energy content should be interpreted with caution, particularly where GE or ME are discussed, as the addition of external sugar during ensiling may influence absolute energy values. However, the consistently elevated FA content in HME silage—which was not influenced by sugar addition—represents a genuine genotypic difference and may support potential gains in animal productivity through enhanced energy density and altered rumen fermentation [56,57].

4.4. Fatty Acid Retention in HME and Compositional Stability During Ensiling and Storage

Extended storage influenced silage fermentation quality and nutrient composition [37]. The stable DM and pH values indicate that fermentation and preservation were successful across both genotypes. The higher GE and DMD in HME silage translated to increased predicted ME, highlighting the potential nutritional benefits of HME forage even after prolonged storage.
Consistently lower HAc levels in HME silage, alongside the observed decline in BC over time for both silages, indicate that HME modifications did not adversely affect fermentation stability.
The central objective of this study was to determine whether elevated lipid content in HME ryegrass could be retained following ensiling and extended storage under containment. The pronounced differences in FA composition, with HME silage enriched in unsaturated C18:1 and C18:2 and lower saturated FA proportions, suggest that HME modifications confer greater FA stability during storage, whereas polyunsaturated FAs in null silage were preferentially degraded or oxidized over time. Observed shifts in FA composition during storage were consistent with those reported for conventional ryegrass silage [58] and did not negate the lipid advantage of the HME genotype.
FA class distribution was characterized but not optimized, and no inference is made regarding the mitigation efficacy of specific FA classes. Although polyunsaturated and medium-chain FAs have been associated with CH4 suppression [6,59,60], the present study was not designed to assess mitigation outcomes.
Over the two assessed storage durations, while these observations describe trends in fatty acid composition, the underlying mechanisms cannot be determined from only two time points. We acknowledge that more frequent sampling over storage would be required to draw mechanistic conclusions. Such changes in plant FA composition can vary with storage conditions and duration, and observed trends in individual FA classes from only two times points cannot be mechanistically definitive [61].
Rather than implying a mechanistic “protection” against lipid degradation, these results demonstrate relative compositional stability of HME silage with enhanced energy-related traits without compromising silage preservation or quality during extended storage. Elevated FA retention may influence palatability, energy density, and feed value through known effects of lipids on aroma, flavor, and rumen metabolism [5,7,62,63].

4.5. Energy Content, Fermentation Profile, and Implications for Downstream Studies

Extended ensiling can alter fiber structure and protein availability through partial proteolysis and cell-wall modification [64,65]. Although NDF concentrations remained unchanged, the 4% increase in DMD observed in HME silage after prolonged storage suggests modest improvements in degradability, potentially linked to altered carbon partitioning in HME plants [25,66,67].
HME silage exhibited significantly lower HAc concentrations than null silage, while butyric acid remained within acceptable ranges for both genotypes [37]. These differences may reflect altered microbial fermentation dynamics associated with higher lipid content, as certain FAs can inhibit HAc-producing microorganisms [68]. Despite this difference, LA levels, pH and other key fermentation parameters remained stable across storage durations, indicating effective fermentation and long-term stability.
The advantageous characteristics of HME silage for at least a year storage highlights the practical value of the trait. The higher GE and ME contents of HME silage are consistent with previous reports of increased energy density in HME ryegrass [1,4], supporting its suitability for controlled animal evaluation. These findings suggest that HME modification did not adversely impact silage quality or nutritive value. The observed improvements appear to be specifically associated with enhanced energy-related traits rather than broad alterations to fermentation stability or the nutritional profile.
However, sugar supplementation during ensiling across treatments may influence the absolute values of GE and predicted ME reported here. While this approach does not affect the validity of the relative energy differences observed between HME and null genotypes, the absolute ME values should not be interpreted as directly representative of commercial silage systems. Future studies evaluating unsupplemented silages under field-relevant conditions will be important to validate the practical impact of HME forage on energy supply.

4.6. Relevance to Sheep Feeding Trial and Scope Limitations

The silage production system generated approximately 130 kg DM each of HME and null material, which was subsequently used in a controlled sheep feeding trial conducted in AgResearch’s respiration chamber facilities (24 sheep chambers) [69,70]. Based on the FA enrichment levels observed here, empirical prediction equations suggested a theoretical potential reduction in enteric CH4 emissions of approximately 10% [6]. These estimates are derived from empirical models and do not account for ruminal microbial adaptation, voluntary intake responses, or broader diet composition, all of which are known to influence in vivo methane emissions [71].
However, the animal performance and CH4 emission outcomes of that trial are reported separately and are not evaluated here. This study does not attempt to link compositional differences to animal intake, productivity, or CH4 emissions. Such responses depend on complex interactions involving rumen adaptation, intake regulation, and diet digestibility and must be evaluated directly in vivo [6,72].

4.7. Methodological Considerations and Limitations

Several limitations should be acknowledged. Pot-based cultivation constrained root volume and may have influenced growth patterns relative to field-grown ryegrass [42,43,73]. As described in Section 2.6, sugar was added to standardize fermentation in small-scale silos under containment conditions. While this approach alters the fermentation environment relative to commercial systems, it may partially obscure intrinsic genotype-related differences in silage composition to be evaluated [74,75]. Only two storage durations were evaluated, limiting inference regarding longer-term stability beyond the periods assessed. In addition, repeated harvests represent temporal measures rather than independent biological replicates and were treated accordingly in the statistical analysis.
It is also important to note that the current analysis was conducted on a subset of 12 (6 HME, and 6 null) silage batches out of total 56 batches, which may limit the generalizability of the results, given the known variability in silage composition across batches and storage conditions [76]. From a feeding trial perspective, it is essential to confirm that these compositional enhancements translate to measurable improvements in animal performance, and particularly reductions in enteric CH4 emissions, as such responses depend on complex interactions between diet composition, intake regulation, and rumen [6,72]. Furthermore, any potential differences in cultivation inputs, management requirements, or environmental tolerances between the HME and null should be assessed to evaluate the broader economic viability and scalability of HME implementation in commercial production systems [5].
Despite these constraints, the workflow reliably generated well-characterized GM silage of acceptable quality across multiple production cycles. The limitations outlined here reflect practical realities of contained GM research and do not detract from the primary objective of enabling downstream animal-based evaluation.

5. Conclusions

In conclusion, this study systematically demonstrates, for the first time, that multiple cycles of cultivation under contained conditions, ensiling, and prolonged storage do not compromise the lipid advantage of the HME ryegrass genotype. HME silage maintained enhanced FA content, energy density, and stable fermentation characteristics across storage periods, without adversely affecting key nutritional parameters. These findings confirm the robustness of HME traits under controlled production and storage conditions and highlight the potential for developing energy-dense forage for ruminant nutrition. While the workflow established here provides a reliable framework for investigating HME forage traits and silage performance, it has also been successfully applied in an in vivo feeding trial (results published separately), demonstrating practical applicability.
Importantly, this work addresses a key translational gap in GM forage research. The ensiling-based approach provides a practical and scalable means of preserving characterized GM biomass for subsequent in vivo evaluation, remains compliant with regulatory requirements, and is readily adaptable to other GM forage systems requiring contained biomass production.

Author Contributions

Conceptualization: L.J.C. and N.J.R. Formal analysis: S.W., P.A. and A.P. Funding acquisition: L.J.C. and N.J.R. Investigation: S.W. and A.P. Methodology: All Authors. Writing—original draft: S.W. Writing—review and editing: S.W., J.K., K.A.R., A.J., L.J.C. and N.J.R. All authors have read and agreed to the published version of the manuscript.

Funding

This manuscript was funded by the AgResearch Strategic Science Investment Fund through the PRJ0522733 research program.

Informed Consent Statement

Ethics, Consent to Participate, and Consent to Publish declarations: not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

Author Jakob Kleinmans was employed by the company Nutriassist Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Seasonal variation in herbage yield and fatty acid (FA) content across multiple harvests. Left panel shows spring–summer period and right panel shows autumn–winter period. Data represent mean between two greenhouse harvests of yield (kg dry matter (DM), left y-axis) and FA content (% DM, right y-axis) ± standard error of the mean for null (solid lines) and HME (dashed lines) genotypes across seven sequential harvests. Letters (a, b, c) indicate significant differences in FA levels between the first and the last harvest within each season. Yield peaks occurred at harvest 2–3 in spring–summer but remained relatively stable and lower during autumn–winter. FA content showed no different seasonal patterns, with higher and more variable levels in HME compared to null.
Figure 1. Seasonal variation in herbage yield and fatty acid (FA) content across multiple harvests. Left panel shows spring–summer period and right panel shows autumn–winter period. Data represent mean between two greenhouse harvests of yield (kg dry matter (DM), left y-axis) and FA content (% DM, right y-axis) ± standard error of the mean for null (solid lines) and HME (dashed lines) genotypes across seven sequential harvests. Letters (a, b, c) indicate significant differences in FA levels between the first and the last harvest within each season. Yield peaks occurred at harvest 2–3 in spring–summer but remained relatively stable and lower during autumn–winter. FA content showed no different seasonal patterns, with higher and more variable levels in HME compared to null.
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Figure 2. Water-soluble carbohydrate (WSC) content in two genotypes across seasonal periods. Stacked bars show mean WSC content (g/kg dry weight) ± standard error of the mean for low molecular weight (LMW, dark grey) and high molecular weight (HMW, light grey) fractions in null and HME genotypes during spring–summer and autumn–winter seasons. Analysis of variation (ANOVA) indicates highly significant seasonal effects (*** p < 0.001), with no significant genotype effects (p = 0.258) or genotype × season interaction (p = 0.363). Total WSC content was approximately 4–5 times higher during spring–summer compared to autumn–winter periods for both genotypes.
Figure 2. Water-soluble carbohydrate (WSC) content in two genotypes across seasonal periods. Stacked bars show mean WSC content (g/kg dry weight) ± standard error of the mean for low molecular weight (LMW, dark grey) and high molecular weight (HMW, light grey) fractions in null and HME genotypes during spring–summer and autumn–winter seasons. Analysis of variation (ANOVA) indicates highly significant seasonal effects (*** p < 0.001), with no significant genotype effects (p = 0.258) or genotype × season interaction (p = 0.363). Total WSC content was approximately 4–5 times higher during spring–summer compared to autumn–winter periods for both genotypes.
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Figure 3. Effect of additional sugar concentration on silage lactic acid content. Bars represent mean silage lactic acid (LA) percentage dry matter (% DM) ± standard error of the mean for null (black bars) and HME (grey bars) genotypes across increasing sugar concentrations (0, 0.5, 1.5, 2.5, and 5% dry weight) added during the ensiling process. Analysis of variation (ANOVA) shows significant effects of sugar treatment (*** p < 0.001), with marginally significant genotype effects (p = 0.064) and no genotype × sugar interaction (p = 0.845).
Figure 3. Effect of additional sugar concentration on silage lactic acid content. Bars represent mean silage lactic acid (LA) percentage dry matter (% DM) ± standard error of the mean for null (black bars) and HME (grey bars) genotypes across increasing sugar concentrations (0, 0.5, 1.5, 2.5, and 5% dry weight) added during the ensiling process. Analysis of variation (ANOVA) shows significant effects of sugar treatment (*** p < 0.001), with marginally significant genotype effects (p = 0.064) and no genotype × sugar interaction (p = 0.845).
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Table 1. Insecticides and fungicides registered for use on pastures and forage crops in New Zealand [14].
Table 1. Insecticides and fungicides registered for use on pastures and forage crops in New Zealand [14].
Active IngredientChemical Class 1Target SpeciesTrade Product 2Rate per HectareW/h Period (Days)
MethomylCarbamateaphidsOrion Methomyl 200SL1.5–2 L7
ChlorpyrifosOrganophosphateaphids, thripsNufarm Chlorpyrifos 500EC300–400 mL7
CarbendazimCarbamatepowdery mildewAdria Goldazim 500SC300–500 mL14
DiflubenzuronBenzoylureasciarid flyNufarm Dimilin40 L7
* PirimicarbCarbamateaphidsAdria Piritek250 g7
(forage brassica grazing)
* DeltamethrinPyrethroidaphids, thripsAdria Deltamax 25EC250–500 mL14
(maize grazing)
* Pirimiphos-methyl
+ permethrin		Organophosphate + pyrethroidaphids, thripsOrion Ambush750 mL–1 L7 (fodder brassicas and fodder beet)
* Azoxystrobinß-methoxyacrylatepowdery mildewSyngenta Amistar750 mL28 (wheat, barley, ryegrass seed crops—silage)
* TebuconazoleTriazolepowdery mildewBayer Folicur SC145 mL14 (peas)
* FipronilPhenylpyrazolesciarid flyAdria Recoil16 mL/300 L soil7 (vegetable brassicas)
* Approved for off-label use for animals not entering food-chain. 1 Chemical class indicating chemical structure and mode of action. 2 Formulation abbreviations: EC = emulsifiable concentrate, SL = soluble concentrate, SC = suspension concentrate.
Table 2. Production and chemical analysis of silage from null and HME genotypes.
Table 2. Production and chemical analysis of silage from null and HME genotypes.
Items (n = 12)NullHMEp Value
Total mass a
(kg DM)		138131-
% DM30.1 ± 1.1530.6 ± 1.020.7407
FA
(% DM)		2.75 ± 0.244.85 ± 0.27***
BC
(mmoles/kg DM)		735 ± 51.8754 ± 32.80.7496
pH4.21 ± 0.124.21 ± 0.090.9734
Lactic Acid
(% DM)		15.2 ± 0.4416.2 ± 0.370.1010
C
(% DM)		42.5 ± 0.2843.3 ± 0.25*
N
(% DM)		3.76 ± 0.253.84 ± 0.220.8072
CP
(% DM)		23.5 ± 1.5524.2 ± 1.450.7147
NDF
(% DM)		34.5 ± 1.9834.4 ± 2.010.9878
DMD
(kg/kg DM)		0.72 ± 0.010.73 ± 0.010.7035
GE
(MJ/kg DM)		17.5 ± 0.0618.1 ± 0.07***
Predicted ME1
(MJ/kg DM)		9.96 ± 0.1510.0 ± 0.140.7035
Predicted ME2
(MJ/kg DM)		10.3 ± 0.1510.8 ± 0.160.0581
Acetic acid
(% DM)		1.58 ± 0.180.83 ± 0.01***
NH4+-N
(g/kg DM)		0.10 ± 0.030.08 ± 0.020.5387
Data represent means ± standard error of the mean from 12 randomly selected silage batches (8 from Greenhouse A and 4 from Greenhouse B) out of 56 batches (28 HME and 28 null) collected over 16 months (October 2022 to January 2024). Total mass a represents cumulative silage production using 40 m2 Greenhouse A for 16 months, 60 m2 Greenhouse A for 9 months (May 2023 onward), and 40 m2 Greenhouse B for 14 months (December 2022 onward). Significance levels: * p < 0.05, *** p < 0.001. Predicted ME was estimated using two approaches: ME1, calculated from the equation ME (MJ/kg DM) = 0.153 × DMD (%) − 1.057 [22]; and ME2, calculated as ME (MJ/kg DM) = GE × DMD (kg/kg DM) × 0.82, where 0.82 represents a typical digestible energy-to-ME conversion factor [23]. Calculation for % increase in FA = (FAHME − FAnull) * 100/FAnull; therefore, (4.85 − 2.75) * 100/2.75 = 76%. Abbreviations: DM, dry matter; FA, fatty acid; BC, buffering capacity; C, carbon; N, nitrogen; CP, crude protein; NDF, neutral detergent fiber; DMD, dry matter digestibility; GE, gross energy; ME, metabolizable energy.
Table 3. Comparison of silage quality after long-term storage.
Table 3. Comparison of silage quality after long-term storage.
ItemsNull-52 DASHME-52 DASNull-342 DASHME-342 DASp Value
% DM29.0 ± 0.8628.5 ± 1.1627.7 ± 1.3231.0 ± 0.120.1236
pH4.01 ± 0.083.94 ± 0.084.07 ± 0.023.95 ± 0.040.7481
FA (% DM)3.59 ± 0.505.75 ± 0.42 G2.80 ± 0.20 D × G5.17 ± 0.12 D × G***
∆ Increase in FA
(% DM)		2.16 ± 0.132.37 ± 0.090.8327
C16:0 (% FA)14.8 ± 0.0111.2 ± 0.09 G21.8 ± 1.21 D × G11.3 ± 0.38 G***
C16:1 (% FA)2.69 ± 0.082.24 ± 0.005 G3.17 ± 0.06 D × G2.22 ± 0.05 G**
C18:0 (% FA)0.79 ± 0.031.14 ± 0.031.88 ± 0.13 D1.35 ± 0.20*
C18:1 (% FA)0.72 ± 0.0098.90 ± 0.04 G2.97 ± 0.22 D × G9.64 ± 0.13 G*
C18:2 (% FA)6.97 ± 0.0321.0 ± 0.02 G8.77 ± 0.06 D × G21.5 ± 0.12 G**
C18:3 (% FA)74.0 ± 0.8355.6 ± 0.5361.4 ± 2.40 D × G54.0 ± 0.65 G**
DMD (kg/kg DM)0.69 ± 0.030.74 ± 0.020.75 ± 0.0050.78 ± 0.004 G*
GE (MJ/kg DM)17.6 ± 0.1318.4 ± 0.10 G17.6 ± 0.0718.3 ± 0.07 G**
ME1 (MJ/kg DM)10.0 ± 0.4810.2 ± 0.3810.5 ± 0.0810.8 ± 0.06 G*
ME2 (MJ/kg DM)10.3 ± 0.4911.1 ± 0.4110.8 ± 0.0311.6 ± 0.02 G***
HAc (% DM)1.56 ± 0.180.85 ± 0.01 G1.34 ± 0.140.94 ± 0.05 G***
BC (mmoles/kg DM)775 ± 53.8837 ± 11.9404 ± 6.28 D417 ± 21.9 D***
LA (%DM)16.2 ± 0.3316.9 ± 0.4210.8 ± 1.11 D11.7 ± 0.98 D***
Data represent means ± standard error of the mean calculated at the silo level, with each silo constituting one experimental unit. n = 6 independent silos. Δ Increase in fatty acid content represents the difference between HME and null genotypes at each storage period. Superscript letters indicate significant differences: D indicates significant difference between storage period; G indicates significant genotype effect. Significant difference relative to the null and 52 DAS, and D × G interaction indicated by *, ** and *** representing p < 0.05, p < 0.01 and p < 0.001, respectively. ME1, calculated from the equation ME (MJ/kg DM) = 0.153 × DMD (%) − 1.057 [24]. ME2, calculated as ME (MJ/kg DM) = GE × DMD (kg/kg DM) × 0.82, where 0.82 represents a typical digestible energy-to-ME conversion factor [23]. Abbreviations: DM, dry matter; DMD, dry matter digestibility; FA, fatty acid; GE, gross energy; ME, metabolizable energy; BC, buffering capacity; LA, lactic acid; HAc, acetic acid.
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MDPI and ACS Style

Winichayakul, S.; Prentice, A.; Anderson, P.; Crowther, T.; Xue, H.; Zou, X.; Reid, M.; Richardson, K.A.; Maher, D.; Scott, R.W.; et al. Contained Ensiling of High-Lipid Perennial Ryegrass: Fermentation Quality, Fatty Acid Retention, and Storage Stability. Agriculture 2026, 16, 358. https://doi.org/10.3390/agriculture16030358

AMA Style

Winichayakul S, Prentice A, Anderson P, Crowther T, Xue H, Zou X, Reid M, Richardson KA, Maher D, Scott RW, et al. Contained Ensiling of High-Lipid Perennial Ryegrass: Fermentation Quality, Fatty Acid Retention, and Storage Stability. Agriculture. 2026; 16(3):358. https://doi.org/10.3390/agriculture16030358

Chicago/Turabian Style

Winichayakul, Somrutai, Ashley Prentice, Philip Anderson, Tracey Crowther, Hong Xue, Xiuying Zou, Michele Reid, Kim A. Richardson, Dorothy Maher, Richard W. Scott, and et al. 2026. "Contained Ensiling of High-Lipid Perennial Ryegrass: Fermentation Quality, Fatty Acid Retention, and Storage Stability" Agriculture 16, no. 3: 358. https://doi.org/10.3390/agriculture16030358

APA Style

Winichayakul, S., Prentice, A., Anderson, P., Crowther, T., Xue, H., Zou, X., Reid, M., Richardson, K. A., Maher, D., Scott, R. W., Cooney, L. J., Jonker, A., Kleinmans, J., & Roberts, N. J. (2026). Contained Ensiling of High-Lipid Perennial Ryegrass: Fermentation Quality, Fatty Acid Retention, and Storage Stability. Agriculture, 16(3), 358. https://doi.org/10.3390/agriculture16030358

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