A
Are Hull-less Barley and Lentil a Good Match? Production Performance and Co-Growth Dynamics in a Three-year Mixed Cropping Experiment in Switzerland
FilippoCarmenati1,2
YannikSchlup1,2
AndreasKägi1
JohanSix2
SusanneVogelgsang1✉Email
1Agroscope, Research group Extension Arable CropsReckenholzstrasse 1918046ZurichSwitzerland
2ETH ZurichUniversitätsstrasse 28092Sustainable Agroecosystems, ZürichSwitzerland
Filippo Carmenati1,2, Yannik Schlup 1,2, Andreas Kägi 1, Johan Six2, Susanne Vogelgsang1*
1Agroscope, Research group Extension Arable Crops, Reckenholzstrasse 191, 8046 Zurich, Switzerland
2 ETH Zurich, Sustainable Agroecosystems, Universitätsstrasse 2, 8092 Zürich, Switzerland
*Correspondance: susanne.vogelgsang@agroscope.admin.ch
Abstract
Diversifying agroecosystems through crop mixtures has been widely evaluated, demonstrating advantages over conventional sole cropping. In this three-year field experiment in central Switzerland, four lentil (Lens culinaris) cultivars were intercropped with three spring hull-less barley (Hordeum vulgare var. nudum) cultivars by substituting 25% of the lentil seed density in a replacement design. These mixtures were compared with the corresponding sole cropping systems, including both fertilized (additional nitrogen) and non-fertilized hull-less barley treatments, resulting in 22 total treatments.
Throughout the growing seasons, we recorded morphological traits (tiller number and plant height) and phenological stages (BBCH 65 in lentils and BBCH 55 in hull-less barley) to characterize the co-growth dynamics. We then correlated these traits with performance metrics: weed suppression, lodging reduction, total and partial grain yield, land equivalent ratio (LER), net effect (NE), and competitive ratio (CR).
Mixed cropping reduced both weed biomass and lodging incidence while increasing total grain production, evidenced by LER > 1 and positive overyielding. In mixed cropping, hull-less barley tiller number and lentil height increased, while lentil phenology remained unchanged. In contrast, hull-less barley exhibited reduced height and delayed heading compared to fertilized sole crops. Mixed cropping combinations with a high tiller count and more balanced height ratios showed the strongest increases in overall yield. Furthermore, pairings of early-flowering lentil cultivars with late-heading hull-less barley resulted in higher total and lentil grain yields, despite slightly lower LER and NE values.
Delayed sowing and unstable precipitation reduced the overall system performance, emphasising the advantages of early sowing for both crops.
Keywords:
co-growth dynamic
intercropping performance
legume
mixture
mixing ability
tiller number
maturing time
hull-less barley
lentil
1. Introduction
A
The global food system is under increasing pressure to safeguard both human and environmental health (Willett et al., 2019). In recent years, attention has turned towards the cultivation of legumes (Stagnari et al., 2017) and diversified cropping systems (Rosa-Schleich et al., 2019), spurred by growing interest in plant-based protein sources (Semba et al., 2021) and sustainable agricultural practices. Among these, cereal-legume intercropping emerged as a promising strategy for enhancing productivity, improving resilience to climate variability, and reducing input dependency (Brooker et al., 2015; Bedoussac et al., 2015). Intercropping between cereals and legumes offers a relatively simple way to deliver numerous benefits, including higher yields (Li et al., 2020; Yu et al., 2016), more stable production (Raseduzzaman & Jensen, 2017; Huang et al., 2024), improved land-use efficiency (Yu et al., 2015), decreased weed competition (Gu et al., 2021) and durable disease control (Zhang et al., 2019) while enabling lower reliance on synthetic inputs (Jensen et al., 2020; Gu et al., 2021) and thus reducing greenhouse gas emission (Brooker et al., 2015, 2021; Zhang et al., 2019). Furthermore, mixing crop species enhances overall ecosystem services without compromising crop yield (Ditzler et al., 2021). Incorporating underutilised crops into intercropping systems may further enhance biodiversity and sustainability in agricultural landscapes (Gregory et al., 2019; Mustafa et al., 2019).
Hence, these benefits render intercropping through underutilised crops a key approach for achieving more sustainable and resilient food systems (Brooker et al., 2021).
In Europe, considerable economic (Pool, 2023) and research effort have been placed to enhance knowledge on crop diversification practices and their application by European farmers toward innovations across the Agri-value chain (Brannan et al., 2023).
Producing inland plant-based protein food represents a concrete pathway to fulfil the increasing demand for plant-based protein products, as well as reducing import and greenhouse gas emissions.
Recent research by Keller et al. (2024) suggests that Swiss agriculture has significant potential to shift away from livestock- and fodder-intensive systems towards small-grain legumes for food purposes. Such a transition could replace up to 41% of animal-based protein consumption with plant-derived alternatives, thereby substantially reducing the sector’s environmental footprint.
Among the possible legumes proposed as alternative food, lentils (Lens culinaris Medik. subsp. culinaris) have been identified as a valuable food crop for future Swiss agriculture under scenarios of more frequent weather extremes (Heinz et al., 2024). Lentils contain important components for human nutrition such as high protein content, a rich source of minerals and water-soluble vitamins (Sanots et al., 2020; Urbano et al., 2007).
Nevertheless, lentil production in Switzerland remains limited, and agronomic knowledge about successful production is scarce due to the technical challenges related to its production. The crop was largely abandoned in the late 1940s, resulting in a loss of local expertise (Anonymous, 2019). While there has been a modest resurgence in lentil cultivation, current production levels are still not sufficient to meet the growing consumer demand (Anonymous, 2024), supplied from imports (Keller et al., 2024).
Lentil cultivation poses several challenges, especially in humid climates and under mechanized or organic systems. Their weak stems and indeterminate growth make lentils prone to lodging and yield loss under wet conditions (Wang et al., 2012). Moreover, lentil plants are not very competitive against weeds and hence, weed control is a significant constraint, particularly under low-input systems.
Intercropping lentils with a companion cereal crop may offer a potential solution by improving structural support, reducing lodging, and suppressing early-season weed species through competitive growth. Hull-less barley (Hordeum vulgare var. nudum), a subspecies of common barley (Dickin et al., 2012), presents an attractive companion crop due to its agronomic resilience and nutritional value for human consumption (Geng et al., 2022).
Intercropping performances are often measured through the implementation of metrics (Zustovi et al., 2024). However, in the context of plant-plant interaction, the selection of mixtures by including complementarity for morphological and phenological traits often implies the advantage obtained by the intercropping system (Bedoussac et al., 2015; Brooker et al., 2015; Demie et al., 2022). Cereal/legume mixtures could include systems where both species have similar phenology but contrasting morphology, or contrasting phenology and morphology, resulting in temporal and/or spatial niche complementarity (Gaudio et al., 2019). Complementarity is a paramount feature in cereal/legume intercrops grown under low-nitrogen (N) conditions, in which biological N fixation by the legume and strong competition for soil-N by the cereal may synergize to enhance yield and grain quality.
So far, previous studies on lentil intercropping focused on the overall system improvement to increase the land equivalent ratio (LER), reduce lodging and weed pressure (Wang et al., 2012, 2013a, 2013b, Tosti et al., 2023).
However, in addition to those, a better knowledge of the cultivars and their associated functional trait effects in intercropping is needed to make the selection of successful mixtures more targeted.
Morphological traits, such as the number of tillers in cereals (Mmbando, 2025; Yao et al., 2021) and plant height (Cadotte, 2017), are often used as proxies to estimate crop vigor and productivity. In addition, temporal dynamics play a crucial role in resource utilization and in reducing temporal niche overlap, which can enhance complementarity between intercrops and improve the productivity of intercropping systems (Yu et al., 2015; Dong et al., 2018).
We assumed that mixed cropping systems between lentils/hull-less (HL) barley reduced intraspecies competition for HL barley, increasing tillering, encouraging total higher yields (Zhang et al., 2021).
Besides that, a higher number of tillers can provide physical support to lentil plants, reducing lodging and weed pressure, and thereby increasing lentil yields. Moreover, differences in HL barley and lentil plant height and asynchrony in maturity should minimize interspecies competition, further enhancing overall system productivity.
The current study aims to understand the relationship of morphological and phenological traits on the production performance and co-growth dynamics of lentils and HL barley grown in sole and mixed cropping systems under field-scale conditions. We examined the following hypotheses:
1.
Mixed cropping of lentils and HL barley achieves total grain yields that are comparable to monocultures, while improving land-use efficiency.
2.
Compared to sole cropping systems, mixed system reduces lodging and weed pressure in lentils and HL barley.
3.
Higher number of tillers, reduced height ratio and phenological asynchrony in maturity are all factors positively correlated with overall improvement of mixed cropping system by increasing LER, reducing lodging and increasing weed suppression.
2. Material and methods
2.1 Study site
The field experiment was conducted over three consecutive seasons (2022, 2023, and 2024) at two Agroscope sites in Switzerland: Reckenholz (Zürich-Affoltern; altitude 444 m; 47°42'87"N, 8°51'67"E, canton Zürich) and Tänikon (Aadorf; altitude 539 m; 47°47'93"N, 8°90'68"E, canton Thurgau). Different fields were selected each year at both sites for a total of six different environments.
Soil types and field coordinates were identified using the AGSs WebGIS mapping system provided by Heller et al. (2023) based on the World Reference Base (WRB) soil classification. Detailed information regarding soil type, previous crops, and specific field operations for each experimental condition (site × year) is provided in Supplementary Material (SM) (Table A).
2.2 Weather conditions
Fig. 1
Mean daily air temperature at 5 cm and mean daily rainfall recorded in 2022, 2023 and 2024 at the site of Reckenholz (A) and Tänikon (B). The lack bars correspond to sum of daily rainfall, the black continuous lines represent the mean daily temperature for the cropping season, and the grey dashed line represent the mean daily air temperature over 30 years (1990–2020) period. The dashed green lines show the sowing days while the dashed red lines show the harvesting dates.
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Throughout the experimental seasons, Reckenholz experienced overall warmer temperatures and lower precipitation than Tänikon (Table B, SM). However, during the growing seasons, cumulative temperatures were lower at Reckenholz than at Tänikon (Fig. 1; Table C, SM).
The first season (2022) was notably drier compared with historical cumulative precipitation records (1990–2020; Fig. 1; Table B, SM). In contrast, the subsequent seasons (2023 and 2024) recorded above-average precipitation during the early stages of the growing period, followed by drier summer conditions when compared with historical averages (Table B, SM).
2.3 Experimental design and management
A randomized complete block design with four blocks was employed across the entire experiment. The study included four lentil cultivars, Anicia, Beluga, Grüne Berry Linsen, and Château Linsen, and three spring hull-less barley cultivars, Oak Ruby, Golijat, and AF Cesar, as companion cereals.
Each crop was cultivated both as a sole crop and in mixtures. Planting density was standardized at 240 plants/m², with sole cropping representing 100% of the species and mixtures sown at a 3:1 lentil-to-barley ratio. Sole cereal treatments were established under unfertilized and fertilized conditions. Fertilized treatments received a single application of mineral NPK fertilizer with 110 kg N, 95 kg P, 220 kg K ha-1, following Swiss fertilization guidelines to achieve a target of 90 kg N ha-1.
In total, 22 treatments were established: three sole unfertilized barley cropping, three sole fertilized barley, four sole lentil, and 12 mixed. To minimize border effects, all treatments were established in triplicate adjacent plots, with only the central plot used for data collection (excluding destructive sampling) and harvesting (Fig. 2).
For all treatments and years, agronomic management was identical for all plots. Year-specific management details are presented in Supplementary Material (Table A). Sowing was carried out simultaneously each season at a depth of 1.5 to 3 cm, depending on soil conditions. Each individual plot measured 9 m² (1.5 m × 6 m), and a 1.00 ± 0.05 m buffer zone was mown between plots to reduce inter-plot interference, resulting in an effective harvested area of around 8.5 m² (1.5 m × 4.75 m). No herbicides, fungicides or insecticides were applied during the cropping cycle. Harvesting of the central plots was performed using a small-scale experimental combine (Wintersteiger, Ried Austria). Grains were dried until grains reached a maximum humidity of 12%. Subsequently, seeds were cleaned using a gravity separator which separates particles based on specific weight differences, effectively removing lighter or damaged seeds from the sample and then separated using a small-scale seed separator machine (Indented Cylinder, model: LA-T, Westrup, Slagelse, Denmark) with mantle wells of 5.5 cm diameter.
Fig. 2
(a) Drone picture (09.07.2024) for the mixed cropping experiment between lentils and hull-less barley at Reckenholz. The white rectangle in dashed line corresponds to the four blocks. Each treatment was sown in triplet plots adjacent to each other (red rectangle) while measurements and harvested area correspond to the central plot from the triplets (blue rectangle). (b) Picture of sole lentil cropping (Anicia) (30.06.2023 – Reckenholz). (c) Example of mixed cropping system where hull-less barley (Golijat) overgrew lentils (Grüne Berry) reducing their structural function in reducing lodging (30.06.2023 – Reckenholz) (d) Example of a good combination of cultivars using mixed cropping (Oak Ruby – Beluga) (30.06.2023 – Reckenholz).
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2.4 Data collection
Data collection consisted of two phases. A pre-harvest phase where data were collected directly on the field with weekly assessment for the observations reported in Table 1. The post-harvest phase consisted in drying, cleaning and separating grains from mixed cropping to quantify total dry grain yield.
Table 1
Data for weed volume (*) were collected along the whole extent of the experiment. However, given the estimation errors made during the first year of data collection, for these three variables, season 2022 was excluded for the analysis.
Collected data
Method
Reference
Pre-harvest
Weed volume*
Quantified as the total percentage of ground cover multiply by the height ratio between average weed height and the main crops.
 
Phenology
Heading date (BBCH 55, for hull-less barley) and half flowering display (BBCH 65, for lentils) as the day of the year, in which 50% of the plants of the plot had fully reached the respective growing stage.
BBCH-scale: Growth stages of mono- and dicotyledonous plants. (Anonymous, JKI, 2018)
Plant height
Plant height of three randomly selected plants was measured in each plot at BBCH 59–80, by taking the average height (cm) from the ground to the top, excluding awns for barley and without stretching up bent plants.
 
Tiller number
Tillers of barley were counted collecting from three plants from the side plots of the triplets.
 
Plot lodging
Visually assessed one week before harvesting and quantified as the percentage of the plot laying on the ground.
 
Post-harvest
Dry grain yield
Measurement of cleaned, dried grain yield per components for mixed cropping as well as for sole crops. Yield values were adjusted for humidity percentage.
 
2.5 Statistical analyses
2.5.1 Indexes
Advantages related to the adoption of mixed cropping were quantified using three indexes.
Land use efficiency was quantified using the LER. The LER is defined as the ratio of the area under intercropping needed to achieve the same yields (Mead & Willey, 1980) and is estimated as the sum of partial LERs (relative yields) per crop species (pLER1 and pLER2).
where Y1 and Y2 are the yields (per unit of total area of the intercrop) of species 1 and 2 in mixed cropping and M1 and M2 are the yields of species 1 and 2 in monoculture.
The LER is a dimensionless indicator of relative yields in intercropping compared to monoculture. It does not provide information on the absolute yield increase per unit area achieved by intercropping (Li. et al., 2020a). Therefore, the absolute yield gain of species mixtures is assessed by the net effect (NE) of species mixtures on the yield per unit area (Loreau & Hector, 2001), where the NE is defined as the difference in yield or biomass between the mixture and the average of the sole crop.
where
and
are the observed yields of species 1 and 2 in mixed cropping, and
and
are the expected yields of the two crop species in mixture, which were calculated as the product of the monoculture yield and the land share (Li., et al. 2020a).
where
and
are the yields (per unit area of the respective sole crop) of species 1 and 2 in monoculture, and
and
are the land shares (sowing ratio) of species 1 and 2 in mixed cropping.
The information provided by NE and LER is complementary. The LER evaluates the comparative land use efficiency of mixed cropping, while the NE indicates how yield is produced per unit area than expected based on sole crop yields and species’ sowing proportions.
In addition, the competitive ratio (CR) describes the system dynamics measuring the competitive ability of the crops (Willey & Rao, 1980). The CR represents the ratio of individual LERs of the two crop components and considers the proportion of the crops in which they are initially sown.
Where pLER1 corresponds to the partial LER for species 1 (lentils) and LS1 is the sowing ratio in mixed cropping of lentils (0.75 of the full dose). Similarly, pLER2 refers to partial LER for species 2 (hull-less barley) with LS2 equal to the sowing ratio in mixed (0.25 of sole cropping full dose). A CR value greater than 1 indicates that species 1- lentils in our case- are more competitive than specie 2- hull-less barley. CR value of 1 implies equal competitiveness between the two crops.
2.5.2 Effect of different cropping systems, years and sites on response variables
Statistical analyses were conducted using R software, v. 3.5.1 (R Core Team, 2018). Normal distribution was visually inspected by plotting histogram. Subsequently, data normalization was performed utilizing the ‘bestNormalize’ package (Peterson, 2021) to meet the assumptions of linear mixed-effect models. To assess the effects of the cropping system (mixture versus sole crop), year, site and cultivars a linear mixed-effects model was applied using ‘lme4’ package (Bates et al., 2015), with probability testing from ‘lmerTest’ (Kuznetsova et al., 2017).
To reflect the effect of the yearly climatic and pedologic conditions within each experimental block, random effect terms were integrated into each model including each block combined with each environment (year x site x block, block_ID).
All categorical predictions (cropping system, year, site and cultivars) were coded using orthogonal sum-to-zero contrasts to ensure that main effects and interaction terms were linearly independent.
Model residuals were checked for normality using the Shapiro-Wilk test (Shapiro& Wilk, 1965) and visualized through QQ-plots (Wilk & Gnanadesikan, 1968). Regression model performance was assessed with the R package ‘performance’ (Lüdecke et al., 2021). Regression linear-mixed model (lmer) was applied to compared means of our factors (years, sites, cropping systems cultivar and their interactions) on the variable we tested while accounting for random variation among blocks given the randomized-complete-block design with four replicates adopted for this experiment.
Summary function on regression model was used to check for individual effects while ANOVA (type III) was applied to test the significance of each effect. Tables were produced using Satterthwaite's method for degrees of freedom (Bates et al., 2015). Post-hoc comparisons among groups were conducted through estimated marginal means (emmeans) adjusted with Sidak’s correction, and results were summarized with a compact letter display (CLD) (Lenth R., 2024).
Correlation between variables were first measured using the ‘corr.test’ function on the subset dataset for mixed values (Figure B in SM). To test the effect for the morphological traits on the variables a regression linear-mixed model was adopted considering the interaction as well for years and sites.
2.5.3 Effect for morphological and phenological traits with system performances
Before modelling, raw data (days to BBCH 55, days to BBCH 65, number of tillers per plant, HL barley height, lentil height) were inspected for outliers and normality via boxplots and Shapiro–Wilk tests. Missing values (< 2% per trait) were removed listwise. From the BBCH dates we derived (i) Δ maturity days = BBCH 65 – BBCH 55, and from plant heights, we computed the height ratio (HL barley height/lentil height).
We first explored bivariate relationships between each plant trait and our mixture-performance metrics (LER and NE) by calculating Pearson’s correlation coefficients and testing their significance at α = 0.05. To guard against multicollinearity among predictors, we computed variance inflation factors (VIF) from an initial full linear model; any trait exhibiting a VIF > 3 was either removed or combined with correlated variables to ensure model stability. Continuous predictors were then centered to a mean of zero and scaled to unit variance so that effect‐size estimates would be directly comparable across traits.
For each response variable (total and partial grain yield, LER, and NE), we fitted a series of linear mixed-effects models using the lmer function (‘lme4’ package). In every model, the standardized trait under investigation, year, and site were entered as fixed effects, along with their two‐way interactions (Trait × Year and Trait × Site). Random intercepts for block nested within location and for mixture identity were included where appropriate to account for the hierarchical experimental design. An information‐theoretic model‐selection approach (AICc‐based dredging via MuMIn) was used to identify the most parsimonious combination of main effects and biologically plausible interactions. Once the optimal fixed‐effects structure was determined, Type II Wald χ² tests (‘car::Anova’) assessed whether each term differed significantly from zero, and standardized coefficients (β) were extracted from the final model (lme4::fixef) to quantify the magnitude and direction of trait effects. To verify model assumptions, we inspected residual versus fitted plots and used DHARMa simulations to confirm homoscedasticity and approximate normality of residuals. Predictive performance was evaluated via leave‐one‐year‐out cross‐validation: models trained on all but one year were used to predict the held‐out year, and root‐mean‐square error (RMSE) and R² were computed. Finally, we employed the ‘emmeans’ package to generate predicted‐response curves for each trait, holding all other predictors at their mean, to identify thresholds beyond which further increases in the trait yielded diminishing returns in mixture performance.
This multi-step workflow, combining correlation screening, mixed‐effects modelling with interaction terms, rigorous model selection, and effect‐size benchmarking, ensures robust identification of phenological and morphological traits that reliably predict high‐performing barley–lentil mixtures across years and locations.
3. Results and Discussion
3.1 Environmental influence on grain yield production
Different years, cropping systems and cultivars showed significant effects on grain production, whereas different sites showed no significant effect per se for total grain production in lentil but only when interacting with different cropping systems and years (Table 2).
Total grain production decreased steadily throughout the three years (Fig. 3). When pooled across both sites and all treatments, the average median for total productivity peaked in 2022 (2.90 ± 0.06 t ha− 1), fell in 2023 (1.40 ± 0.09 t ha− 1) and reached its lowest in 2024 (0.95 ± 0.05 t ha− 1).
Different cultivars showed a significant effect on total and on components yield for HL barley and lentils.
For the first three environments (Reckenholz and Tänikon 2022 and Reckenholz 2023), Oak Ruby had the highest yield recorded as a cultivar in sole cropping. In the first environment (Reckenholz 2022), the sole unfertilized Oak Ruby averaged a median of 3.20 (± 0.08) t ha-1. In the second (Tänikon 2022) and the third environment (Reckenholz 2023), Oak Ruby showed again the highest yield for sole fertilized cropping, averaging median yield respectively of 3.95 (± 0.17) t ha-1 and 4.90 (± 0.30) t ha− 1, resulting in significantly higher values.
For environments 4 (Tänikon 2023), 5 (Reckenholz 2024), and 6 (Tänikon 2024), dry grain yields dropped (Fig. 3, figure A in SM). In environment 4 - thus same year but different site compared to environment 3 - mean yield dropped by 49% and the highest grain yield was registered for mixtures between Golijat-Beluga, averaging 2.03 (± 0.1) t ha− 1.
In the third year, hull-less barley production dropped (Fig. 3). The highest dried grain yield production was reached by sole Grüne Berry (1.7 ± 0.16) t ha− 1 in Reckenholz (environment 5) and by Oak Ruby/Beluga in Tänikon (environment 6), averaging 1.7 (± 0.11) t ha− 1.
Post-hoc test on regression model for total grain yield demonstrated that sole cropping for lentil cultivars Anicia, Grüne Berry, and Beluga yielded significantly more than all other cultivar–cropping system combinations (p < 0.05). By contrast, Château showed no significant yield difference between sole and mixed cropping. Nonetheless, Château Linsen suffered a marked yield reduction (p < 0.0001; Table E in SM) compared with the other lentil cultivars.
For the first two environments (Reckenholz and Tänikon 2022), a higher mean temperature (1.44 and 1.33°C higher) and lower precipitation (271 mm and 411 mm, − 34% and − 15%) were recorded compared with historical means (table B, table D in SM), resulting in the highest yields across all cropping systems (Fig. 3).
The subsequent year (2023) showed significant site-specific differences in yield (Table 2, Fig. 3), which we attribute to persisting rain leading to a 22-day sowing delay at Tänikon. Although the growing season lengths were similar (140 days in Reckenholz and 139 days in Tänikon), productivity differed considerably between sites for both HL barley and lentils (Table F in SM). At Reckenholz (environment 3), HL barley obtained the highest yields of the entire experiment, increasing by 26% and 24% in sole fertilized and unfertilized cropping, respectively, and 28% when mixed compared with 2022 (Table F in SM). In contrast, lentil yields declined sharply by 76% (mixed) and 68% (sole) compared with 2022. At Tänikon (environment 4), the dynamics were reversed. HL barley yields dropped by 73% (sole) and 87% (mixed) compared with 2022, while the decline in lentil yield was lower with a reduction of 30% in mixed cropping and 25% in sole cropping.
In 2024, the precipitation was slightly above the historical mean (3% at Reckenholz and 6% at Tänikon), yet overall yields were the lowest, reaching a median average of 1.1 t ha− 1. Again, frequent precipitation resulted in an even longer sowing delay of 38 days (at Reckenholz) and 20 days (at Tänikon) compared with 2023, shortening the growing season by 19 to 25 days, respectively, compared with 2022.
The drop in production observed in 2024 was not an isolated episode. As reported by swissgranum, the Swiss branch organization for cereals, oilseeds and protein plants, plant growth in 2024 was overall suboptimal due to the frequent precipitation and significantly fewer sunshine hours compared with the average of recent years, explaining the reduction in quantity and quality of the harvested goods (swissgranum, 2024).
Indeed, temperature and precipitation are major factors influencing inter-annual yield variation (Matiu et al., 2017). We assumed that the major source of yield variations was defined by the combined effect of sowing time and precipitation intensity recorded along the study period.
Late sowing and high precipitation seemed to have a greater effect in reducing HL barley performance than in lentils, highlighting HL barley’s sensitivity to wet conditions and shortened growth period and, conversely, lentil’s superior resilience under the same conditions.
Our results are in line with previous works (Cammarano et al., 2019; Hakala et al., 2012, 2020; Borrego-Benjumea et al., 2018) showing barley as a susceptible crop under wet conditions and sowing delay in temperate environments. In contrast, lentils appeared to be less susceptible to cool and wet conditions as well as sowing delay. A study by Wang et al. (2013b) on HL barley-lentil intercropping confirmed higher yields for early sown mixtures and a yield decline after late sowing for both crops. However, unlike Wang et al. (2013b), it was observed that early-sown lentils yielded poorly, particularly when HL barley exhibited vigorous growth, which might have outcompeted lentils for light and nutrients, as was the case for Reckenholz in 2023 (Fig. 3; Table F in SM).
Barley and lentils are often proposed as highly resilient crops against abiotic and biotic stresses (Witzel et al., 2009; Mahmud Al Noor et al., 2024), especially under drier conditions. However, it is often underestimated how changing rainfall patterns and weather extremes may negatively affect such crops (IPCC, 2012).
Fig. 3
Stand type refers to cropping systems: sole unfertilized hull-less barley (HL barley), sole hull-less barley + nitrogen fertilization (HL barley + N), mixed cropping (mixed), sole lentil (lentil). Median for grain yield (t ha− 1) with MAD (median absolute error) during the three years and for the two sites Reckenholz (canton Zurich) and Tänikon (canton Thurgau). Number of observations per each environment (year x site) was n = 12 for unfertilized HL barley - sole; n = 12 for hull-less barley + nitrogen - sole; n = 48 for mixed (HL barley + lentils); n = 16 for lentils – sole. Environments (x axis) correspond to each year x site. Yield dynamics among environments reported in Figure A in Supplementary Material.
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Table 2
ANOVA (Type III) results for total yield in hull-less (HL) barley (Total prod.b), in lentil (Total prod.l) systems and HL barley yield for HL barley systems (HL bar.b) and lentil production in lentil systems (Lentill)
 
Total prod.b
Total prod.l
HL bar.b
Lentill
Year
***
***
***
***
Site
**
 
***
***
Cropping System
*
***
***
***
Cultivar
***
***
***
***
Year x Site
***
 
***
***
Year x Cropping System
 
***
  
Site x Cropping System
***
***
  
Year x Cultivar
***
***
 
*
Site x Cultivar
***
 
***
***
Cropping system x Cultivar
 
***
 
***
Year x Site x Cropping System
***
***
 
***
Year x Site x Cultivar
*
  
**
Year x Cropping System x Cultivar
*
*
 
**
Site x Cropping System x Cultivar
    
Year x Site x Cropping System x Cultivar
 
*
  
Significance: ***: p < 0.001 **: p < 0.01 *: p < 0.05
    
3.2 Lentil performance: effect of mixed versus sole cropping on productivity
Few studies observed mixed cropping performances between lentils and spring barley under temperate areas (Schmidtke et al., 2004; Wang et al., 2012, 2013a, 2013b). In all the previously cited studies, mixed cropping reported improved yields compared to sole-cropped systems.
Our values obtained for the land equivalent ratio (LER) support the advantage of adopting mixed cropping systems for lentils paired with HL barley as a companion species.
Across all data (n = 269), the mean LER was 1.23 (± 0.30), and all mixtures except Golijat / Grüne Berry (0.88 ± 0.40, p > 0.05) exceeded a LER of 1 (Table 3). The partial LER was overall higher for lentils (0.78 ± 0.26) than for HL barley (0.46 ± 0.17), confirming previous findings that lentil-barley combinations often outperform sole cropping (Tosti et al., 2023; Wang et al., 2012).
Significant sources of variation for LER were found for different HL barley and lentil cultivars, as well as for lentil cultivars-by-year. Different years and sites did not have an effect per se on LER values, but only a marginal combination with different HL barley cultivars.
Year 2022 reported significantly higher values (+ 0.14) for LER with an average mean of 1.29 (± 0.05).
Among lentil cultivars, Château Linsen showed a significant positive effect in increasing LER (+ 0.31) while a negative effect was observed for Anicia (− 0.12). For HL barley cultivars, a significant increasing effect was given by AF Cesar (+ 0.08) while mixtures with Golijat tended to reduce significantly LER (− 0.09).
LER values obtained are comparable to the meta-analysis from Yu et al. (2015), showing an advantage in cereal/legume intercropping systems, averaging 1.22 (± 0.22). Specifically, considering a similar experimental setting, our results correspond to the one obtained by Wang et al. (2012) for lentil / HL barley mixtures averaging 1.38 (± 0.05) at a 3:1 sowing ratio. Similarly, average yields obtained were similar, as well as variation due to weather conditions (Wang et al., 2012).
The lower LER obtained for mixtures using Anicia as a lentil cultivar and Golijat as HL barley is a consequence of the higher productivity recorded as sole cropping for these two specific cultivars.
The significantly higher values obtained by Château Linsen (Table 4) are assumed to result from a possible positive effect given by a contamination in the seed lot with vetches (Vicia sativa), which potentially influences mixed cropping results. The improvement in LER shows the high benefit for Château Linsen when grown under mixed cropping, as reported also by average general higher partial LER for Château compared with the other cultivars.
The year effect obtained in 2022 resulted from the overall higher yield performance recorded during the first year of the experiment. As mentioned in section 3.1, lower precipitation and warmer temperature combined with a regular sowing time (beginning of March) resulted in overall higher productive performances, which have benefits as well as mixed cropping values compared with sub-optimal recorded in 2023 and 2024.
Positive NE was observed in all mixtures except Golijat/Grüne Berry (NE < 0). The main contribution to NE came from the HL barley component, which showed consistently positive average NE and a significant cultivar effect (Table 4). Mixtures with Oak Ruby significantly increased NE (+ 0.14) while Golijat showed a reduction effect on NE (− 0.15). Lentil cultivars Anicia and Château Linsen showed also a significant effect on NE. Combinations with Anicia tended to reduce NE (-0.18) while Château Linsen increased (+ 0.14)
Year, site, and their interaction also had a significant effect on overyielding, showing higher estimates in 2022 (+ 0.27) and Reckenholz (+ 0.09).
For the CR, a significant effect was found for year and lentil cultivars as independent factors, while two-way interactions year-by-site and year-by-HL barley cultivars were found to have a significant effect on CR (Table 4). AF Cesar and Golijat showed a reverse effect depending on the season. In 2022, Golijat showed a significant lowering effect (-0.32) while AF Cesar tended to increase CR by 0.46. Contrary, in 2023, AF Cesar had a negative estimate (-0.28) on CR, while Golijat had a positive (+ 0.42), meaning that for the first year (2022), combinations using Golijat tended to have higher yields compared to the lentil component, lowering lentil presence. A reverse effect was observed in 2023 with significantly lower Golijat presence. Such effects are in line with the yield dynamics registered, which presented a lowered fit for HL in 2023 and 2024. Concerning lentil cultivars, Beluga and Château Linsen increased CR significantly, meaning that those two mixtures were better at keeping HL barley contained, reducing competition.
Comparing the yield performances between mixed and sole lentil systems, lentil yielded significantly lower in mixed cropping compared with sole (− 22%). However, considering total production, a significant positive estimate was found for mixed cropping, showing an increase in overall yield of 13%. Total yields for systems using Anicia and Beluga were significantly higher compared with Château by 12% and 11.7%. The year effect was also found to be significant. Total yields obtained in 2022 were 22% higher compared with the general mean, while in 2023, they decreased by 17%.
Despite not having a significant site effect, the advantage of mixed cropping was most pronounced under Reckenholz conditions. A significantly higher total yield (+ 21%) for mixed cropping was obtained in 2023 at Reckenholz. Considering the interaction between high total grain yield and LER, the best combinations were Beluga with Oak Ruby or with AF Cesar as companion HL barley cultivars (Fig. 4).
Fig. 4
Total grain yield production and Land Equivalent Ratio (LER) depending on the cropping system and the cultivars used. Dashed lines are mean values for LER (1.23, horizontal) and total grain production (1.92, vertical). Values in quadrant II (red square) represent mixtures below average total yield and no LER advantage by mixed cropping. Quadrant I (green square) shows values with LER above 1 and total grain production above average. Quadrant IV (blue square) shows mixtures with outstanding results with both LER and total grain production above average. Quadrant III (yellow square) shows mixtures with partial advantages with LER above 1 but below average grain production.
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Table 3
Median values from three years, two locations, four replicates for total grain production per hectare (Total t ha− 1), Hull-less (HL) barley yield (HL barley t ha− 1), lentil yield (Lentils t ha − 1), LER = land equivalent ratio, NE = net effect, CR = competitive ratio. MAD = median absolute deviation, SE = standard error.
T.
HL barley cv.
Lentil cv.
Total t ha− 1
MAD
HL barley t ha− 1
MAD
Lentil t ha− 1
MAD
LER
SE
NE
SE
CR
SE
1
Oak Ruby
 
1.95
0.20
1.95
0.20
        
2
Golijat
 
1.95
0.18
1.95
0.18
        
3
AF Cesar
 
1.00
0.09
1.00
0.09
        
4
Oak Ruby + N
 
1.95
0.21
1.95
0.21
        
5
Golijat + N
 
1.50
0.14
1.50
0.14
        
6
AF Cesar + N
 
1.05
0.11
1.05
0.11
        
7
 
Anicia
1.70
0.09
  
1.70
0.09
      
8
 
Beluga
1.60
0.06
  
1.60
0.06
      
9
 
Château Linsen
0.60
0.03
  
0.60
0.03
      
10
 
Grüne Berry
1.65
0.07
  
1.65
0.07
      
11
Oak Ruby
Anicia
1.70
0.13
0.50
0.06
1.10
0.06
1.03
0.04
0.23
0.10
1.22
0.64
12
Oak Ruby
Beluga
2.00
0.10
0.50
0.06
1.40
0.04
1.21
0.06
0.45
0.12
1.26
0.19
13
Oak Ruby
Château Linsen
1.10
0.12
0.75
0.10
0.60
0.03
1.37
0.16
0.40
0.15
1.27
0.16
14
Oak Ruby
Grüne Berry
1.95
0.18
0.90
0.12
1.10
0.06
0.98
0.07
0.29
0.15
0.75
0.11
15
Golijat
Anicia
1.55
0.08
0.60
0.07
0.90
0.02
0.97
0.05
0.09
0.09
0.64
0.10
16
Golijat
Beluga
1.85
0.10
0.80
0.10
1.15
0.06
1.06
0.06
0.21
0.07
1.13
0.22
17
Golijat
Château Linsen
1.10
0.07
1.10
0.12
0.60
0.03
1.42
0.14
0.26
0.10
0.98
0.11
18
Golijat
Grüne Berry
1.25
0.08
0.85
0.10
0.60
0.04
0.80
0.05
-0.10
0.08
0.46
0.10
19
AF Cesar
Anicia
1.80
0.13
0.50
0.06
1.40
0.07
1.09
0.08
0.11
0.09
1.05
0.34
20
AF Cesar
Beluga
2.10
0.09
0.30
0.03
1.50
0.04
1.16
0.07
0.27
0.09
1.19
0.18
21
AF Cesar
Château Linsen
1.60
0.12
1.00
0.11
0.50
0.03
1.57
0.10
0.50
0.11
1.14
0.22
22
AF Cesar
Grüne Berry
2.20
0.15
1.10
0.10
1.25
0.08
1.10
0.08
0.35
0.14
0.61
0.12
Table 4
ANOVA (Type III) on indexes (LER = land equivalent ratio, NE = net effect, CR = competitive ratio)
 
LER
NE
CR
Year
*
***
***
Site
 
**
 
HL barley cv.
**
***
 
Lentil cv.
***
***
***
Year x Site
 
***
*
Year x HL barley cv.
  
***
Site x HL barley cv.
 
**
 
Year x Lentil cv.
*
*
 
Site x Lentil cv.
   
Lentil cv. x HL barley cv.
   
Year x Site x HL barley cv.
*
***
 
Year x Site x Lentil cv.
 
***
 
Year x HL barley cv. x Lentil cv.
   
Site x HL barley cv. x Lentil cv.
  
*
Year x Site x HL barley cv. x Lentil cv.
   
Significance: ***: p < 0.001 **: p < 0.01 *: p < 0.05
   
3.3 Lentil performance: effect of mixed versus sole cropping on weed suppression and lodging reduction
Analysis of variance for site, cropping system and year reported significant variation on both weed volume and lodging (Table 5).
Weed pressure was significantly lower in season 2023 (− 45%) and at Reckenholz (− 43%) compared with season 2024 and Tänikon. Mixed system reduced significantly the weed pressure by 30% while no significant effect was found for any specific lentil cultivars.
Similarly, lodging varied significantly during the experiment period. Years effect reported significantly lower values for 2022 (− 31%) and positive for 2023 (+ 17%). Location effect was also found significant, with lower values obtained at Reckenholz (− 11%) compared with Tänikon. Cultivar effect found significantly lower lodging for mixture using Beluga (− 7.8%), although no significant effect was found for cultivar-by-cropping system, suggesting a missing specific improvement for any cultivar when grown under sole or mixed cropping. Finally, the cropping system reported a significant effect, showing a reduction of 19% of plot lodging in lentil-HL barley mixtures compared with sole lentil cropping.
The main role of the cereal in mixed cropping is to reduce weed pressure and to provide mechanical support to avoid lodging. Overall, our results confirm this assumption. Earlier studies reporting higher weed suppression ability for mixtures between legume and small cereal grains compared to sole crop legume systems (Gu et al., 2021), particularly when barley was used as a companion plant (Corre-Hellou et al., 2011; Wang et al., 2012), correspond to our observations. The significantly higher weed pressure observed in Tänikon likely reflected differences in field management practices and a larger soil seed bank at this site. Still, we suggest the importance of mechanical weeding as the main method to reduce weed pressure during early crop development (Gardarin et al. 2022).
Results for lodging support our assumption that combinations for lentils-HL barley can reduce plot lodging as reported in previous studies (Anil et al., 1998; Podgorska-Lesiak & Sobkowicz, 2013; Bedoussac et al., 2015).
Table 5
P-values for the ANOVA (Type III) on weed volume and lodging in lentils. (*)
 
Weed volume
Lodging
Cropping System
***
***
Site
***
***
Year
**
***
Lentil cv.
 
***
Cropping system x site
 
***
Cropping system x year
 
***
Site x year
***
**
Cropping system x lentil cv.
  
Site x lentil cv.
  
Year x lentil cv.
*
 
Site x year x cropping system
  
Site x year x lentil cv.
 
**
Year x cropping system x lentil cv.
  
Site x cropping system x lentil cv.
  
Year x site x cropping system x lentil cv.
  
Significance: ***: p < 0.001 **: p < 0.01 *: p < 0.05
 
3.3 Effect of year and cropping systems on morphological traits
Expression of the morphological traits varied by year, by cropping systems and by cultivars (Table 6).
Overall, our results suggest an increase in canopy structure for lentil and HL barley under mixed cropping. In HL barley, tiller numbers were significantly higher in mixtures compared to sole cropping, while height increased under sole fertilized systems compared to unfertilized and mixtures (Table 6).
Different years, sites, cropping systems and two-way interaction year-by-site and year-by-cropping systems were found to significantly affect tiller numbers along the study period (Table 6).
Higher counts were found for AF Cesar and Oak Ruby compared with Golijat, despite no specific significant effect on any specific cultivar (Table 6) being noted. On the other hand, the number of tillers observed in mixtures was significantly higher compared to sole systems, with an average median of 7 tillers compared to 5 tillers from sole cropping.
Higher values were counted at Reckenholz (8 versus 5 recorded in Tänikon) and during the 2023 season, getting 17% more compared to the average (8 versus 7 in 2022 and 5 in 2024). Significant negative reduction was observed at Tänikon 2023, recording a median of 5 tillers versus 10 at Reckenholz 2023 and for sole systems in 2022, reporting the lowest average with 4 tillers, explaining the year-by-site and year-by-cropping system effect. We assume that the improved vigor registered corresponds to the better productive performance recorded for Reckenholz 2023.
A
The higher tiller count found in mixed cropping (7 versus 5 for sole cropping) resonated with the review article written by Mmbando (2025). Tillering can be impacted by planting density, which can change the resources available to individual plants (Yang et al. 2019; Yu et al. 2020; Veenstra et al. 2023a). A lower tiller number and less tillering are, in general, results of increased competition between plants for resources (Huang et al., 2013; Yu et al., 2020; Alipour Abookheili & Mobasser, 2021). Reduced planting density might encourage greater tillering and possibly higher yields (Zhang et al. 2021; Alipour Abookheili & Mobasser 2021). Similarly to Koskey et al. (2022), they found an increasing percentage of tiller index under low wheat-lentil density intercropping. We argue that the higher number of tillers found in the mixture can be a consequence of the lower density and possible lower intraspecies competition for similar resources, which may have enhanced spatial growth for HL barley.
Besides tiller numbers, plant height also presented significant variation along the study period with year, site, cropping system and cultivar, resulting in significant effect on plant height variation, as well as for two-way interaction year-by-site (Table 7). For HL barley, site-by-cropping system and cultivar-by-year reported significant variation, while these significant interactions were not observed in lentils.
Considering HL Barley, a significant effect for cropping systems is related to taller plants observed under fertilized sole cropping systems (Table 8), presenting an increase in height on average of 4 per cent compared with unfertilized systems and mixed stands. The cultivar AF Cesar was significantly shorter (50.0 ± 13.3 cm) compared with Golijat (64.5 ± 19.2 cm). Also, the year 2022 (+ 8.9%) and 2023 (+ 3.15%) showed significantly taller plants compared with 2024, as well as values for Reckenholz (+ 2.46 cm), which were higher compared with Tänikon. Year-by-site interaction confirmed significantly taller HL barley in Reckenholz in 2023 (+ 8.0 cm) and the significantly taller Golijat observed in 2022 (+ 7.45 cm).
Lentil vigor also showed improvement under mixed systems with significant decrease in height under sole cropping by 49%. In mixtures, they gain on average up to 10 cm in height from an average of 23 cm in sole cropping to 33 cm in mixtures. Anicia was significantly the shortest lentil cultivar (Table 8). Yet, when mixed with crops, its height increased by 8% compared with the others. On the other hand, Beluga and Château were found to be significantly taller cultivars, with Beluga being the tallest (35 ± 14.8 cm) among the four lentil cultivars (Table 8). Year-by-site effect recorded referred to significantly shorter lentils recorded in 2024 at Tänikon (22.0 ± 4.4 cm).
In contrast, the height ratio, calculated as HL barley height divided by lentil height, was not directly influenced by HL barley–lentil interactions but was determined independently by each species.
Mixtures with Golijat were on average higher (+ 0.35), while combinations with Beluga (-0.26) and Château (-0.24) reduced the differences between species. Variation in plant height for different seasons resulted in a significant year effect on height ratio as well. Significantly higher values were found for 2023 (+ 0.26) and 2024 (+ 1.79).
Contrary to Tosti et al. (2022), who did not find an influence of companion plants (barley and triticale) on lentil height, we support the assumption that mixed cropping improves lentil vertical growth, increasing its height. An interaction observed in the field, but not quantified, involved the number of tillers produced by HL barley and the tendrils of lentils. Fabaceae generally produce specialized leaf tendrils that twine around supports, providing a secure attachment (Hattermann et al., 2022). We assume that in mixed systems for cereals-legumes, the presence of robust cereal stems may help the vertical growth of the legume, enhancing its vertical height by creating support for the tendril anchored
3.4 Effect of the year and cropping systems on phenological traits
Similarly to morphological traits, phenology was also directly influenced by seasons, cropping systems and cultivars used (Table 6). We considered days after sowing to reach half plant flowering (BBCH 65 in legumes) and to reach half heading (BBCH 55 in cereals) as a benchmark for the phenological status. Different cropping systems did not show a significant effect on lentils, while a significant reduction was present on sole HL barley cropping systems with an observed earlier heading under sole fertilized contexts (− 2 days on average).
AF Cesar showed significant delay in heading (+ 2 days) while Golijat required fewer growing days (-1), being then an earlier maturing cultivar. Year effect referred to longer growing days registered in 2022 (+ 3 days) and 2023 (+ 7 days), while on average, Reckenholz recorded a delay heading (+ 1 day) compared with Tänikon.
A significant cultivar effect was found for flowering in lentils and their combinations for year and sites. Also, different years and sites had an independent effect on reaching flowering stage. Year 2022 and 2023 required significantly more growing days (+ 6 days in 2022 and + 5.6 days in 2023) to reach maturity compared to 2024. Also, observations in Reckenholz reported a delay in flowering by 3 days compared to Tänikon.
Anicia is confirmed as an early-flowering cultivar (− 4.9 days) while Château Linsen was a late cultivar (+ 9 days). Year-by-site effect reported significantly fewer growing days in Reckenholz 2022 (− 3 days) and significantly more growing days (+ 5 dys) in the following season 2023 to reach flowering.
Gap in reaching maturity (Δ maturity) was estimated as the difference between days after sowing registered for HL barley (BBCH 55) and days after sowing for lentil (BBCH 65).
A significant increase in Δ maturity was found for mixtures involving the HL barley AF Cesar and the lentil Anicia. AF Cesar increased Δ maturity as a heading cultivar, while Anicia increased Δ maturity as an early-flowering cultivar. Significant year effect reported lower Δ maturity days in 2022 (− 3 days) and longer in 2024 (+ 4.3 days). Site effect registered lower Δ maturity at Reckenholz. However, year-by-site effect showed significantly larger Δ maturity at Reckenholz in 2022 (3.25 days), while significantly lower for the following season (− 5 days). Combinations using AF Cesar and Anicia significantly increased Δ maturity by 2.2 days and 4.3 days. Contrary, significant reduction effects for Δ maturity were registered for Golijat (− 1 day) and Château Linsen (− 9 days) Delay or anticipation in reaching flowering did not vary significantly in lentil when grown under sole or mixed cropping systems. Contrary, HL barley showed a significant reduction in days reaching heading in sole cropping. As observed in Hauggaard-Nielsen et al. (2001) and Galanopoulou et al. (2019), the modest delay in barley phenology when grown with legume might be attributed to two reasons. Firstly, the higher N availability in sole fertilized systems may have enhanced stem elongation and grain filling, shortening the time to reach maturity compared to mixed cropping. Furthermore, the sowing delay and reduced growing season for season 2024 and season 2023 at Tänikon might have favored lentils over HL barley during the first stages of growth, particularly related to light acquisition, leading to a delay in reaching maturity. Shorter plants recorded in these three environments (respectively averaging median of 50.0, 45.0, 39.5 cm) could further represent a second factor related to the general reduced growth performance of HL barley recorded.
Table 6
P-values for the ANOVA (type III test) on morphological and phenological trait variation. Height barely stands for final height of hull-less barley, while Height lentil corresponds to final lentil height.
 
Tillers
Height barley
Height lentil
BBCH 65
BBCH 55
Year
***
***
***
***
***
Site
***
***
***
***
***
Cropping System
***
**
***
 
***
Cultivar
 
***
***
***
***
Year x Site
***
***
***
***
***
Year x Cropping System
***
*
*
  
Site x Cropping System
 
***
  
***
Year x Cultivar
 
***
 
***
***
Site x Cultivar
   
***
**
Cropping system x Cultivar
 
*
*
  
Year x Site x Cropping System
 
**
***
 
***
Year x Site x Cultivar
   
*
*
Year x Cropping System x Cultivar
  
*
 
***
Site x Cropping System x Cultivar
*
 
**
  
Year x Site x Cropping System x Cultivar
    
***
Significance: ***: p < 0.001 **: p < 0.01 *: p < 0.05
   
Table 7
P-values for the ANOVA (type III test) on height ratio (HR) and Δ maturity (difference between growing days needed for hull-less (HL) barley to reach half heading and growing days necessary for lentils to reach half plant flowering) in mixed cropping.
 
HR
Δ maturity
Year
**
***
Site
 
***
HL barley cv
***
***
Lentil cv
***
***
Year x Site
 
***
HL barley x Lentil cv
  
Significance: ***: p < 0.001 **: p < 0.01 *: p < 0.05
  
Table 8
Median values for morphological and phenological traits. Variables: count of tillers per plants (Til.); hull-less barley height (Height barley) in cm; lentil height (Height lentil.) in cm; HR (height ratio), BBCH 65 (days to reach half plant of lentil with opened flowers), BBCH 55 (days to reach half head out for hull-less barley). Δ maturity is equal to the difference in days between BBCH 55 and BBCH 65. Hull-less barley cultivars (HL barley cvs.) while lentils cultivars (Lentil cvs.), MAD stands for median absolute deviation.
HL barley cvs.
Lentil cvs.
Til.
MAD
Height bar.
MAD
Height Le.
MAD
HR
MAD
BBCH 65
MAD
BBCH 55
MAD
Δ maturity
MAD
Oak Ruby
 
5
1.48
55.0
15.6
      
87
5.93
  
Golijat
 
5
1.48
65.0
20.0
      
86
8.90
  
AF Cesar
 
6
2.97
48.5
14.1
      
92
5.93
  
Oak Ruby + N
 
5
2.22
57.0
17.1
      
85.5
9.64
  
Golijat + N
 
5
2.97
65.0
18.5
      
85.5
8.90
  
AF Cesar + N
 
6
2.97
53.5
11.9
      
86
11.86
  
 
Anicia
    
19.0
6.67
  
83
13.3
    
 
Beluga
    
27.5
11.12
  
85
11.9
    
Château Linsen
    
27.0
8.90
  
96
14.1
    
 
Grüne Berry
    
21.5
8.90
  
83
8.9
    
Oak Ruby
Anicia
8
4.45
58.5
15.6
37.5
15.57
1.43
0.24
81.5
13.3
89
7.41
7
5.93
Oak Ruby
Beluga
8
3.71
59.0
14.1
45.0
14.83
1.28
0.24
85
11.9
88.5
5.93
0
8.15
Oak Ruby
Château Linsen
7.5
3.71
47.0
14.8
34.5
14.08
1.27
0.32
96
15.6
90.5
5.19
-8
6.67
Oak Ruby
Grüne Berry
6.5
3.71
56.0
17.1
29.0
10.38
1.64
0.40
82
8.9
89
5.19
7
5.93
Golijat
Anicia
6
2.22
68.5
18.5
27.5
8.15
2.10
0.54
82
8.9
88.5
9.64
3.5
8.15
Golijat
Beluga
7
2.97
65.0
21.5
36.5
17.05
1.77
0.59
85
11.9
88
11.12
0
5.93
Golijat
Château Linsen
6.5
3.71
67.5
18.5
39.5
11.86
1.66
0.44
96.5
14.8
88.5
11.12
-8
6.67
Golijat
Grüne Berry
7
2.22
59.0
17.1
25.0
5.93
2.38
0.67
83
16.3
88.5
10.38
7
5.19
AF Cesar
Anicia
8
3.71
52.5
14.1
31.0
11.86
1.70
0.39
83
11.9
92
5.93
9.5
9.64
AF Cesar
Beluga
8
2.22
45.0
19.3
31.5
14.08
1.36
0.39
85
11.9
92
5.93
3
7.41
AF Cesar
Château Linsen
7
2.97
50.5
13.3
35.0
14.83
1.33
0.25
92
11.9
94
2.97
-4
8.90
AF Cesar
Grüne Berry
7
2.97
55.0
19.3
25.0
10.38
1.86
0.68
82
8.9
92
5.93
9
7.41
3.5 Effect of morphological traits on mixed cropping performances
Morphological disparity, measured as height ratio, significantly affected both system productivity and lodging. Estimates obtained for total and lentil grain yields as well as for LER, NE indicate a decrease in performance for mixed cropping with increasing height ratio between species (Table 9). Also, a significant positive estimate was found for height ratio and lodging (Table 10). Spearman’s correlation between height ratio and Δ maturity (r = 0.27, p < 0.0001) also supports the assumption that matching late-flowering lentils together with early-heading HL barley will likely reduce height differences, advantaging similar growth between the two partners.
Conversely, tiller numbers did not influence lentil yield, lodging, or weed volume significantly. Yet, significant coefficients were obtained for total and HL barley grain yields as well as NE and CR, suggesting that mixtures with more tillers generally exhibit greater crop dominance (lower CR) and overall higher productivity (Table 10).
The results support the assumption that canopy structure has considerable implications in intercropping systems (Willey, 1990). Preferably, combinations with reduced height differences and a higher number of tillers demonstrated higher production performances while reducing lodging (Fig. 5; Table 9). The negative estimates between height-ratio and indexes indicate a reduction in LER and NE with the increase in height differences.
The reduction in LER and NE might be explained by the higher yields obtained by taller HL barley cultivars grown in mixtures (r = 0.80, p < 0.0001). Significant height disparities can create competition or even suppression if one crop is overtaking the other (Wang et al., 2021). Correlation between HL barley height and CR showed a significant negative coefficient (r = − 0.43, p < 0.0001), suggesting that taller HL barley tends to reduce lentil competition.
Reduction in performance for lentil resulted in a reduction of performance for the entire systems, considering that the lentil sowing share was higher compared with that of HL barley (180 lentil seeds versus 60 HL barley seeds per m− 2).
Several studies proposed canopy heterogeneity as a key aspect to enhance spatial niche differentiation, increasing light capture and resource utilization (Willey 1990; Hauggaard-Nielsen & Jensen 2001; Bedoussac & Justes, 2010). Frequently, this is proposed in maize intercropping systems (Ren et al., 2025), where C4 and C3 plants are combined. However, given our results, we argue that using combinations of short-stemmed HL barley with lentils may reduce competition (ρ = -0.21, p = 0.001) while enhancing total production and land ratio.
Finally, the overall improvement in mixed cropping performances for cereal cultivars with a higher number of tillers is in line with Haug et al. (2023), indicating also in HL barley-lentil mixtures, barley genotypes with traits that provide above-average competitive ability suitable to attain a high general mixing ability. The assumption that a higher number of tillers would reduce plot lodging was partially confirmed by the correlation coefficient (ρ = − 0.28, p < 0.0001) but was not found to be significant by ANOVA type II (Table 10).
Fig. 5
Morphological traits (height ratio and numbers of tillers) and their correlation with plot lodging and total grain yield. The dashed line represents the general mean value, height ratio (1.8) and plot lodging (46.5). the solid line represents. Figure (A) shows a positive relationship between height ratio and (%) plot lodging. Spearman’s correlation was ρ = 0.45, p < 0.0001. Figure (B) shows a positive relationship between number of tillers and total yield. Mean number of tillers was 7.4 (among mixed systems) while total yield was 1.95 t ha.1. Spearman’s correlation was ρ = 0.49, p < 0.0001. HL barley = Hull-less barley
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Table 9
Effect size in percentage (%) given by each trait on the performance variables Δ maturity days, height ratio and number of tillers. Tot. prod. = total grain yield production; Lentil prod. = Lentil grain yield production HL = hull-less, LER = land equivalent ratio, NE = net effect, CR = competitive ratio, Weed vol. = weed volume.
 
Tot. prod.
Lentil prod.
HL barley prod.
LER
NE
CR
Weed vol.
Lodging
Δ maturity days
2.1***
21.0***
-10.39
-19.0***
-76.3***
  
22.9**
Heightratio
-5.16 **
-14.31*
 
-6.34**
-42.1***
 
16.4***
Number of tillers
7.25 ***
 
6.88*
 
36.1*
-15.7*
  
Significance: ***: p < 0.001 **: p < 0.01 *: p < 0.05
Table 10
P-value for ANOVA Type II Wald chi-square test on: Tot. prod. = total grain yield production; Lentil prod. = Lentil grain yield production HL = hull-less, LER = land equivalent ratio, NE = net effect, CR = competitive ratio, Weed vol. = weed volume.
 
Total prod.
Len. prod.
HL barley prod.
LER
NE
CR
Weed vol.
Lodging
Δ maturity days
***
***
 
***
***
  
**
Height ratio
**
*
 
**
***
  
***
Number of tillers
***
 
*
 
*
*
  
Δ maturity days x site
  
**
     
Δ maturity days x year
*
 
***
***
 
***
 
*
Height ratio x year
 
*
**
  
*
  
Height ratio x site
 
*
     
*
Number of tillers count x site
        
Number of tillers x year
        
Significance: ***: p < 0.001 **: p < 0.01 *: p < 0.05
     
3.6 Effect of phenological traits on mixed cropping performances
Disparity in days between reaching flowering (BBCH 65 in lentils) and heading (BBCH 55 in HL barley) growth stage was found to significantly affect mixed cropping performances.
A Type II ANOVA (Wald χ² test) on the best-fit regression models showed that Δ maturity days, height ratio, and number of tillers significantly influenced total and partial (lentil and hull-less barley) production, LER, NE, and lodging, but not weed volume (Fig. 6; Table 9).
An increase in Δ maturity days had a significant effect on total and lentil grain yields, as well as on lodging and indexes (LER, NE) (Table 9). The effect size of changes in Δ maturity days on total grain yield differed across seasons, with an average marginal increase of 2.1%. Notably, inter-annual variability further modulated this effect. In 2022, Δ maturity days had a significant positive effect compared to the grand mean with increase of 3.78%. In 2023, Δ maturity days increased by 10.3% while dropped in 2024 (-7.7%). Also, lentil production registered higher values for Δ maturity days, boosting yield by 21% when early-flowering lentils grew with late-heading HL barley. In contrast, LER and NE significantly reduced their values with increasing Δ maturity days, with a general reduction of 19% for LER and − 84.5% for NE. Plot lodging was also significantly increased with Δ maturity days (Table 9).
The positive estimates suggest that pairing early-flowering lentils together with late-heading HL barley increased total grain production, boosting lentil yields, even though there was an increased risk of lodging. Contrary to improved yields, combinations between early-flowering lentils and late-heading HL barley showed negative coefficients for the two indexes LER and NE as well as for total grain production, suggesting that combinations of early-heading HL barley with late-flowering lentils tended to improve more under mixed cropping compared to the reverse phenological mixtures. Spearman’s correlations between days to reach heading in HL barley-lentil grain yield and between days to reach flowering in lentils- HL barley grain yield reported significant increases in production for HL barley cultivars paired with late-flowering lentils (r = 0.67, p < 0.0001) while no effect was found between HL barley phenology and lentil grain yield (p > 0.05).
Therefore, according to our results, HL barley grown in mixed cropping contexts received higher benefits and influence from lentils' phenological delay rather than the other way around. Yet, to maximize lentils’ yield and total grain production - based on our results - cultivar choice should pick mixtures of early-flowering lentils with late-heading HL barley. The significant reduction for LER and NE corresponded to the reduced performance of HL barley when it showed late heading.
Beside the production increase, a significant positive effect between lodging and Δ maturity days was found. Such an effect shows that the temporal discrepancy between lentils and HL barley will likely favor lodging between early-flowering lentils, together with late-heading HL barley.
These results might be related to higher biomass observed in the field by early maturing lentil cultivars that tended to push down the overall plot, increasing lodging percentage.
For instance, combinations of AF Cesar with Grüne Berry showed the highest total grain yield, averaging 2.2 t ha− 1, positive overyielding (0.35) and the highest production for HL barley (1.1 t ha− 1). Such a mixture had the largest Δ maturity days with lentils setting flowers 9 days in advance compared with heading for HL Barley. We assumed that an earlier flowering for lentils may increase N fixation and N use by the companion plant, increasing its production. In support of this, the correlation coefficient between HL barley yield and days to reach flowering in lentils was strongly positive (r = 0.67, p < 0.0001).
To further support this mechanism, the other two mixtures, the best performing mixtures in terms of lentil production, were Beluga mixed with AF Cesar (1.50 t ha− 1) or with Oak Ruby (1.40 t ha− 1). These combinations overlapped in co-growth, matching the flowering and heading period. We argue that the reduced temporal complementarity did not boost HL barley as much as for combinations with dissimilar phenology (Golijat-Château Linsen).
Yet, these two mixtures were the second (AF Cesar-Beluga) and the third (Oak Ruby-Beluga) highest in total grain production, both with LER values above 1 (1.20 for Oak Ruby-Beluga and 1.16 for AF Cesar-Beluga).
Successful intercropping aims at a complementarity between diverse functional traits rather than competition, achieved through different resource acquisition strategies (Callaway et al., 2003; Brooker et al., 2015; Zuppinger-Dingley et al., 2014).
Intercrops between early- and late-maturing species are adopted widely to exploit the length of the growing season (Lithourgidis et al., 2011) and increase light interception over time (Keating & Carberry, 1993; Zhang et al., 2008). Our results are in line with previous studies showing how temporal discrepancy affected mixed cropping performances (Yu et al., 2015). Haug et al. (2023), who tested 8 spring barley genotypes with 27 spring pea genotypes under Swiss environments, reported significant GMA (general mixing ability) improvement for pea-traits showing early vigor, onset of flowers together, higher biomass and longer stipule length. Similarly, studies from Jensen et al. (2020) and Timaeus et al. (2022) reported that combinations between early maturing field peas with cereals release N from the roots. This happens around the time when cereal flowers and require increased N for grain filling. Furthermore, as reported by several authors (Schmidtke et al., 2004; Hauggaard-Nielsen et al., 2008; Rodriguez et al., 2020), and in the context of intercropping cereals-legumes, the ability to fix N from legume crops is the reason for the yield advantage of the cereal-legume mixture. Schmidtke et al. (2004) found that intercropping barley with lentils led to increased barley productivity, primarily due to complementary N acquisition strategies between the two species.
Given our experimental design using a replacement design within mixed cropping systems and according to our results, combining early flowering lentils with late-heading HL barley seemed to enhance overall productivity, while higher mixed cropping performances could be obtained for combinations between late-flowering lentils and early ripening HL barley.
Therefore, depending on the purpose of cultivation, cultivar selection could shift for diverse temporal maturity (Ross et al., 2004) if a higher share of one species over the other is desired.
Fig. 6
(A) Positive correlation between increasing Δ maturity days and lentil yield (t ha .1). Spearman’s correlation: ρ = 0.31, p < 0.0001. (B) Negative correlation between Δ maturity days and NE (net effect) reveals that combinations between late flowering lentils and early heading hull-less barley (HL barley) reduce overall over-yielding due to reduced performances for hull-less (HL) barley. Spearman’s correlation result: ρ = − 0.45, p < 0.0001. The dashed horizontal lines are mean values for Δ maturity (1.65) and lentil yield (0.92). Dashed vertical lines correspond to mean NE (net effect) (0.26). The solid line represents the fitted regression line describing the relationship between the variables.
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Overall ranking across multiple agronomic and yield-related traits (Fig. 7) highlighted that Oak Ruby–Beluga and AF Cesar–Château Linsen were the most balanced and stable mixtures, whereas Golijat-based mixtures generally ranked lower, confirming that cultivar choice strongly determines the performance and resilience of mixed intercropping systems.
Fig. 7
Heat-map showing the ranking of mixtures between different hull-less barley (HL barley) and lentil cultivars. The rank values for each variable ranged between12 1. The lower the total rank sum is, the better is the mixture for each variable tested. Variables are: HL (hull-less) Barley yield = partial HL barley yield obtained in mixtures, CR = competitive ratio, Δ maturity days = difference in growing days between BBCH 55 and BBCH 65, HR = height ratio, Lentil yield = partial lentil yield obtained in mixtures), lodging = % plot lodging, LER = land equivalent ratio, NE = net effect, Number of tillers (tillers count), Tot. yield = total yield production in mixed stand. Higher is the rank (max = 12) lighter is the colour. Contrary, lower is the value (min = 1) darker is the colour.
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4. Conclusions
This study confirmed that mixed cropping of lentil with HL barley is a viable alternative to sole lentil production in temperate climates. Replacing 25% of lentils with HL barley increased total dry-grain yield, despite reducing lentil yield relative to monocultures. Mixed cropping improved the LER by 23%, reduced lodging (− 19%), and enhanced weed suppression (− 30%) compared with sole crops.
Early sowing is recommended for both crops, since delayed planting impaired both morphological and yield performance. This effect was more pronounced in HL barley, indicating its greater sensitivity to environmental variation. Morphological and phenological traits varied with cultivar combination and cropping system: mixed stands increased lentil height and HL barley tiller number. Lentil phenology was unaffected by cropping system, whereas HL barley reached maturity in fewer days when fertilized. Pairing early-flowering lentil cultivars with late-heading HL barley boosted lentil yield more than barley yield.
In mixed stands, increased tillering, a lower height ratio, and synchronized maturity were associated with higher productivity and reduced lodging while not showing a direct effect on weed suppression. Correlation analyses reveal complementary trait dynamics between lentil and HL barley, offering a framework for studying other legume–cereal mixed systems. Further evaluation of diverse cultivar combinations under varied conditions could clarify functional traits that maximize barley–lentil synergy.
For implementation on farms, logistical and economic factors, such as separation ability, must be assessed. Furthermore, future studies should also examine grain-quality traits such as protein content and desirable metabolites (e.g. beta-glucans).
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Acknowledgments
The authors thank Sibilla Guillem, Léa Lötscher and Julia Holmes for excellent technical support during the data collection. We would also like to acknowledge Edward Dickin (Harper Adams University, UK), Liljana Brbaklic (Institute of Field and Vegetable Crops, Serbia), Vaculová Kateřina (Agrotest Fyto, Czech Republic) and their institutes for providing the three spring hull-less barley cultivars, Oak Ruby, AF Cesar, Golijat, respectively. We also thank Philippa von Nathusius for her valuable suggestions on improving the manuscript.
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Funding:
This research was funded by CROPDIVA (Climate resilient orphan crops for increased diversity in agriculture), under European Union’s Horizon 2020 research and innovation program (grant number 101000847).
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Conflicts of interest/Competing interests:
The authors declare that they have no conflict of interest.
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Availability of data and material:
The data of this study are available upon request.
Electronic Supplementary Material
Below is the link to the electronic supplementary material
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