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Article

Potential for Enhancing Seed Yield and Quality of Spring Oat and Hull-Less Barley Through Intercropping with Pea Under the Pannonian Climate

by
Radivoje Jevtić
*,
Vesna Župunski
,
Ljiljana Brbaklić
,
Dragan Živančev
,
Anja Dolapčev Rakić
,
Vladimir Aćin
,
Sanja Mikić
and
Branka Orbović
Institute of Field and Vegetable Crops, 21000 Novi Sad, Serbia
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(6), 1349; https://doi.org/10.3390/agronomy15061349
Submission received: 8 May 2025 / Revised: 25 May 2025 / Accepted: 28 May 2025 / Published: 30 May 2025
(This article belongs to the Special Issue Promoting Intercropping Systems in Sustainable Agriculture—2nd Edition)
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Abstract

:
The limited understanding of the factors that influence intercrop component performance continues to constrain the widespread adoption of intercropping systems. This study examined the relationships between dry yield, yield components, thousand kernel weight (TKW), hectoliter weight (HLW), and crude protein content in spring oat and hull-less barley using principal component analysis with mix data (PCA mix), general linear modeling (GLM), and regression analysis. Results showed that the total intercropping yield of spring oat and pea can match that of oat pure stands. Year, cropping system, and their interaction had significant effects on total dry yield (p < 0.001). Spring oat showed more stable seed quality across years and cultivation systems but had lower crude protein content, TKW, and HLW compared to hull-less barley. TKW and crude protein content were significantly influenced by year, crop species, and their interactions (p < 0.001), as well as cultivation practice*year interaction (p < 0.001), while cultivation practice had no significant effect on HLW (p = 0.904). A stronger negative correlation between dry yield and crude protein was observed in hull-less barley (R2 > 57.8%) than in oat (R2 < 13.9%), indicating higher protein yield trade-offs in barley. The dry yield–TKW relationship was negative in barley, reaching an R2 of 52% in 2023, but it was positive in oat (R2 = 26.6% in 2023; 28% in 2024), confirming crop-specific physiological responses under the same agro-ecological conditions.

1. Introduction

Conventional monoculture agriculture, while ensuring high yields, contributes to soil erosion and the increased resistance of pests to pesticides [1,2]. Mixed intercropping was recognized as a promising strategy for enhancing nitrogen (N) utilization in intercropping systems. However, the limited understanding of its impact on N-use efficiency remains an obstacle to wider adoption. In addition, the adoption of intercropping practices is also limited due to yield differences between pure stands and small grain intercrops, as well as an incomplete understanding of how intercropping affects the performance of individual crops.
Oat (Avena sativa) has become a crop with increased demand since it can be used as a substitute for barley and wheat, offering high nutritional value and contributing to lower greenhouse gas emissions. Fodder oats are cultivated for whole-plant use, including grazing, green forage, silage, hay, and grain [3]. They are particularly important in cold, northern regions, but they also remain valuable in Mediterranean climates as a source of winter fodder, where they are often grazed early in the season and later allowed to mature for grain production. Cultivating whole-crop oats offers livestock farmers an additional forage resource, which is particularly useful during dry summer periods when yields from conventional forage crops are limited. According to the USDA Food and Agriculture Organization (FAO), oats rank sixth or seventh globally in terms of cultivated area, following wheat, maize, rice, barley, and sorghum. Oats are also used as a companion crop in mixtures with legumes, peas, and vetch to enhance forage production [4].
Barley (Hordeum vulgare L.) ranks fourth globally in both production volume and cultivated area [5] and stands as the second-most significant cereal crop in the European Union for food and feed purposes, following wheat [5]. Compared to their hulled counterparts, hull-less barley cultivars offer superior nutritional benefits, notably a higher protein content [6,7], high β-glucan content [8], and low glycemic load [9]. Besides its benefits, hull-less barley is considered an underutilized crop due to lower yields, lower percentage of establishment, and limited breeding investments [10].
Although many studies have highlighted the beneficial effects of intercropping on ecosystem services, controversy remains regarding its impact on key agronomic traits. The effect of intercropping cultivation on the thousand kernel weight (TKW) of cereal crops remains unknown due to the complexity of the yield–TKW relationship and the diversity of environmental factors affecting that relationship. Previous studies have shown that the advantages of intercropping in nitrogen-use efficiency arise from complex mechanisms involving competitive, complementary, and facilitative interactions between grain legumes and cereal intercrops, but the mechanisms that contribute to the improved crude protein content in intercropping systems remain insufficiently understood [11].
The association between yield and yield components of wheat and other cereal crops have been largely studied, but these studies were mostly related to identifying traits that will guarantee high wheat performance when cultivated as a pure stand [12,13,14]. In mixed cropping systems, the ecological dynamics of plant–plant interactions between different varieties are fundamentally different from those observed in monocultures [15]. Stefan et al. [16] also highlighted that wheat variety performances in mixtures could be different from those in monocultures due to specificity in plant–plant interactions in mixtures. It is also noted that ideotypes and key traits identified for high performance in monocultures may not be optimal for mixtures [17,18].
The lack of knowledge of how intercropping affects the performance of individual crops was highlighted by Annicchiarico et al. [19] who reported that the mutual interactions between species create an unstable dynamic equilibrium in intercropping systems. It consequently makes it challenging to identify suitable traits for intercropped cultivars, particularly when these cultivars have been evaluated under pure stand conditions. Timaeus et al. [20] highlighted the lack of studies addressing the multifunctional aspects of species mixtures, as most research focuses on only specific components of cropping system performance. Despite extensive research, compensatory growth involving multiple factors and yield components remains poorly understood [21,22], highlighting a lack of knowledge regarding the trade-off between grain weight and grain number [23]. Consequently, the objectives of this study were to explore the following: (1) the potential for yield differential compensation between pure stands and intercrops of commercial spring oats and hull-less barley varieties when intercropped with pea, (2) the relationship between seed yield and quality parameters of spring hull-less barley and spring oat under diverse cropping systems (pure stand and intercropping with pea), and (3) the association of yield components with yield and quality parameters in hull-less barley and oat under extreme climatic fluctuations.

2. Materials and Methods

Field experiments were conducted at the experimental field of the Institute of Field and Vegetable Crops in Novi Sad, Northern Serbia, during 2022, 2023, and 2024 under Serbia’s Pannonian climate. Commercial varieties of spring oats (cv. Dunav) and hull-less barley (cv. Golijat) were cultivated with pea (cv. Partner) in mixed intercropping systems as well as pure stands. Seeding rates in the mixed intercropping systems were set at 70% for pea and 30% for oats and hull-less barley, based on the conventional seeding rates of 550 seeds/m2 for spring oat and hull-less barley, and 110 seeds/m2 for spring pea. All varieties were released by the Institute of Field and Vegetable Crops, Novi Sad, Serbia.
In general, spring hull-less barley and spring oat belong to the same grass family (Poaceae) but to different genera, which are Hordeum for hull-less barley and Avena for oat. They also diverged along different evolutionary paths; barley originates from the tribe Triticeae in the Fertile Crescent, while oat belongs to the tribe Aveneae and was domesticated in Europe or the Near East. Oat exhibits greater genomic complexity, as it is a hexaploid (2n = 42), whereas hull-less barley is a diploid (2n = 14).
The optimal time for sowing spring varieties is at the end of February and the beginning of March in all growing seasons. The soil was classified as a slightly calcareous loamy chernozem. Sowing preparation involved ploughing, disc harrowing, and cultivating. The field trial was established using a randomized block design with four replications, and each plot was divided into three subplots. One subplot covered an area of 9 m2. Harvesting took place in early July. Crops had similar maturity periods in 2022 but not in 2023 and 2024; thus, peas were manually removed from the experimental plots before harvesting the cereal crops. The yield was measured at 15% water content. Crude protein content in the seed was measured using a chemical analytical method (DUMAS). Besides crude protein content, we also analyzed thousand kernel weight (TKW) and hectoliter weight (HLW) as seed quality parameters. Ten plants in each plot were selected randomly to investigate the following yield components: head weight, kernel weight, number of kernels per spike/panicle, number of spikelets/panicles per spike/panicle, and spike/panicle length.

2.1. Climatic Conditions

Significant fluctuations in climatic factors were recorded over the three growing seasons. The data originated from the Republic Hydrometeorological Service of Serbia (http://www.hidmet.gov.rs/) (accessed on 15 April 2025). The 2024 growing season was characterized by high temperatures, a lack of precipitation, and warm winds, which were particularly limiting for legume crops. In contrast, precipitation levels in April and May of 2023 exceeded the seventeen-year average. The entire 2022 growing season exhibited a lack of precipitation, especially in March and May (Table 1).
Since spring oat performs better in moist, cooler environments and may yield more under higher precipitation, it had an advantage over hull-less barley in 2023, which is more drought-tolerant. Additionally, hull-less barley’s requirement for longer sunshine duration may have hindered its performance during the wetter 2023 season, resulting in lower yields compared to spring oat. The lack of precipitation in March and May 2022—critical periods for crop establishment and yield formation—made that season less favorable for cereal crops than 2024 and negatively affected the growth of both oat and hull-less barley.

2.2. Statisitcal Methods

The correlations between dry yield, yield components, and seed quality parameters in two crop species, as well as factors influencing these traits, were analyzed using correlation analysis (Spearman coefficient), principal component analysis (PCA), principal component analysis with mix data (PCA mix), general linear modeling (GLM), and regression analysis.
Principal component analysis was used to visualize the overall association between dry yield, seed quality parameters (crude protein content, TKW, HLW), and yield components in hull-less barley and oat, while a correlation matrix was used to standardize the measurements because they were not measured on the same scale. General linear modeling (GLM) and regression analysis were used to investigate influential factors on yield and quality parameters in two crop species since PCA and correlation analysis only show associations but do not indicate causality between predictor (year, cropping system, crop species) and dependent variables (dry yield, quality parameters). The effects of yield components on yield and quality parameters were analyzed with regression modeling. Tukey’s pairwise comparisons at a 95% confidence level were used to identify which means of the analyzed traits differed significantly.
Statistical analyses were performed using Minitab 17 Statistical Software (2010) (trial version), XLSTAT 2022.5.1, and package ‘ggplot2’ in R software (RStudio Team, 2022).

3. Results

3.1. Total Intercropping Yield of Spring Oat and Pea Shows Potential to Align with Yield of Oat Pure Stands

Our study indicated the vulnerability of legume crops when exposed to extreme weather conditions. In 2023 and 2024, pea yield (cv. Partner) did not exceed 0.4 t/ha in pure stands. However, oat (cv. Dunav) and hull-less barley (cv. Golijat) in intercropping systems contributed to overcoming legume crop losses (Figure 1).
In 2024, oat yield in the pure stand (5 t/ha) and total yield under intercropping cultivation (4.5 t/ha) were not significantly different (p ˂ 0.001), although the seeding ratio of oat in the intercropping system was 30% of the commercial one (Table 2). In addition, when grown under high temperatures in 2024, oat dry yields were not significantly different from those in 2023 when growing conditions were characterized by lower temperatures and high levels of precipitation. In 2022, yields of cereal crops were lower than in 2023 and 2024, but the relationship between oat pure stand yield and total yield of intercropping cultivation did not differ from that in 2024 (Figure 1).
In contrast to spring oat, intercropping cultivation affected the lowering of the dry yield of hull-less barley to the extent that the difference between pure stand dry yields and total dry yields under intercropping cultivation was greater than that in oat in both 2023 and 2024 (Figure 1, Table 2). This indicates different yield responses of oat and hull-less barley to intercropping cultivation practice and the same weather conditions (Figure 1). A low yield of hull-less barley under intercropping production (0.3 t/ha) in 2022 was compensated with pea, which performed better in 2022 than in 2023 and 2024 (Table 2).
General linear modeling (GLM) confirmed significant effects of the year (p ˂ 0.001), cropping system (p ˂ 0.001), and interaction between year and cropping system (p ˂ 0.001) on total dry yield as well as dry yield of cereal crops (Table 2).
Our results indicated that, under unfavorable growing conditions, pure stand oat yields and total intercropping yield were comparable, although the seeding ratio of oats in intercropping was 30% of the commercial one.

3.2. Seed Quality Parameters Were Higher in Hull-Less Barley than in Oat Intercrops and More Dependent on Yield Fluctuation Under Diverse Cropping Systems

In general, intercropping affected the lowering of dry yield of spring oat and hull-less barley, but the extent of intercrop dry yield decrement was crop-specific and dependent on the year. Seed quality parameters and their association with dry yield were also crop-specific and more affected by different cultivation practices in hull-less barley (Figure 2, Table 3).
On average, quality parameters (thousand kernel weight (TKW), hectoliter weight (HLW), crude protein) were higher in hull-less barley than in oat (Table 3). The difference in cultivation practices affected crude protein content differentials more in hull-less barley than in oats (Figure 2, Table 3). There were no significant variations in the protein content of spring oat cultivated as pure stands in 2022 (14.1%) and 2023 (14.2%) or as intercrops in 2022 (15.3%) and 2023 (14.9%). In 2024, oat crude protein contents in both pure stand (13.5%) and intercropping systems (13.3%) were lower than in 2022 and 2023; however, there were no significant effects of cultivation practices (Figure 2, Table 3). Although oats grown in intercropping systems had higher protein content in 2022 and 2023 than those in pure stands, the differences were not significant (Table 3). The thousand kernel weight (TKW) of oat was not affected by differences in cultivation practices and remained more stable over the years than the TKW of hull-less barley (Table 3).
For hull-less barley intercrops, a significant increase in protein content was recorded in 2023 (15.7%) and 2024 (15.7%) compared to pure stands in 2023 (13.6%) and 2024 (14.1%) (Figure 2, Table 3). A significant increase in TKW under intercropping cultivation was also recorded for hull-less barley in 2023 (36.7 g) when compared with that in pure stand (32.8 g), which was also associated with the greatest difference between pure stand and intercrop yields in the three years (Figure 2, Table 3). These results suggest that the increase in quality parameters under the intercropping cultivation of hull-less barley with peas is associated with a yield decrement. This is also supported by the fact that the protein content of hull-less barley reached notably higher values in 2022 under both pure stand (17.9%) and intercrop (18.2%) conditions when seed yield was lowest in the three years and did not exceed 0.3 t/ha (Table 3, Table 2).
To visualize associations between different cultivation practices, crop species, yield, and quality parameters during three-year field experiments, principal component analysis with mixed data (PCAmix) was performed. The first two dimensions contributed 64.2% to the overall variability. The contributions of the first and second dimensions were 38.9% and 25.3%, respectively (Figure 3). Overall, different cultivation systems (pure stand and intercropping with pea) grew on opposite sides of the plot origin, as well as crop species. Dry yield and quality parameters were not grouped on the factor map and contributed differently to the first two dimensions. This indicated that they were affected by different factors.
Crude protein, TKW, and HLW were more associated with each other than with yield. Quality parameters contributed more to the first dimension, while dry yield contributed to the second one. Intercropping cultivation was more associated with 2022. On the other hand, pure stands were more associated with both 2023 and 2024. The quality of association between variable categories and a particular axis was presented with squared cosine (cos2). Squared cosine showed that quality parameters had the highest degree of association with the first dimension (red color), while crop species, cropping systems, year, and dry yield had lower associations with the first two dimensions (blue color) (Figure 3). Since PCAmix is used as a tool in exploratory data analysis, further analysis was performed with GLM modeling.
General linear modeling (GLM) confirmed that year (p ˂ 0.001), crop species (p ˂ 0.001), and interaction between year and crop species (p ˂ 0.001) significantly affected the TKW, HLW, and crude protein content of cereal crops. Cultivation practice significantly affected TKW (p = 0.05) and crude protein content (p ˂ 0.001), as well as the interaction between year and cultivation practice (p ˂ 0.001), while cultivation practice did not affect the HLW of these two crop species (Table 3).

3.3. Association of Yield Components with Yield and Quality Parameters Differed in Hull-Less Barley and Oat Under the Same Agro-Ecological Conditions

To find out whether changes in specific yield components influence changes in the quality parameters of hull-less barley and oat under different cropping practices and how they relate to yield under extreme variations in weather conditions, a data analysis was conducted on data sets from 2023 and 2024, when climatic factors showed extreme variations between two growing seasons, and dry yields differed between cropping practices per growing season.
Interstingly, the correlations of all five yield components with quality parameters (crude protein, TKW, and HLW) took different directions in the two crop species and were negative for crude protein and TKW in oats, but positive for the same quality parameters in hull-less barley (Figure 4).
Head length and number of spikelets per spike/panicle increased under intercropping cultivation in both crop species, but that increment was prominent only for oat (Table 4). Significant and different directions of correlataion between protein content and TKW with head length in two crop species indicate that this yield component contributed differently to the yield stability of oat and hull-less barley. In addition, the number of spikelets per spike was significantly positively correlated with the protein content of hull-less barley and was significantly higher under intercropping cultivation in 2023, which probably affected the protein content increment of hull-less barley in the year when dry yield differentials were the highest.
Head weight, kernel weight, and the number of kernels per spike did not differ significantly between pure stand and intercropping cultivation of hull-less barley, although yield differentials were observed between the two cropping systems. The correlations of these yield components with crude protein content and TKW in hull-less barley were also not significant, although they showed a moderately positive trend (Table 4). In contrast, for oat, these three yield components did not differ between cultivation practices during the hot and dry growing season (2024) but were higher under intercropping in the wet growing season (2023) (Table 4). The correlations of all three yield components with crude protein content and TKW in oat were moderately negative and statistically significant.
HLW was positively correlated with dry yield in both crop species, but that correlation was stronger for hull-less barley. The relationship between HLW and protein content was weak and positive for both crop species (Figure 4). Among yield components, only the number of kernels per spike and kernel weight per spike were significantly moderately positively correlated with the HLW of hull-less barley. In oats, yield components were negatively correlated with HLW, but it was only for panicle length that this association was significant.
Principal component analysis was also used to visualize the overall association of yield components with dry yield and seed quality parameters in hull-less barley and oats (Figure 5a,b). Similarly to the correlation analysis, PCA indicated that yield components (head weight, number of kernels per spike, kernel weight) were negatively correlated with all quality parameters (protein content, TKW, and HLW) in oats, since angles between them were equal or close to 180° (Figure 5a). Contrary to this, the same yield components were positively correlated with quality parameters of hull-less barley, with vectors forming smaller angles than 90 (Figure 5b). The contribution of yield components to final yield achievements was shown to be crop-specific and more correlated with dry yield in hull-less barley than in oats due to the smaller angle between them.
To assess whether individual yield components specifically influenced the dry yield of oat and hull-less barley, regression modeling was conducted, including year and cultivation practice as categorical predictors. Year and cultivation practice emerged as the predominant factors affecting dry yield, with no single yield component showing a greater influence over the others. Similarly, the cropping system significantly affected crude protein content and TKW in hull-less barley, but none of the yield components had a dominant influence. In oat, no yield component had a predominant effect on protein content, while the number of kernels per panicle significantly influenced TKW (p = 0.002), and panicle length significantly affected HLW (p = 0.03).
Regression modeling also indicated that the relationship between dry yield with TKW and protein content was crop-specific. Associations between TKW and dry yields were higher in hull-less barley than in oats and had different directions. The highest value (R2 = 52%) was reached in 2023 when the dry yield differential of the pure stand and intercropping cultivation of hull-less barley was the greatest (Figure 6a). Similarly, higher levels of associations between crude protein and dry yields were also found only for hull-less barley in both 2023 (R2 = 68.2%) and 2024 (R2 = 57.8%). Coefficients of determination for crude protein and dry yield association for oat were 13.9% in 2023 and 0.4% in 2024 (Figure 6b). This could be a reason why changes in the dry yield of hull-less barley caused more changes in protein content in hull-less barley than in oat, but factors influencing that relationship must still be found.

4. Discussion

At present, most research focuses on the performance of specific components of individual species in intercropping systems, while comparative studies on the effects of different cultivation practices on the seed yield, yield components, and seed quality of cereal crops under the same agro-ecological conditions are limited. Our study revealed that the intercropping cultivation of oat and hull-less barley with pea affects agronomic traits differently, even under identical agro-ecological conditions. Although the three growing seasons were marked by extreme climatic events, such as excessive drought or precipitation, which limited the full yield potential of spring oat and hull-less barley, our findings indicate that intercropping these crop species with pea may help mitigate the effects of abiotic stressors. These results provide a valuable basis for future research on breeding and predicting the performance of oat and hull-less barley intercrops under changing agro-ecological conditions.

4.1. Spring Oat–Pea Intercropping Sustains Monocrop Oat Yield Under Unfavorable Conditions: Contrasting Associations Between Yield and Yield Components in Oat and Hull-Less Barley

Spring oat intercrops, rather than hull-less barley, showed greater potential in producing dry yields comparable to those of pure stands when grown under limited growing conditions. The lower yield performance of cereal crops under intercropping systems has been reported in many agroecological zones, and there are different reports on how the lowering of seed densities affects yield performance [24,25]. Hauggaard-Nielsen et al. [24] reported that the decrease in wheat grain yield under intercropping cultivation is related to a reduction in wheat density. Li et al. [25] observed that intercropping wheat with broad beans could produce yields comparable to pure stand cultivation; however, in their study, the plant density (plants/m2) of wheat remained the same across both cultivation methods. Since yield formation in cereals can be viewed as complementary and interdependent processes that include development, during which grains are formed, and growth, which supplies the necessary assimilates, for grain formation and filling [26], it can be expected that a complex of factors affects yield differentials between different cultivation practices and crop species. In the study of Jevtić et al. [27], changes in seeding rates differently affected the yield formation processes of different cereal crops under the same agro-ecological conditions, which also indicates that the effect of seeding rate on yield differentials should not be analyzed without the consideration of a range of interconnected factors.
In our study, the yield differential between intercropped and pure stand oat was not as pronounced as that observed in hull-less barley, even though the seeding rate under intercropping was reduced to 30% of the commercial rate. This aligns with findings from Browne et al. [26] who reported that oat seed rate had small and inconsistent effects on mean grain weight. Additionally, it has been shown that higher oat seed rates tend to reduce the number of grains per panicle [26]. A similar trend was observed in our study when reducing seeding rates under intercropping led to an increased number of grains per panicle, but this increment was only statistically significant in the wetter and cooler growing season (2023) in contrast to the hot and dry one (2024). This suggests that, in 2024, the increased number of grains per panicle likely did not contribute substantially to the stability of oat yield when comparing intercropped and sole-cropped systems, so that the other yield components were also important contributors to the yield stability of oat. In hull-less barley, lowering of the sowing ratio did not affect changes in grain weight and number of grains per spike. According to Thomason et al. [28], a higher seeding rate reduced the number of kernels per head in hulled and hull-less barley, but the reduction was more pronounced in the hulled barley. The results of our study were also consistent with those of Balouchi et al. [29], who reported that hull-less barley kernel numbers vary less with seeding rate.
Vincentin et al. [30] indicated that the relationship between increased grain weight and overall yield improvement is complex due to the trade-off between grain weight and grain number in wheat and other crops. The causes of the trade-off between grain weight and number are not fully understood, despite extensive research [21,22], and genomic studies indicated that many regions associated with grain number and grain weight coincide and have inverse phenotypic effects [23]. The lack of knowledge of mechanisms affecting the trade-off between grain weight and grain number also affects the limited understanding of how the relationship between these yield components affects yield and seed quality performances.
Intercropping oats with peas resulted in a significantly higher number of panicles per panicle and increased panicle length, but these yield components still exhibited negative correlations with dry yield. The lack of a positive correlation between increased panicle number and panicle length with oat dry yield may be explained by a compensatory growth strategy. Under intercropping conditions, plants may allocate resources toward producing more panicles as a reproductive response. However, if environmental conditions are insufficient to support effective grain filling, the additional panicles may remain underdeveloped or produce lighter grains. As a result, the overall yield does not improve, and may even decline, despite an increase in these structural yield components. This finding supports the results of Browne et al. [26], who reported that a lower seeding rate can lead to an increase in the number of panicles per panicle. In the study of Ju et al. [31], oat yield components per plant also increased with the decrease in planting density, which was explained with a lower competition at a reduced planting density, which enabled oat to make better use of available light. However, in that study, the R2 of the regression analysis between yield and panicle length and number of panicles per panicle did not follow a linear relationship and were quite low, with values of 0.252 and 0.136, respectively. In hull-less barley, the number of spikelets per spike was significantly higher under intercropping cultivation in wetter conditions. The association of this yield component with dry yield was not significant and negative, but the association with crude protein content and thousand kernel weight (TKW) was significant and positive. This indicates that the increase in spikelet number and head length under intercropping, while maintaining a similar number of grains per spike and kernel weight compared to pure stands, contributes to higher protein content and TKW at the expense of yield formation. These findings suggest that longer heads with more spikelets in hull-less barley may favor the development of fewer but better-filled grains, particularly under resource-limited intercropping conditions. This pattern reflects a classic dilution effect, where an increase in reproductive structures results in more grains, but these grains are less dense and lower in protein and weight, especially under stress or limited nutrient availability.
In order to explain the different yield responses of hull-less barley and oat to different cultivation practices, it is also important to note that, in oat, the husk composed of the lemma and palea constitutes approximately 25% of the harvested grain’s weight [26], unlike hull-less barley, where the husk is absent in the final product. Due to the substantial size and weight of oat husks, there is a risk of unfilled husks contaminating the harvested material under extreme climatic conditions. This factor should also be taken into consideration when evaluating the yield and quality performance of oat cultivars.

4.2. Seed Quality Traits Were Higher in Hull-Less Barley than in Oat and More Sensitive to Yield Variation Across Cropping Systems

Our study showed that an increase in crude protein content is not guaranteed in cereals, as was the case with the spring oat cultivar Dunav, and this appears to be closely tied to the degree of yield differentials produced by different cropping systems, as such was the case in hull-less barley. This was also supported by the fact that, in 2022, the protein content reached notably higher values under both pure stand (17.8%) and intercrop (18.1%) conditions when seed yield was lowest in the three years and did not exceed 0.3 t/ha. Our findings support the findings of Jensen et al. [11], who reported that cereals, being stronger competitors for soil nitrogen, often absorb a disproportionately large share relative to their presence in the intercrop. Previous studies have shown that the benefits of intercropping for nitrogen-use efficiency arise from complex mechanisms involving competitive, complementary, and facilitative interactions between grain legumes and cereals [11]. However, the specific mechanisms that contribute to higher crude protein content in intercropping systems remain not fully understood. Jensen et al. [32] suggested that the intercropping advantage in pea–barley systems was primarily due to the complementary use of both soil-derived and atmospheric nitrogen sources, rather than facilitative processes, where symbiotically fixed N2 is shared with the cereal component. Other studies have reported the partial transfer of fixed nitrogen from legumes to cereals, though the extent of this transfer varied considerably across experiments [33,34]. Jensen et al. [35] also proposed that nitrogen nutrition in intercropped non-legumes may be linked to nitrogen deposited in the legume rhizosphere during growth.
An increase in the TKW of cereal crops under intercropping with legumes has been reported in many studies. However, there are also studies showing that TKW is not consistently affected by different cultivation practices. In our study, increases in both crude protein content and TKW were observed under intercropping only in hull-less barley, and these increases were strongly associated with a decrease in dry yield. In the oat cultivar Dunav, the effect of cultivation practices on TKW was less pronounced compared to hull-less barley. Contrary to our findings, Jevtić et al. [27] reported that cultivation practices significantly influenced the TKW performance of cv. Dunav. In that study, the yields of cv. Dunav in 2018 and 2019 reached 6 t/ha and 9.5 t/ha, respectively, while in our study, yields did not exceed 5 t/ha. Furthermore, Jevtić et al. [27] observed a more pronounced yield reduction of cv. Dunav under intercropping with pea, which led to a TKW increase from 30 g to 34.4 g in 2018 and from 30 g to 34.5 g in 2019. In contrast, our study showed a more stable yield as well as TKW performance across different cultivation practices.
Since our findings and those of Jevtić et al. [27] are related to the same oat variety cultivated under different climatic conditions, they contribute to a broader understanding of how yield variation influences TKW in oats. The growing seasons of 2022, 2023, and 2024 in our study were marked by extreme climatic fluctuations, which negatively impacted the yield performance of oat cv. Dunav, preventing it from reaching its full yield potential under pure stand cultivation. Yield differences between cultivation practices, even under such challenging conditions, were not sufficient to influence changes in the quality parameters as they were in hull-less barely. Therefore, our results, in combination with those of Jevtić et al. [27], suggest that an increase in TKW under intercropping is linked to a specific range of yield differentials, which must be reached out under particular agro-ecological conditions to initiate changes in quality parameters. Neugschwandtner et al. [36] also reported that the TKW of oats could increase with decreasing shares of oats in oat–pea intercropping systems, but the results of our study pointed out that these relationships are highly related to the extent of yield differentials between different cultivation practices. In a hull-less barley yield, differentials between cultivation practices under extreme variations of climatic conditions were met and resulted in more prominent differences of quality parameters.
Studies have also shown inconsistent effects of nitrogen (N) availability on TKW performance in cereal crops. In some cases, soil inorganic N content was either negatively correlated or not correlated at all with TKW [37,38]. Sugár et al. [37] found that N fertilization increased yield but decreased TKW. In trials without N fertilization, the correlation between TKW and yield was not significant. Similarly, Protić et al. [38] observed that increasing N input led to a reduction in TKW. Conversely, Xu et al. [39] reported that TKW was influenced by the cropping system rather than N management. All of these studies showed different levels of correlation between yield and TKW, but our study pointed out that the evaluation of factors affecting the TKW–yield relationship should generate yield differentials to the extent that will initiate TKW differentials between treatments.
Previous studies have shown that a decrease in the nitrogen-to-carbohydrate (N/carbohydrate) ratio, shaped in part by starch content, is positively associated with TKW [40]. Grain carbohydrates, which are largely derived from photosynthesis during the grain-filling period, constitute the bulk of the endosperm alongside proteins. Therefore, the N/carbohydrate ratio plays a key role in determining TKW and should be considerd as the factor influencing TKW and yield relationship in intercropping systems.
In our study, hectoliter weight (HLW) was positively correlated with dry yield in both crop species, but this correlation was stronger for hull-less barley. However, the relationship between HLW and quality parameters (TKW, protein content) differed in two crop species, showing a positive correlation in oat and a negative correlation in hull-less barley. A higher TKW generally contributes to higher HLW, as heavier and denser grains increase bulk density. However, hulls contribute significantly to HLW in oats, so when compared with naked barley, this correlation may be less straightforward. In addition, HLW is primarily a genetic trait of the variety, which was confirmed in our study. In our study, the difference in cultivation practices did not affect changes in the HLW of both crop species.
Head weight, number of kernels per spike, and kernel weight were positively correlated with crude protein content, TKW, and HLW in hull-less barley, although the correlation was weak and negatively correlated with the same quality parameters in oat. The observation that the same yield components correlate positively with quality parameters in hull-less barley but negatively in oats reflects possibly different physiological trade-offs and genotypic strategies between the two crop species. These differences include the following: (1) Resource allocation: Hull-less barley appears more efficient in converting biomass into both yield and quality attributes (such as protein content, HLW, and TKW), while in oat, yield formation seems to be prioritized at the expense of protein content and density, likely due to a dilution effect. (2) Nitrogen use efficiency: In hull-less barley, nitrogen was more evenly partitioned between starch and protein synthesis. In contrast, oat tended to favor starch accumulation (increased weight) over protein formation. (3) Grain development: Hull-less barley showed more compact and dense grain development even when yield increased, whereas oat tended to produce lighter grains with more variable fill.
The difference in response of oat and hull-less barley to different cultivation practices concerning associations between yield and grain quality parameters could be attributed to structural variations in the oat inflorescence. According to Browne et al. [26] structural variations in the oat inflorescence affect differences in individual spikelets and grains, which influence the distribution of photosynthates during grain filling. Unlike the spike-shaped inflorescences of wheat and barley, oat has a panicle-type inflorescence, characterized by numerous spikelets borne at the ends of branches arising from several nodes along the rachis. All of these, together with the husk that contributes 25% of the harvested grain’s weight, could affect differences in yield and quality parameters associated with oat and hull-less barley.

5. Conclusions

The main contributions of intercropping to ecosystem services include promoting biodiversity, improving soil health, and reducing the need for external inputs. By growing multiple crop species together, intercropping supports more diverse habitats for beneficial insects and soil microorganisms. It also enhances nutrient cycling—particularly when legumes are included—due to their ability to fix atmospheric nitrogen. Furthermore, intercropping is expected to increase resilience to climatic variability, thereby contributing to more sustainable and ecologically balanced agricultural systems. However, the broader adoption of intercropping systems remains limited due to yield differentials between pure stands and intercropped species, as well as a lack of knowledge on how intercrop competitiveness affects agronomic traits and their interactions. Our study revealed that the associations between yield components, overall yield, and seed quality parameters are highly crop-specific, even under identical agro-ecological conditions. Comparative research on the performance of yield components in different cereal crops within the same environment is scarce; to our knowledge, this is the first study to directly address this gap. The main conclusions of this study are as follows:
  • Our results suggest that intercropping can achieve total seed yields comparable to those of oat pure stands, while potentially improving grain quality due to the presence of a legume component in the mixture. A key physiological distinction observed was that, under intercropping, hull-less barley tended to produce fewer but larger and more protein-rich kernels. In contrast, oat prioritized yield maintenance, often at the expense of grain quality.
  • The differing responses of hull-less barley and oat to pure stand and intercropping cultivation—particularly in terms of dry yield and grain quality—demonstrate that the behavior of these crops in mixtures cannot be reliably predicted based on their performance in monoculture. This highlights the need for the development of new methodologies and breeding strategies specifically tailored to intercropping systems.
  • Varied contributions of specific yield components to oat and hull-less barley yield and quality parameters were observed across growing seasons, suggesting that compensatory growth involving multiple factors should be a focus of future research. In particular, compensatory growth in spring oat and hull-less barley should be further investigated concerning variable seeding ratios and climatic conditions. Additional studies are needed to explore these factors as part of a broader network influencing crop performance under intercropping and environmental stress.

Author Contributions

Conceptualization, R.J. and V.Ž.; methodology, R.J.; software, V.Ž.; validation, R.J.; formal analysis, V.Ž.; investigation, L.B., D.Ž., A.D.R., S.M., V.A., and B.O.; resources, R.J.; data curation, V.Ž.; writing—original draft preparation, V.Ž.; writing—review and editing, R.J.; visualization, V.Ž.; supervision, R.J.; project administration, R.J.; funding acquisition, R.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by CROPDIVA-Climate resilient orphan crops for increased diversity in agriculture, the project funded from the European Union’s Horizon 2020 research and innovation program under grant agreement N°101000847.

Data Availability Statement

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

Acknowledgments

The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agronomy 15 01349 g001
Figure 1. Box plots showing total dry yields of pure stands and intercropping of: (a) oat cv. Dunav with pea cv. Partner and (b) hull-less barley cv. Golijat with pea cv. Partner over three years (2022, 2023, and 2024) at Rimski Šančevi (Serbia). Tukey’s pairwise comparisons with 95% confidence were used to provide information on differences between different cultivation practices, crop species, and years. Means with the same letters are not significantly different at α = 0.05.
Figure 1. Box plots showing total dry yields of pure stands and intercropping of: (a) oat cv. Dunav with pea cv. Partner and (b) hull-less barley cv. Golijat with pea cv. Partner over three years (2022, 2023, and 2024) at Rimski Šančevi (Serbia). Tukey’s pairwise comparisons with 95% confidence were used to provide information on differences between different cultivation practices, crop species, and years. Means with the same letters are not significantly different at α = 0.05.
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Figure 2. Box plots showing dry yield, thousand kernel weight (TKW), crude protein content, and hectoliter weight (HLW) of the following: (a) oat cv. Dunav and, (b) hull-less barley cv. Golijat cultivated as pure stands and as intercrops with pea cv. Partner in three years (2022, 2023, and 2024) at Rimski šnačevi (Serbia).
Figure 2. Box plots showing dry yield, thousand kernel weight (TKW), crude protein content, and hectoliter weight (HLW) of the following: (a) oat cv. Dunav and, (b) hull-less barley cv. Golijat cultivated as pure stands and as intercrops with pea cv. Partner in three years (2022, 2023, and 2024) at Rimski šnačevi (Serbia).
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Figure 3. Graphical representation of PCAmix analysis between dry yield, TKW, crude protein, HLW, cultivation systems, and varieties belonging to different cereal crops. Dunav is spring oat and Golijat is hull-less barley.
Figure 3. Graphical representation of PCAmix analysis between dry yield, TKW, crude protein, HLW, cultivation systems, and varieties belonging to different cereal crops. Dunav is spring oat and Golijat is hull-less barley.
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Figure 4. Heat mapps showing overall correlation between dry yield, TKW, HLW, protein content, number of spikelets per spike or panicles per panicle, head length, head weight, kernel weight per head, number of kernels per spike/panicle, plant height, number of stems, and number of nodes of oat cv. Dunav and hull-less barley cv. Golijat. Green colors indicate positive correlations and red colors indicate negative correlations. The closer the correlation coefficient is to +1 or −1, the deeper the color intensity, reflecting a stronger relationship.
Figure 4. Heat mapps showing overall correlation between dry yield, TKW, HLW, protein content, number of spikelets per spike or panicles per panicle, head length, head weight, kernel weight per head, number of kernels per spike/panicle, plant height, number of stems, and number of nodes of oat cv. Dunav and hull-less barley cv. Golijat. Green colors indicate positive correlations and red colors indicate negative correlations. The closer the correlation coefficient is to +1 or −1, the deeper the color intensity, reflecting a stronger relationship.
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Figure 5. Principal component analyis showing the assocation between dry yield, TKW, HLW, protein content, number of spikelets per spike or panicles per panicle, head length, head weight, kernel weight per head, number of kernels per spike/panicle of (a) oat cv. Dunav and (b) hull-less barley cv. Golijat.
Figure 5. Principal component analyis showing the assocation between dry yield, TKW, HLW, protein content, number of spikelets per spike or panicles per panicle, head length, head weight, kernel weight per head, number of kernels per spike/panicle of (a) oat cv. Dunav and (b) hull-less barley cv. Golijat.
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Figure 6. Regression modeling of (a) dry yield with TKW (b) and dry yield with crude protein content of oat cv. Dunav and hull-less barley cv. Golijat in three years (2022, 2023, and 2024) when both pure stand and intercropping cultivation were taken into consideration.
Figure 6. Regression modeling of (a) dry yield with TKW (b) and dry yield with crude protein content of oat cv. Dunav and hull-less barley cv. Golijat in three years (2022, 2023, and 2024) when both pure stand and intercropping cultivation were taken into consideration.
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Table 1. Climatic conditions in three growing seasons at Rimski šančevi (Serbia).
Table 1. Climatic conditions in three growing seasons at Rimski šančevi (Serbia).
YearT
Feb.
°C		Prec. Feb.
mm		T
March
°C		Prec. March
mm		T
April
°C		Prec. April
mm		T
May
°C		Prec. May
mm
20225.723.75.61.110.954.519.217.9
20233.657.29.025.310.463.917.2124.8
20249.8911.21615.521.718.979
Average 2006–20233.344.17.443.012.843.517.391.0
Table 2. The most influencing factors on total dry yield and dry yield of oat cv. Dunav and hull-less barley cv. Golijat cultivated in pure stands and intercropping systems with pea cv. Partner in three years (2022, 2023, and 2024) at Rimski šnačevi (Serbia).
Table 2. The most influencing factors on total dry yield and dry yield of oat cv. Dunav and hull-less barley cv. Golijat cultivated in pure stands and intercropping systems with pea cv. Partner in three years (2022, 2023, and 2024) at Rimski šnačevi (Serbia).
VarietyCultivation
Practice		Dry Yield Cereal
t/ha		Total Dry Yield
t/ha		VarietyCultivation
Practice		Dry Yield Pea
t/ha
202220232024202220232024 202220232024
Dunav (oat)Pure stand1.74.85.0 Partner
(pea)		Pure stand1.10.40.4
Intercropping with Partner0.93.64.41.53.84.5 Intercropping with Dunav0.50.20.1
Golijat (hull-less barley)Pure stand0.32.93.7
Intercropping with Partner0.31.42.70.91.82.8 Intercropping with Golijat0.60.40.1
p p p
GLMYear ˂0.001 ˂0.001 ˂0.001
Cropping system ˂0.001 ˂0.001 ˂0.001
Year × Cropping System ˂0.001 ˂0.001 =0.002
Table 3. The most influencing factors on TKW, crude protein content, and HLW of oat cv. Dunav and hull-less barley cv. Golijat cultivated in pure stands and intercropping systems with pea cv. Partner in three years (2022, 2023, and 2024) at Rimski šnačevi (Serbia). Tukey’s pairwise comparisons with 95% confidence was used to provide information on differences between different cultivation practices, crop species, and years. Means with the same letters are not significantly different at α = 0.05.
Table 3. The most influencing factors on TKW, crude protein content, and HLW of oat cv. Dunav and hull-less barley cv. Golijat cultivated in pure stands and intercropping systems with pea cv. Partner in three years (2022, 2023, and 2024) at Rimski šnačevi (Serbia). Tukey’s pairwise comparisons with 95% confidence was used to provide information on differences between different cultivation practices, crop species, and years. Means with the same letters are not significantly different at α = 0.05.
VarietyCultivation
Practice		TKW gCrude Protein %HLW
kg/ha
202220232024Aver.202220232024Aver.202220232024Aver.
Dunav (oat)Pure Stand26.9 D29.8 CD27.3 D2814.1 CD14.2 CD13.5 D14.036.4 D43.6 C42.1 C40.7
Intercropping with Partner 27.5 D28.4 D26.8 D27.615.3 CD14.9 CD13.3 D14.536.8 D42.9 C41.3 CD40.3
Golijat (hull-less barley)Pure Stand29.2 D32.8 BC34.5 AB32.217.9 AB13.6 D14.1 CD15.257.6 B57.9 B66.1 A60.5
Intercropping with Partner 29.8 CD36.7 A35.6 AB34.018.2 A15.7 BC15.7 BC16.561.2 AB55.7 B66.8 A61.2
p p p
Year ˂0.001 ˂0.001 ˂0.001
GLMCrop Species ˂0.001 ˂0.001 ˂0.001
Cultivation Practice 0.054 ˂0.001 0.904
Year × Crop Species ˂0.001 ˂0.001 ˂0.001
Year × Cultivation Practice ˂0.001 ˂0.001 0.151
Year × Crop Species × Cultivation Practice 0.015 0.088 ns
Table 4. Yield components of oat cv. Dunav and hull-less barley cv. Golijat cultivated in pure stands and intercropping systems with pea cv. Partner in three years (2022, 2023, and 2024) at Rimski šnačevi (Serbia). Tukey’s pairwise comparisons with 95% confidence were used to provide information on differences between different cultivation practices, crop species, and years. Means with the same letters are not significantly different at α = 0.05. Yield components included spikelets/panicles per spike/panicle, head length, head weight, kernel weight per head, and number of kernels per spike/panicle.
Table 4. Yield components of oat cv. Dunav and hull-less barley cv. Golijat cultivated in pure stands and intercropping systems with pea cv. Partner in three years (2022, 2023, and 2024) at Rimski šnačevi (Serbia). Tukey’s pairwise comparisons with 95% confidence were used to provide information on differences between different cultivation practices, crop species, and years. Means with the same letters are not significantly different at α = 0.05. Yield components included spikelets/panicles per spike/panicle, head length, head weight, kernel weight per head, and number of kernels per spike/panicle.
VarietyCultivation
Practice		Number of Spikelets per Spike or Panicles per PanicleHead LengthHead WeightKernel Weight per HeadNumber of Kernels per Spike/Panicle
2023202420232024202320242023202420232024
Golijat (hull-less barley)Pure Stand17.2 D20.8 CD7.6 C8.0 C0.5 C0.9 BC0.3 C0.7 BC11.4 D19.9 CD
Intercropping with Partner 22.7 CD22.2 CD9.6 C9.5 C0.7 C0.9 BC0.5 C0.8 BC14.0 D21 CD
Dunav (oat)Pure Stand29.4 BC34.8 AB14.2 B16.1 AB1.0 BC2.0 A0.8 BC1.3 A28.1 BC53.9 A
Intercropping with Partner 39.1 AB40.1 A15.5 AB17.8 A1.3 B2.5 A1.0 AB1.5 A37.9 B61.1 A
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Jevtić, R.; Župunski, V.; Brbaklić, L.; Živančev, D.; Dolapčev Rakić, A.; Aćin, V.; Mikić, S.; Orbović, B. Potential for Enhancing Seed Yield and Quality of Spring Oat and Hull-Less Barley Through Intercropping with Pea Under the Pannonian Climate. Agronomy 2025, 15, 1349. https://doi.org/10.3390/agronomy15061349

AMA Style

Jevtić R, Župunski V, Brbaklić L, Živančev D, Dolapčev Rakić A, Aćin V, Mikić S, Orbović B. Potential for Enhancing Seed Yield and Quality of Spring Oat and Hull-Less Barley Through Intercropping with Pea Under the Pannonian Climate. Agronomy. 2025; 15(6):1349. https://doi.org/10.3390/agronomy15061349

Chicago/Turabian Style

Jevtić, Radivoje, Vesna Župunski, Ljiljana Brbaklić, Dragan Živančev, Anja Dolapčev Rakić, Vladimir Aćin, Sanja Mikić, and Branka Orbović. 2025. "Potential for Enhancing Seed Yield and Quality of Spring Oat and Hull-Less Barley Through Intercropping with Pea Under the Pannonian Climate" Agronomy 15, no. 6: 1349. https://doi.org/10.3390/agronomy15061349

APA Style

Jevtić, R., Župunski, V., Brbaklić, L., Živančev, D., Dolapčev Rakić, A., Aćin, V., Mikić, S., & Orbović, B. (2025). Potential for Enhancing Seed Yield and Quality of Spring Oat and Hull-Less Barley Through Intercropping with Pea Under the Pannonian Climate. Agronomy, 15(6), 1349. https://doi.org/10.3390/agronomy15061349

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