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Article

Intercropping Forage Mulberry Benefits Nodulation and Growth of Soybeans

by
Xinjie Feng
1,
Minghui Zhong
1,
Xuexian Zhao
1,
Xiuli Zhang
1,2,*,
Yanbo Hu
1,* and
Huihui Zhang
1,2
1
College of Life Science, Northeast Forestry University, Harbin 150040, China
2
Key Laboratory of Saline-Alkali Vegetation Ecology Restoration, Northeast Forestry University, Ministry of Education, Harbin 150040, China
*
Authors to whom correspondence should be addressed.
Agriculture 2025, 15(8), 902; https://doi.org/10.3390/agriculture15080902
Submission received: 28 February 2025 / Revised: 9 April 2025 / Accepted: 15 April 2025 / Published: 21 April 2025
(This article belongs to the Section Crop Production)
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Abstract

:
In northern China, intercropping soybeans with forage mulberry (Morus alba L.) enhances soybean yields through the optimization of natural resource use. However, the mechanisms underlying these improvements remain largely unknown. The aim was to explore the effects of this intercropping on soybean growth and yield. We used transcriptomics, redundancy analysis, and structural equation modeling to evaluate soybean growth, yield, and nodulation; results showed that intercropping did not adversely affect plant height or stem diameter but increased chlorophyll content, photosynthetic rate, leaf area, and yield of soybean. It also increased soil available phosphorus, soil available potassium and soil water content, while reducing soil available nitrogen and the pH value. It promoted P and organic acid metabolism, transporter activity, and key-gene expression. Redundancy analysis strikingly reveals that intercropping is positively correlated with yield, gene expression and soil properties. Meanwhile, structural equation modeling analysis demonstrates that the content of available phosphorus, available potassium, and water in rhizosphere soil are positively correlated with soybean nodulation. Additionally, nodulation traits can directly enhance nitrogen metabolism, which subsequently boosts photosynthesis and ultimately exerts an indirect positive influence on soybean yield. Furthermore, intercropping soybeans with forage mulberry did not induce shade stress on the above-ground portion of soybeans but promoted its growth and nodulation.

1. Introduction

Soybean (Glycine max L.) is a highly versatile crop used in food products, oils, proteins, and animal feed [1], with a low yield in China [2] due to a restricted acreage of suitable arable land [3] and inherent intolerance to continuous cropping [4]. Therefore, there is a need to optimize cultivation practices to enhance soybean production and reduce its import dependency. Intercropping is a widely used agricultural practice that enhances land productivity [5,6]. Intercropping gramineous plants with legumes can reduce nitrogen depletion in soil, improve nodulation for N fixation, and increase N transfer [7], thereby decreasing the need for chemical fertilizers [8]. Mechanistic studies on the promotion of N fixation in legumes by intercropping with gramineous plants mainly focus on the absorption of nitrogen in gramineous plants to create nitrogen-depleted conditions and prompt soybean roots to release nodulation signal substances like flavonoids [7,9,10]. Intercropping also aids rhizosphere soil acidification that benefits the activation of soil phosphorus [11] and strengthens the expression of genes related to nodulation and N fixation [12]. Intercropping soybeans with corn is especially widespread in China and enables farmers to obtain an additional soybean harvest while not impacting the yield of corn [5,13]. However, during the symbiotic stage, soybeans endure considerable shade stress imposed by corn, which reduces their photosynthetic capacity and biomass [14,15] and alters the red-to-far-red light ratio in their canopy [16,17,18], leading to their collapse [19] and a reduced yield [20,21,22].
To mitigate the shading impact on intercropped soybeans, forage mulberry (Morus alba L.) is usually intercropped with soybeans. When forage mulberry reaches a plant height of up to 1 m, it can be cut two to three times annually in Heilongjiang province, China. This growth stage optimizes both its nutritional quality and digestibility and simultaneously provides the intercropped soybeans with more time and space to absorb sunlight [23]. Unlike traditional sericulture mulberry varieties (Morus alba L.), which harvest low-fiber leaves (neutral detergent fiber < 12%) from lignified stems, forage mulberry cultivars grow non-lignified and herbaceous under high-density cultivation. They achieve an annual biomass of 18–22 t/ha (2.3 times greater than sericulture varieties), with a crude protein content of 18–22% in shoots and flavonoid concentrations of 1.5–2.0% in leaves [24]. Therefore, mulberry leaves are the potential resources for animal feed [25].
The ancient Chinese agricultural treatise Qi Min Yao Shu documents that intercropping with leguminous crops such as mung beans (Vigna radiata) and adzuki beans (Vigna angularis) significantly improves the growth performance of mulberry trees cultivated for sericultural purposes [26]. Similarly, previous field investigations have revealed that when mulberries (cultivated for silkworm rearing) are intercropped with soybeans, the mulberries shows significant physiological improvements. These improvements are manifested in multiple aspects, including an increase in above-ground biomass, enhanced photosynthetic efficiency, increased nitrogen uptake, greater root dry weight, and a higher root length density. In contrast, the soybean plants in an intercropping system exhibit noticeable decreases in growth parameters when compared to those in a sole cropping [27]. The inhibited growth of soybeans could be ascribed to the luxuriant branches and trunks of mulberry trees, which cast shade over the soybeans. Whether forage mulberry, which is routinely cut at a height of 1 m, causes shading stress when intercropped with soybeans and whether this affects soybean yield are the research topics currently under investigation in our laboratory.
The benefits of the mulberry–soybean intercropping system on forage mulberry growth have been firmly authenticated, but the effects of this system on the growth of soybeans still lack comprehensive and in-depth exploration and understanding. Therefore, this study aimed to investigate soybean growth under the forage mulberry–soybean intercropping system with two key objectives: to assess the impact of intercropped forage mulberry on soybean growth and photosynthesis and determine whether shade stress occurs; to explore the effect of the forage mulberry–soybean intercropping system on nitrogen fixation by soybean nodules. Our findings are expected to play a facilitating role in the formulation of a high-yield intercropping model specific to soybeans. Moreover, these results will enrich the theory of high-yield soybean cultivation, thereby offering a valuable reference point for the expansion of the soybean cultivation area.

2. Materials and Methods

2.1. Site Description

A field experiment was conducted in 2021, 2022, and 2023 at the experimental base of Northeast Forestry University in Li Ming Town, Harbin City, Heilongjiang Province (45°44′ N, 126°36′ E), situated at an altitude of 95.0 m. The region experiences an annual average temperature of 5.5 °C, a cumulative temperature above 10 °C totaling 2700 °C, a frost-free period of 115–130 days, and an annual average precipitation of 560 mm, predominantly falling between July and September, which accounts for over 59% of the total. The experimental site was characterized by meadow soil composed of 1.19 g∙kg−1 of available nitrogen, 2.23 g∙kg−1 of available potassium, 1.62 g∙kg−1 of available phosphorus, 31.1 g∙kg−1 soil organic matter content, and a pH of approximately 6.51.

2.2. Agriotechnical Methods in Experimental

The soybean (Glycine max L.) variety was ‘Dongnong 50’, and the forage mulberry (Morus alba L.) selected for the experiment was Moros alba ‘Qinglong’, provided by Heilongjiang Mulberry Silkworm Research Institute. The field experiment was conducted in a randomized block design on 600 m2 of irrigated, unobstructed arable land. Each intercropping plot and sole cropping plot had dimensions of 6 m × 12 m, and each treatment was replicated three times. In the intercropping system, the rows of plants were arranged in a 3:4 ratio, specifically 3 rows of forage mulberry followed by 4 rows of soybean (Figure 1). Both soybeans under the sole cropping system and those in the intercropping system with forage mulberries were planted with a uniform row-to-row spacing of 0.65 m. Soybeans are sown in rows in mid-May. Once the soybeans reach the seedling stage, forage mulberries are planted. Both the above-ground and under-ground portions of the forage mulberry seedlings are pruned, with each part being left at a length of 5 cm.
To explore the effects of intercropping with forage mulberry on soybean nodulation, the researchers deliberately excluded nitrogen fertilizer to establish a nitrogen-deficient condition. The treatments consisted of plots with sole crop soybeans without nitrogen fertilizer (SN) and intercrops of forage mulberries and soybeans without nitrogen fertilizer (IN). The soybean was planted in rows spaced 8 cm apart to reach a final population of 190,000 kg∙ha−1 fertilized with 65 kg∙ha−1 of P as triple superphosphate and 75 kg∙ha−1 of K as KCl, whereas the forage mulberry was planted in rows 5 cm apart for a population of 300,000 plants∙ha−1 fertilized with 90 kg∙ ha−1 of P as triple superphosphate and 100 kg∙ha−1 of K as KCl. The fertilization regime for soybeans in sole cropping was the same as that in intercropping. Irrigation was initiated when soil moisture levels fell below 60% of the field capacity. Water was pumped from a nearby river using an engine-driven pump and conveyed through a hose-type irrigation system to irrigate the crops. For both sole cropped and intercropped soybeans, an equal volume of irrigation water was applied per row.

2.3. Evaluation of Soybean Growth Performance and Yield

To ensure sample representativeness and minimize edge effects, we implemented a systematic random sampling approach. From 25 carefully selected plants, 5 were chosen for each indicator to form the final 5 replicates. The diameter of the stem base and the length and width of the third compound leaf were measured using vernier calipers (DL91150, Deli, Ningbo, China), while the leaf area was calculated using the following formula: leaf area = length × width × 0.75, where 0.75 means the leaf area coefficient of soybeans. Plant height was measured at the soybean growth stage of bloom (R1), as described previously [28] for treatments. Fresh and dry weights of whole plants and nodulations were recorded using an analytical balance (BSA223S, Sartorius, Gottingen, Germany). The plants and nodulations were dried in an oven at 105 °C for 1 h, then dried at 75 °C until a constant weight was reached to determine the dry weight and calculate the number of nodulations per plant. The chlorophyll content was determined using the ethanol extraction colourimetric method, and so 0.5 g of leaves were placed in a 50 mL centrifuge tube with 20 mL of 95% ethanol, sealed, and extracted in the dark at room temperature for 24 h until the tissue turned white. The chlorophyll content was then measured using a UV–visible spectrophotometer at wavelengths of 665 nm and 649 nm. To determine the yield, soybean grains were harvested separately from each treatment plot and then threshed. Subsequently, the weight of the grains from each plot was measured using an electronic balance.

2.4. Gas Exchange Measurement

The photosynthetic parameters were measured using a Li-6400 portable photosynthetic system (LI-COR, Lincoln, NE, USA) configured with an LED red/blue light source (6400-02B). Measurements were taken from 09:00 to 11:00 local time on the third fully expanded trifoliate leaves at the R1 stage, before the first forage mulberry mowing. A randomized complete block design was used for data acquisition. Each treatment had five biological replicates, with each replicate comprising three technical measurements taken at 120 s intervals. This setup ensured representative and reliable data, minimizing error and enabling a comprehensive understanding of the photosynthetic characteristics.

2.5. Measurement of Related Nitrogen Metabolism Activity

The nitrogenase activity of root nodules was indirectly determined by the acetylene reduction assay. Briefly, the roots from each plant with root nodules were collected and placed into sealed vials. Two milliliters of air were removed from each vial and replaced with an equal volume of acetylene. After incubating at 28 °C for 2 h, the ethylene content was measured using gas chromatography (GC-2010, Shimadzu, Kyoto, Japan). The nitrogenase activity of nodules was expressed as the amount of ethylene produced in micromoles per hour per gram of sample. Each measurement was repeated five times. The third compound leaf of the soybean was collected at the bloom stage (R1) in 2023. The concentrations of NH4+-N in the leaves were measured using phenol disulfonic acid colorimetry and potassium chloride extraction–indophenol blue colorimetry [29]. The activities of glutamine synthetase and glutamate synthase in soybean leaves were measured by using the method of Feng [30].

2.6. Transcriptome Analysis

Soybean root samples were collected at the R1 stage in triplicates and stored in a cryostat. The root samples were washed with 75% ethanol to remove dust and soil and then frozen in liquid nitrogen for 1 h and stored at −80 °C. The total RNA extracted from the root samples was used to construct the library and also for transcriptome sequencing at Hangzhou Kaitai Biotechnology, Hangzhou, China.

2.7. Estimation of Soil Physical and Chemical Properties

The soil samples from soybean roots were collected at the R1 stages. The pH value of the soil was measured using a pH meter (delta 320, Mettler Toledo, Zurich, Switzerland) with electrodes in a soil and water (1:2.5) suspension. The available nitrogen was determined using the alkali hydrolysis diffusion method [31], while the available phosphorus and potassium were determined as described by Lu [29]. The soil water content (SWC) was measured by weighing fresh soil samples. The samples were then dried in the oven at 105 °C to a constant mass. Oven-dry weight was then determined. Gravimetric SWC was calculated as (wet soil weight-dry soil weight)/dry soil weight [12].

2.8. Statistical Processing of Data

All independent experiments were repeated at least five times. Statistical analyses were performed using SPSS 24.0 (IBM, Armonk, NY, USA) with a two-way analysis of variance to analyze the interaction of planting pattern and year on soil physicochemical properties. Least significant difference tests were used to compare differences between cropping patterns in the same year, as well as differences among treatments between years within the same cropping pattern. Canoco 4.5 (Microcomputer Power, CA, USA) was used to reveal the correlation among planting patterns, growth indices, and soil properties though redundancy analysis. To establish a theoretical framework for intercropping that favors soybean cultivation and management, we employed structural equation modeling to uncover the pathways and interaction mechanisms of various factors affecting soybean growth and nodulation traits and analyzed their direct and indirect effects. The interaction relationship was further analyzed by the partial least squares path model (PLS-PM). The path and determination coefficients (R2) in the path model were calculated by the plspm package of R (version 4.4.1).

3. Results

3.1. Growth Indices

Based on three years of data (Table 1), there were no significant differences in the plant height and stem diameter of soybean between sole cropped and intercropped with forage mulberry. In 2021, 2022, and 2023, the leaf area of soybeans in the intercrop was 5.17%, 8.11%, and 5.79% higher than that in the sole crop, respectively. Similarly, the soybean fresh weight per plant of intercropped soybeans was 5.81%, 5.10%, and 4.63% higher, and the dry weight was 4.19%, 2.69%, and 3.81% higher than that in the sole cropping. The results of the two-way ANOVA test showed that pattern has significant effect on soybean fresh weight per plant. Meanwhile, year, pattern, and year × pattern have no significant effects on plant height, stem diameters, leaf area, and dry weight. Therefore, this clearly indicates that intercropping with forage mulberries impacts on growth and biomass of soybean plants.

3.2. The Yield Components of Soybean

From 2021 to 2023, the number of pods per plant in intercropped soybeans was 5.48%, 4.39%, and 5.84% higher than that in sole cropped soybeans, respectively (Table 2). The number of seeds per plant in intercropped soybeans was 12.63%, 11.39%, and 8.47% higher than in sole cropped soybeans. In the same vein, the grain yield per plant of intercropped soybeans was 7.41%, 6.31%, and 7.84% higher. The 100-seed weight of intercropped soybeans was 11.85%, and 9.39% higher, and the overall grain yield was 8.39%, 7.69%, and 10.88% higher than that in sole cropped soybeans. The results of the two-way ANOVA test showed that the cropping pattern had a significant effect on the grain yield per plant and 100-seed weight of soybean grains. Meanwhile, year and year × pattern have no significant effects on these characteristics.

3.3. Root Nodule Traits

From 2021 to 2023, compared with sole cropped soybeans, the number of root nodules, along with the fresh and dry weights of root nodules intercropped with forage mulberry treatment, were significantly increased (Table 3). In particular, in 2021, 2022, and 2023, the number of root nodules per plant of intercropped soybeans were 21.43%, 24.21%, and 25.79% more than that in sole cropped soybeans, respectively. Similarly, the fresh weight of nodules per plant of intercropped soybeans was 51.58%, 54.89%, and 56.78% (p < 0.05) higher, and the dry weight was 40.21%, 44.00%, and 51.30% higher than that in sole cropped soybeans. The results of the two-way ANOVA test showed that the cropping pattern had a significant effect on the number of nodules, the fresh weight of nodules, and the dry weight of nodules. Conversely, both the year and the interaction of the year and the cropping pattern had no significant impacts on these features.

3.4. Physical and Chemical Properties in Rhizosphere Soil

From 2021 to 2023, when compared with sole cropped soybeans, the content of available nitrogen (AN) and the pH value in the treatment of soybeans intercropped with forage mulberry decreased significantly (Table 4). In contrast, the content of available phosphorus (AP), the content of available potassium (AK), and the soil water content (SWC) were higher in the intercropping system than in the sole cropping system. For example, in 2021, 2022, and 2023, the AN in the soil of intercropped soybeans was 9.95%, 8.95%, and 9.31% lower, respectively, and the pH value was 1.62%, 3.04%, and 2.44% lower than that in sole cropped soybeans. On the other hand, the AP in the soil of intercropped soybeans was 16.72%, 16.48%, and 16.30% higher, and the AK was 19.77%, 19.53%, and 20.57%, and the SWC was 13.51%, 11.28%, and 12.06% higher than that in sole cropped conditions. The results of the two-factor variance analysis indicated that the planting pattern had a significant influence on the pH value, AN, AP, AK, and SWC in rhizosphere soil of the soybean. However, year and the interaction between the year and the planting pattern had no significant impact on the above-mentioned properties of the rhizosphere soil.

3.5. Photosythetic Parameters

Intercropping soybeans with forage mulberries significantly affected the main gas exchange parameters of soybean leaves, as presented in Figure 2. When compared to sole crop, the net photosynthetic rate of soybeans in the intercropping system with forage mulberries increased by 24.86%, and the intercellular CO2 concentration increased by 5.48%. However, no significant differences were observed between the intercropping and sole cropping systems in terms of chlorophyll content, stomatal conductance, and transpiration rate.

3.6. Nitrogen Metabolism Changes

Below is example 1 of the NH4+-N generated by nitrogen fixation in root nodules which is assimilated through the GS/GOGAT cycle within the leaves of soybeans (Figure 3A). Intercropping soybeans with forage mulberries enhanced the nitrogenase activity of soybean roots (Figure 3B), along with the content of NH4+-N and the activities of glutamine synthetase (GS) in soybean leaves at the R1 stage (Figure 3C,D).
Compared to sole cropping, intercropping with forage mulberry led to a significant increase in nitrogenase activity in nodules by 135.28%, NH4+-N content in soybean leaves by 31.13%, and GS activity in soybean leaves by 19.30%. Conversely, the glutamate synthase activity (GOGAT) in soybean leaves within the intercropping system with forage mulberry was 24.64% lower than that in the sole cropping system (Figure 3E).

3.7. Transcriptome Analysis

The transcriptome analysis identified 1462 differentially expressed genes (DEGs) in the soybean roots of intercropping with forage mulberries compared to sole cropping. Among these, 569 DGEs were up-regulated, and 893 DGEs were down-regulated, suggesting that intercropping with forage mulberry modified the expression of genes in soybean roots (Figure 4A).
The DEGs were categorized into biological processes, cellular components, and molecular functions based on the gene ontology (GO) terms (Figure 4B). The DEGs enriched in the biological processes mainly included the phosphorus metabolic process, organic acid metabolic process, oxoacid metabolic process, response to organonitrogen compound, and response to nitrogen compound. The enriched molecular functions mainly included oxidoreductase activity, organic acid transmembrane transporter activity, and carboxylic acid transmembrane transporter activity (Figure 4B). The KEGG enrichment analysis showed that DEGs in sole crops and were highly enriched in plant–pathogen interaction and isoflavone biosynthesis pathways (Figure 4C).

3.8. Isoflavone Biosynthesis

Flavonoids serve as crucial signaling molecules in the symbiosis between soybean and rhizobium and are synthesized through the isoflavone biosynthesis pathway, which comprises the phenylpropane pathway from phenylalanine to coumarin-CoA, the flavonoid biosynthesis from p-coumarin-CoA to naringenin, and the isoflavone biosynthesis from naringenin to isoflavones (Figure 5). Compared with sole cropping, intercropping with forage mulberry increased the expression of DEGs related to coenzyme A ligase (4-coumarate: coenzyme A ligase, 4CL), chalcone synthase (CHS), chalcone isomerase (CHI), flavone synthase (FNS), and 2-hydroxyisoflavanone dehydratase (HIDH). This indicates that intercropping with forage mulberry activated the “isoflavone biosynthesis” pathway and enhanced the metabolism and secretion of flavonoids in the soybean roots compared to sole cropping, thereby facilitating the biosynthesis of rhizobial nodulation factor to promote N fixation through root nodulation.

3.9. Redundancy Analysis

Redundancy analysis of the planting pattern, growth related parameters, genes, and soil properties indicated that intercropping with forage mulberry had the highest positive value along axis 1, while sole cropping had the highest negative value along axis 1 (Figure 6). The genes encoding the enzymes in the isoflavone pathway, including 4-coumarate: coenzyme A ligase (4CL), chalcone synthase (CHS), chalcone isomerase (CHI), flavone synthase (FNS), and 2-hydroxyisoflavanone dehy-dratase (HIDH), glutamine synthetase (GS) and glutamate synthase (GOGAT), nitrogenase activity (Fnase), and the main soil properties, namely available phosphorus (AP), available potassium (AK), and soil water content (SWC), were positively correlated with intercrop (IN) and negatively correlated with sole crop (SN). The growth related parameters, including grain yield per plant (Grain/pl), 100-seed weight (100 SW), pod number per plant (Pod num), seed number per plant (Seed num), plant height (Height), stem diameter (Stem), fresh weight per plant (FW/plant), dry weight per plant (DW/plant), leaf area (LA), chlorophyll content (Chl), net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO2 concentration (Ci), transpiration rate (Tr), the soil properties of available nitrogen (AN), and pH value (pH), were positively correlated with sole cropping and negatively correlated with intercropping.

3.10. Structural Equation Modeling

Structural equation modeling was used to analyze both the direct associations and indirect and causal linkages among variables for a better understanding (Figure 7). Intercropping with forage mulberry had highly significant negative effects on pH and AN with a path coefficient of −0.940 (p < 0.001) and significant positive effects on the AP, AK, and SWC with path coefficients of 0.940 (p < 0.001). The contents of AP and AK had the most significant positive effects on the soybean isoflavone synthesis pathway, with path coefficients of 0.977 (p < 0.001). Moreover, isoflavone synthesis pathways were positively correlated with nodulation traits (β = 0.997, p < 0.001), while nodulation-mediated effects positively regulated nitrogen metabolism in soybean leaves (β = 0.991, p < 0.001), and the nitrogen metabolism positive correlated with the gas exchange parameters in soybean leaves (β = 0.986, p < 0.001). The results also showed a positive and insignificant correlation of the gas exchange parameters with yield (β = 0.595, p > 0.05), and a positive correlation of intercropping with yield (β = 0.960, p > 0.05).
Goodness of fit is more than 0.600, indicating that the model has a good fit. The isoflavone pathway includes genes of 4CL5, 4CL7, CHI3, FNS, and HIDH3, while the nodulation traits include the number, fresh weight and dry weight of nodules, and nitrogenase activity. The photosynthetic parameters used include the net photosynthetic rate, stomatal conductance, and transpiration rate. Other parameters used are soil pH, soil available nitrogen, soil available phosphorus, soil available potassium, and soil water content. The nitrogen metabolism includes the nitrogenase activity, NH4+-N content, glutamine synthetase activity, and glutamate synthase activity.

4. Discussion

4.1. Effects of Intercropping of Forage Mulberry on Soybean Growth

Legumes are preferred for intercropping primarily due to their ability to symbiotically fix N, which they utilize and can also be used by adjacent crops [32,33]. Meanwhile, intercropping with gramineous plants can reduce nitrogen (N) depletion in legumes, improve nodulation for N fixation, and increase N transfer, thereby decreasing the need for chemical fertilizers [8]. Intercropping with legumes greatly conforms to the strategy of reducing N input in agriculture [34]. However, the symbiotic N fixation is an energy-expensive process that depends greatly on shoot photosynthetic processes [35]. The light available to plants is a primary influencing factor in photosynthesis since it provides energy. Moreover, light also serves as an essential signal for biological nitrogen fixation [36]. On the other hand, shading brought by intercropping directly leads to a decline in soybean’s photosynthetic parameters [14], thinning of the stems, elongation of the internodes, increase in plant height, lodging, and reduced yields [17,20]. In this study, intercropping with forage mulberries did not hinder the plant height and stem diameter of soybeans. In contrast, it enhanced the chlorophyll content and net photosynthetic rate, thereby increasing the soybean yield. This indicated that the regularly mowed forage mulberries did not exert shading effects on soybeans during the intercropping symbiosis period. To some extent, intercropping with forage mulberry also had beneficial effects on soybean growth and yield.

4.2. Effects of Intercropping on Nodulation Related Indicators

Intercropping with gramineous plants creates a nitrogen-depleted environment. This reduces the “nitrogen repression” on the root systems of leguminous plants by competing for soil nitrogen and also promotes nodulation [37]. Our previous studies found that the contents of available nitrogen content (AN) in the rhizospheric soil of the legumes intercropped with forage mulberries declined, while the number of nodules increased [12,38,39]. Similarly, in this current study, the AN content in the rhizospheric soil of soybeans intercropped with forage mulberries also declined over the three-year period. Therefore, it is likely that the forage mulberry enriched protein was mowed two-to-three times, just like gramineous plants, to take away a large amount of N elements from the soil, thereby creating an N-deficient environment. When the roots of leguminous plants sense the deficiency in soil N, they secrete flavonoid substances as signals into the soil, which plays the role of a key signaling molecule in symbiosis [40,41].
Intercropping can promote the expression level of CHI genes in pea roots, thereby enhancing the secretion of flavonoids in leguminous crops, which is beneficial in the nodulation of legumes [42]. In this study, intercropping with forage mulberry stimulated the expression of genes encoding the key enzymes, including 4CL, CHS, CHI, FNS, and HIDH, which are involved in the isoflavone biosynthesis in soybean roots. Correspondingly, the nodule traits of soybeans intercropped with forage mulberries are significantly superior to those of soybeans under monoculture. However, the N-fixation in leguminous plants is limited by the contents of the soil P and K [20] and the legumes are stimulated to adopt potential P uptake strategies via root-secreting organic acid to meet their high P demand for N fixation [42]. In the present study, intercropping with forage mulberry decreased the rhizospheric soil pH of intercropped soybeans but increased the content of soil AP and AK. Additionally, the gene ontology analysis also showed the significant enrichment of organic acid and ion transmembrane transporter proteins in the intercropped soybeans. Therefore, these findings suggest that intercropping with forage mulberry could potentially stimulate soybean roots to secrete organic acids, consequently enhancing soil phosphorus activity. Meanwhile, ample soil moisture acts as an indispensable medium for the activated phosphorus to penetrate root. Moreover, soil water content (SWC) significantly impacts the nodulation traits of leguminous plants [43]. Specifically, inadequate SWC can impede nodule formation and reduce nodule activity. Shen et al. [44] reported that intercropping with maize plants can enhance the SWC in soybean rhizosphere soils. Similarly, intercropping with forage mulberry has been shown to increase the SWC in the rhizosphere soil of soybean roots. The adequate SWC may facilitate the utilization of nitrogen fixed by root nodules, transport it to the leaves, and promote nitrogen metabolism in the leaves.

4.3. Effects of Intercropping on NH4+-N Assimilation in Soybean Leaf

Previous research has demonstrated that the most vigorous stage of nitrogen fixation, transport, and assimilation in soybean leaves occurs at the flowering stage [45]. Therefore, aiming to build upon previous findings, in this experiment, all indicators associated with nitrogen metabolism were assayed during the flowering stage. We observed that the nitrogenase activity in soybean root nodules and the NH4+-N content in leaves in the intercropping system with forage mulberries were higher than those in the sole cropping system. To investigate the effects of intercropping with forage mulberry on soybean nodulation, nitrogen fertilizer was deliberately omitted to create a nitrogen-limited environment. It is highly likely that the main source of ammonium ions (NH4+) in soybean leaves is the nitrogen fixed via soybean nodulation. Meanwhile, the conversion of NH4+ into glutamine and glutamate depends on the interaction between glutamine synthetase (GS) and glutamate synthase (GOGAT) [46]. In this experiment, the activity of GS in soybean leaves was found to be higher in the intercropping system with forage mulberries than in the sole cropping system. Conversely, the activity of GOGAT exhibited an opposite trend. There was no correlation found among the NH4+ content, GS activity, and GOGAT activity in soybean leaves. A possible reason for this is that the function of GS–GOGAT may not be restricted to nitrogen assimilation. The products of GS–GOGAT, glutamine and glutamate, not only participate in amino acid metabolism but also potentially act as signal molecules in various pathways [47]. There are still many gaps in a better understanding of the interactions of GS–GOGAT and the concentration of NH4+ in soybean intercropped with forage mulberry.

4.4. Relationships Between Plant Pattern and Parameters of Soybean

In recent years, there has been an exponential increase in studies examining the effects of agronomic practices on soil microbial communities [48]. However, it remains a challenge to elucidate the relationships between plant phenotypic traits, soil physicochemical properties, plant yield, and plant gene expression, as well as their impact pathways under intercropping conditions [49]. Combining RDA and SEM can help explore the correlations between variables and then delve deeply into their specific cause–effect relationships and the underlying mechanisms [50]. In this study, RDA indicated that on the same coordinate axis, the genes involved in soybean root isoflavone biosynthesis, nodule traits, along with soil AP, AK, and SWC, were positively associated with intercropping patterns but negatively correlated with sole cropping. Meanwhile, the main soybean growth indices, along with soil pH and AN, were positively related to sole cropping and negatively related to intercropping. Previous studies have demonstrated that intercropping soybeans with maize exerts a detrimental influence on the photosynthetic traits, soil nitrogen content, and yield of soybeans [49]. On the contrary, our SEM results indicate that the soil P and K content, as the main contributors to soybean yield, had the most significant positive effects on isoflavone synthesis and nodulation traits, while the nodulation traits positively related to nitrogen metabolism and photosynthesis in leaves, which in turn affected the soybean yield. Based on the above discussion, we have elucidated the fundamental mechanisms by which forage mulberries promote the growth of soybeans and established a theoretical framework for enhancing soybean nodulation in the intercropping system (Figure 8).

5. Conclusions

The presented data elucidate the fundamental mechanisms of forage mulberries facilitating the growth of soybeans, and the data formulate a theoretical framework for enhancing nodulation in an intercropping system. In this experiment, being intercropped with forage mulberries did not induce shade stress on soybeans. Additionally, intercropping significantly reduced the content of AN and the value of pH in the rhizosphere soil, while enhanced the levels of AP, AK, and SWC. Moreover, the intercropping activated the expression of genes encoding key enzymes involved in the “isoflavone biosynthesis” pathway, including 4CL, CHS, CHI, FNS, and HIDH. Furthermore, the intercropping of forage mulberry significantly increased the number of nodules, and nitrogenase activity in soybean roots, which collectively contributed to higher soybean yields.

Author Contributions

Conceptualization, X.Z. (Xiuli Zhang), Y.H. and H.Z.; methodology, X.F. and M.Z.; data curation, X.F. and X.Z. (Xuexian Zhao); writing—original draft preparation, X.F.; writing—review and editing, X.Z. (Xiuli Zhang); visualization, Y.H.; supervision, H.Z.; project administration, X.Z. (Xiuli Zhang); funding acquisition, X.Z. (Xiuli Zhang). All authors have read and agreed to the published version of the manuscript.

Funding

This research was founded by the Natural Science Foundation of Heilongjiang Province, China (Grant No. LH2021C009) and the National Natural Science Foundation of China (Grant No. 31600508).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Figure 1. Intercropping of forage mulberry and soybean. (A) Diagram of the row configuration of forage mulberry and soybean. (B) Forage mulberry starting to grow leaves during the soybean seedling stage in the field. (C) Soybean seedlings when the forage mulberry begins leaf-sprouting in the field. (D) Before the forage mulberry is mowed, soybeans and forage mulberries are nearly of equal height. (E) Before the forage mulberries are mowed, soybeans are at the R1 stage. Notes: SN indicates sole cropping of soybeans; IN indicates intercropped with forage mulberry.
Figure 1. Intercropping of forage mulberry and soybean. (A) Diagram of the row configuration of forage mulberry and soybean. (B) Forage mulberry starting to grow leaves during the soybean seedling stage in the field. (C) Soybean seedlings when the forage mulberry begins leaf-sprouting in the field. (D) Before the forage mulberry is mowed, soybeans and forage mulberries are nearly of equal height. (E) Before the forage mulberries are mowed, soybeans are at the R1 stage. Notes: SN indicates sole cropping of soybeans; IN indicates intercropped with forage mulberry.
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Figure 2. Effects of intercropping with forage mulberry on soybean photosynthetic parameters at the blooming stage. (A) Chlorophyll content, (B) net photosynthetic rate (Pn), (C) intercellular CO2 concentration (Ci), (D) transpiration rate (Tr), and (E) stomatal conductance (Gs). Notes: SN indicates sole crop; IN indicates intercrop; ns indicates p > 0.05, * indicates p < 0.05, and ** indicates p < 0.01.
Figure 2. Effects of intercropping with forage mulberry on soybean photosynthetic parameters at the blooming stage. (A) Chlorophyll content, (B) net photosynthetic rate (Pn), (C) intercellular CO2 concentration (Ci), (D) transpiration rate (Tr), and (E) stomatal conductance (Gs). Notes: SN indicates sole crop; IN indicates intercrop; ns indicates p > 0.05, * indicates p < 0.05, and ** indicates p < 0.01.
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Figure 3. Effects of intercropping forage mulberry on soybean leaf nitrogen metabolism at the blooming stage. (A) Ammonia assimilation in leaves, (B) nitrogenase activity, (C) NH4+-N content, (D) glutamine synthetase activity (GS), (E) glutamate synthase activity (GOGAT). Notes: SN indicates sole crop; IN indicates intercrop; ** indicates p < 0.01 and *** indicates p < 0.01.
Figure 3. Effects of intercropping forage mulberry on soybean leaf nitrogen metabolism at the blooming stage. (A) Ammonia assimilation in leaves, (B) nitrogenase activity, (C) NH4+-N content, (D) glutamine synthetase activity (GS), (E) glutamate synthase activity (GOGAT). Notes: SN indicates sole crop; IN indicates intercrop; ** indicates p < 0.01 and *** indicates p < 0.01.
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Figure 4. Transcriptome analysis of soybean roots under intercropping. (A) Volcano plot of differentially expressed genes (DEGs), (B) gene ontology enrichment analysis of DEGs in different treatment groups. (C) KEGG enrichment analysis of DEGs in different treatment groups. SN indicates sole crop; IN indicates intercrop.
Figure 4. Transcriptome analysis of soybean roots under intercropping. (A) Volcano plot of differentially expressed genes (DEGs), (B) gene ontology enrichment analysis of DEGs in different treatment groups. (C) KEGG enrichment analysis of DEGs in different treatment groups. SN indicates sole crop; IN indicates intercrop.
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Figure 5. Transcriptome changes in soybean isoflavone biosynthesis. Note: heat map showing transcriptional changes in soybean roots. Different colors indicate the intensity of normalization according to the corresponding genes. SN indicates sole crop; IN indicates inter crop.
Figure 5. Transcriptome changes in soybean isoflavone biosynthesis. Note: heat map showing transcriptional changes in soybean roots. Different colors indicate the intensity of normalization according to the corresponding genes. SN indicates sole crop; IN indicates inter crop.
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Figure 6. Ordination plots of redundancy discriminatory analysis showing the relationship between plant patterns and the environmental variables. Note: (○) sole crop of soybeans; (□) soybeans intercropped with forage mulberries.
Figure 6. Ordination plots of redundancy discriminatory analysis showing the relationship between plant patterns and the environmental variables. Note: (○) sole crop of soybeans; (□) soybeans intercropped with forage mulberries.
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Figure 7. Structural equation modeling showing the relationship among plant growth parameters, soybean yield, and soil physicochemical characteristics. Note: The green arrows indicate positive effects, while the yellow arrows indicate negative effects; *** indicates p < 0.001.
Figure 7. Structural equation modeling showing the relationship among plant growth parameters, soybean yield, and soil physicochemical characteristics. Note: The green arrows indicate positive effects, while the yellow arrows indicate negative effects; *** indicates p < 0.001.
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Figure 8. Underlying mechanisms of intercropping with forage mulberry-induced impacts on soybean growth and nodulation.
Figure 8. Underlying mechanisms of intercropping with forage mulberry-induced impacts on soybean growth and nodulation.
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Table 1. Effects of intercropping forage mulberry on the growth indices of soybean.
Table 1. Effects of intercropping forage mulberry on the growth indices of soybean.
TreatmentPlant Height
(cm)		Stem Diameter
(mm)		Leaf Area
(cm2)		Fw of Plant
(g∙plant−1)		DW of Plant
(g∙plant−1)
Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop
202160.50 61.19 4.67 4.67 19.09 b20.08 a29.43 c31.14 a12.88 b13.42 a
202260.56 60.99 4.68 4.6719.13 b20.68 a29.75 b31.26 a12.88 b13.22 a
202360.12 61.17 4.69 4.66 19.11 b20.22 a29.78 b31.16 a12.80 b13.29 a
Source of variationF value from two-way ANOVA test
Pattern1.445 ns3.808 ns 50.075 ns 255.289 *62.405 ns
Year0.924 ns1.533 ns1.268 ns2.27 ns1.362 ns
Pattern × Year0.326 ns0.186 ns0.776 ns0.639 ns1.03 ns
The ns indicates no significant difference while * indicates significant difference at p < 0.05. Different letters indicate significant differences according to the LSD test (p < 0.05).
Table 2. Effects of intercropping forage mulberry on the yield components of soybean.
Table 2. Effects of intercropping forage mulberry on the yield components of soybean.
TreatmentNumber of Pods Plant−1Number of Seeds Plant−1 Grain Yield
(g∙plant−1)		100-Seeds
(g)		Yield
(kg∙ha−1)
Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop
202158.41 bc61.60 a150.4 c169.4 a10.58 b11.37 a29.43 c31.14 a2160 b2342 a
202259.20 b61.80 a154.8 b172.4 a10.58 b11.25 a29.75 b31.26 a2180 b2347 a
202358.20 b61.60 a155.8 bc169.6 a10.71 b11.55 a29.78 b31.16 a2131 b2363 a
Source of variationF value from two-way ANOVA test
Pattern162.769 ns90.249 ns 227.532 * 216.552 *97.859 ns
Year2.385 ns1.556 ns6.558 ns4.69 ns0.254 ns
Pattern × Year0.65 ns1.801 ns0.243 ns1.82 ns0.502 ns
The ns indicates no significant difference while * indicates significant difference at p < 0.05. Different letters indicate significant differences according to the LSD test (p < 0.05).
Table 3. Effects of intercropping forage mulberry on the nodule properties of soybean.
Table 3. Effects of intercropping forage mulberry on the nodule properties of soybean.
TreatmentNumber of Nodules
Plant−1		FW of Nodules
(g∙plant−1)		DW of Nodules
(g∙plant−1)
Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop
202139.20 b47.60 a0.46 b0.69 a0.12 b0.17 a
202238.00 c47.20 a0.45 b0.71 a0.12 b0.17 a
202338.00 c47.80 a0.46 b0.71 a0.11 b0.17 a
Source of variationF value from two-way ANOVA test
Pattern507.27 *1365.81 *294.646 *
Year1.324 ns0.877 ns0.212 ns
Pattern × Year1.51 ns5.91 ns2.717 ns
The ns indicates no significant difference while * indicates significant difference at p < 0.05. Different letters indicate significant differences according to the LSD test (p < 0.05).
Table 4. Effects of intercropping forage mulberry on the physicochemical properties of soybean rhizospheric soils.
Table 4. Effects of intercropping forage mulberry on the physicochemical properties of soybean rhizospheric soils.
TreatmentAvailabe Nitrogen
(mg∙kg−1)		Available Phosphorus
(mg∙kg−1)		Available Potassium
(mg∙kg−1)		SWC
(%)		pH
Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop Sole Crop Intercrop
2021138.1 a124.3 c257.6 b300.7 a286.7 b343.4 a18.26 b20.73 a6.45 a6.34 b
2022137.9 a127.6 bc256.9 b299.2 a287.3 b343.4 a18.41 b20.48 a6.48 a6.28 b
2023138.2 a125.8 ab258.7 b300.8 a286.2 b345.0 a18.13 b21.46 a6.46 a6.30 b
Source of variation F value from two-way ANOVA test
Pattern1025.242 *22,934.79 *46,878.507 *369.304 *32.58 *
Year2.801 ns12.692 ns0.119 ns2.077 ns0.197 ns
Pattern × Year1.247 ns0.048 ns1.637 ns0.151 ns1.511 ns
The ns indicates no significant difference while * indicates significant difference at p < 0.05. Different letters indicate significant differences according to the LSD test (p < 0.05).
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Feng, X.; Zhong, M.; Zhao, X.; Zhang, X.; Hu, Y.; Zhang, H. Intercropping Forage Mulberry Benefits Nodulation and Growth of Soybeans. Agriculture 2025, 15, 902. https://doi.org/10.3390/agriculture15080902

AMA Style

Feng X, Zhong M, Zhao X, Zhang X, Hu Y, Zhang H. Intercropping Forage Mulberry Benefits Nodulation and Growth of Soybeans. Agriculture. 2025; 15(8):902. https://doi.org/10.3390/agriculture15080902

Chicago/Turabian Style

Feng, Xinjie, Minghui Zhong, Xuexian Zhao, Xiuli Zhang, Yanbo Hu, and Huihui Zhang. 2025. "Intercropping Forage Mulberry Benefits Nodulation and Growth of Soybeans" Agriculture 15, no. 8: 902. https://doi.org/10.3390/agriculture15080902

APA Style

Feng, X., Zhong, M., Zhao, X., Zhang, X., Hu, Y., & Zhang, H. (2025). Intercropping Forage Mulberry Benefits Nodulation and Growth of Soybeans. Agriculture, 15(8), 902. https://doi.org/10.3390/agriculture15080902

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