Next Article in Journal
Adaptability of Toxoptera aurantii (Hemiptera: Aphididae) to Different Tea Cultivars
Next Article in Special Issue
Effects of Defoliation at Different Fertility Stages on Material Accumulation, Physiological Indices and Yield of Cotton
Previous Article in Journal
The Application of Artificial Intelligence Models for Food Security: A Review
Previous Article in Special Issue
Genetic Improvement of Sugarcane (Saccharum spp.) Contributed to High Sucrose Content in China Based on an Analysis of Newly Developed Varieties
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Italian Ryegrass (Lolium multiflorum) Cultivation for Green Manure and Forage on Subsequent Above- and Below-Ground Growth and Yield of Soybean (Glycine max)

1
Division of Applied Life Science (BK21), Gyeongsang National University, Jinju 52828, Republic of Korea
2
Future Agriculture Center, Kyung Nong Corporation, Gimje 54338, Republic of Korea
3
Crop Physiology and Production, National Institute of Crop Science, Rural Development Administration, Wanju 55365, Republic of Korea
4
Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea
5
Institute of Agriculture and Life Science, Gyeongsang National University, Jinju 52828, Republic of Korea
*
Author to whom correspondence should be addressed.
Agriculture 2023, 13(10), 2038; https://doi.org/10.3390/agriculture13102038
Submission received: 25 September 2023 / Revised: 19 October 2023 / Accepted: 21 October 2023 / Published: 23 October 2023
(This article belongs to the Special Issue Advances in Stability and Adaptability on Crop Production)

Abstract

:
To diversify upland cropping systems, Italian ryegrass (Lolium multiflorum; IRG) can be incorporated as forage or green manure to soybean (Glycine max L.). The current study was conducted to analyze the effect of IRG cultivar and usage methods on the subsequent soybean above- and below-ground growth, as well as the yield, under different conditions. Three cycles of crop rotation were implemented with the combination of IRG cultivar (early maturing “Kowinearly”; late maturing “Winterhawk”), IRG usage (green manure for which both above- and below-ground biomass was incorporated, +CC; and forage for which only below-ground biomass was incorporated, −CC), and fallow soil as control. The soybean yield of +CC was consistently high regardless of the IRG cultivar, and it demonstrated an increase even under unfavorable weather conditions, while −CC treated did not differ from control. Incorporated IRG could serve as a starter fertilizer (79 to 156 kg ha−1 of N input). Soybean root characteristic differences showed substantial variability depending on the year and treatments. However, when compared to the control, no adverse effects of IRG were evident. Thus, using IRG as a green manure has the potential to enhance soybean yield, while using IRG as a forage could bring additional harvested matter to the rotational system.

1. Introduction

Soybean (Glycine max L.) is the most important leguminous grain crop in the world. In an association with rhizobium bacteria, soybean fixes N2 through biological nitrogen fixation (BNF). It is an important part of the human diet and contributes to livestock feed because of its high protein concentration [1]. In addition, after grain harvest, crop residues supply nitrogen to subsequent crops and improve soil properties [2].
Due to climate change and global warming, many areas where intensive soybean production occurs have experienced challenges associated with changing weather patterns and frequent occurrences of extreme weather events [3,4]. For example, soybean yield reduction has followed the occurrence of flooding during germination and early seedling growth [5]. Waterlogging-restricted seed germination and initial root development damage the water and nutrient uptake capability of the crop [5]. The scarcity of water negatively impacts the symbiotic association at its early stages by damaging the signal exchange between host plants and rhizobia. Thus, BNF by soybean was highly susceptible to drought [6].
Crop rotation refers to the practice of cultivating various crops in sequence on the same field. Utilizing cover crops in a rotation may have several benefits that could ameliorate challenges associated with climate change, including increased soil fertility, reduced soil erosion, and enhanced soil moisture retention and weed suppression [7,8,9,10].
Italian ryegrass (Lolium multiflorum, IRG) is a winter-annual forage and cover crop that can be rotated with summer crops. IRG is rotated with cotton and peanut in the southern United States, and it is currently widely grown as a winter forage crop in rice paddies during the winter season in Korea [11]. If IRG is used for forage, growers can have an additional source of income. As a forage crop, above-ground biomass of IRG can be utilized for animal feed, while its roots and stubble residue can protect the soil. Previous studies have reported that IRG had a greater root biomass, root length, and root surface area than other cover crops, and that it continues to produce roots until late growth stages [10,12]. As a result, it can provide more below-ground biomass than other cover crops, and longer root persistence is associated with the provision of a greater amount of nutrients to the subsequent primary crop [13]. As a cover crop, IRG increased soil organic carbon more than leguminous crops [14]. Additionally, nine years of IRG use resulted in greater soil organic N accumulation than other green manure crops such as hairy vetch [15]. When 40 Mg ha−1 of IRG were incorporated as a green manure, it improved soil total N and available K, and increased seedling biomass of rice in an IRG–rice rotation [16]. Although there are significant potential benefits of using IRG as a green manure, research is limited, especially regarding its effects on subsequent crops in the rotation. As a result, it is necessary to experiment with various crop rotations involving IRG, particularly to determine their impact on subsequent crops such as soybean. For instance, physiological and morphological responses of above- and below-ground parts of following soybean crop have not been tested in a multi-year field scale by different regimes of IRG usage.
Thus, the objectives of the current study were to determine: (1) The effects of incorporating IRG to existing soybean production as a novel rotational cropping system for the region; (2) The comparison of different usage regime and ecotypes of IRG on subsequent soybean shoot and root development; and (3) The evaluation of IRG biomass and nitrogen contents as a potential N supply to following soybean production.

2. Materials and Methods

2.1. Research Site and Field Conditions

The field experiment was conducted at Gyeongsang National University (GNU) Research Farm in Jinju, Korea (35°14′ N 128°09′ E). Soils are sandy loams. They are, from the 0-to-30-cm depth, 68% sand-, 30% silt-, and 2% clay-sized particles. Soil samples were collected at a 30-cm depth using a soil auger (diameter 2.54 cm) before and after IRG planting. Twenty soil samples were collected in a “W” pattern and then composited. Soil chemical properties are shown in Table 1. The weather data during three growing seasons were obtained from the Automatic Weather Station, Korea Meteorological Administration (available at https://data.kma.go.kr/, accessed on 24 September 2023, in Korean). Table 2 shows the monthly mean temperature, growing degree days (GDD), and precipitation for the study period.

2.2. Experimental Design Layout and Field Management

The plowed and rotovated field received 45, 36, and 36 ha−1 of N, P2O5, and K2O, respectively, using mixed fertilizer (21–17–17) each season for three years of the study. Seeds of two IRG ecotypes (Kowinearly and Winterhawk) were broadcasted (40 kg ha−1). Additional N fertilizer was broadcasted with a handheld fertilizer sprayer (GE –US 18 Li, Einhell, Landau an derIsar, Germany) at N level of 60 kg ha−1 using urea (60–0–0) in February. The fallowed control (F) did not receive any fertilizer during the winter season.
The experimental design was a randomized complete block with four replications of five treatments. Four of the treatments were combinations of two IRG ecotypes and two usage options for IRG prior to planting soybean. The two IRG cultivars (early maturing ecotype “Kowinearly”, Ko; late maturing ecotype “Winterhawk”, Win) were selected to assess their adaptability to different usage regimes and whether IRG ecotype affected subsequent soybean performance. Two different IRG usage regimes included either use as a forage in which shoots were removed but the roots were soil-incorporated (−CC), or usage as a green manure cover crop with both shoots and roots incorporated into the soil (+CC). The other treatment was fallow control (F).
When the winter season ended, IRG herbage was harvested from −CC plots using a gasoline-powered brush cutter (FS55, STIHL, Waiblingen, Germany) leaving 3–5 cm of stubble height from the soil surface. After the IRG was harvested, fields were shallowly rotovated (10–15 cm) using a tractor-mounted rotary tiller to mix existing IRG stubble and below-ground biomass with soil. The above- and below-ground IRG herbage from +CC plots (used as a green manure) was incorporated in the same manner as the −CC residue.
The “Daewon” soybean cultivar (one of the most commonly grown cultivars in Korea with relatively large grain size and 120–140 days of growing period) was planted at 4 weeks after IRG harvest to allow sufficient time for incorporated IRG decomposition (Table 3). Before soybean planting, the field was rotovated and a ridge was made to increase infiltration during the monsoon season. Soybean seeds were planted at two seeds per hill, on the ridge with 90 cm inter-row spacing and 15 cm intra-row spacing using a hand-pushed disk planter (TP–10RA, Korea Agritechno Search Corp., Cheongju, Republic of Korea). Soybean was planted each year at 150,000 seeds ha−1. The herbicide alachlor (2.0 kg a.i. ha−1) was applied immediately following planting for weed management. Other management practices followed the guidelines of agricultural standard cultural practices of the Korea Rural Development Administration (RDA, 2003) [17].

2.3. IRG and Soybean Plants Responses Measured

The IRG shoot and root samples were collected at the IRG harvest (Table 3). For IRG above-ground biomass yield, samples were taken from an area of 2-m-×-2-m area per plot. Then, approximately 1 kg of fresh sub-sample was dried at 70 °C until constant dry weight was reached to determine the ratio of fresh to dry matter. In order to collect the IRG below-ground parts, soil was removed in a cylinder shape with 30 cm of diameter and 30 cm of depth in two random locations within each plot. Collected root samples were washed to remove attached soil, then dried at 70 °C for 72 h to determine dry matter. Harvested IRG above-ground biomass was dried, and then the N concentration of above-ground IRG was determined using a Leco TruMac CNS Analyser (LECO Corp., St. Joseph, MI, USA). Above-ground biomass nitrogen content was calculated.
Soybean leaf area index (LAI) and leaf chlorophyll content were measured approximately every two weeks from V7 to R6 stages. LAI was estimated using LAI2200–C with a 90°-angle cap (LI–COR BioSciences, Lincoln, NE, USA). Measurements of LAI were obtained with one above-canopy reading as a reference and six below-canopy readings at 0, 25, and 50% between row centers. The soybean showed leaf color change differences by visual observation in the first year, so in the second and third year, chlorophyll content was measured on fully developed uppermost leaves of 10 plants per plot using the CCM–300 (Opti–Sciences Inc., Hudson, NH, USA), which records chlorophyll content on a surface basis (mg m−2).
The soybean root characteristics were assessed three times to analyze growth development in each stage (Table 3). Cylindrical sampling plots were established with a radius of 15 cm and a depth of 30 cm. A total of seven samples per plot were collected, and after removing the two that were most different, five individuals with similar growth conditions were selected. The selected plants were divided into shoot and root fractions. Washed roots were placed in plastic trays filled with water and then scanned using a flatbed scanner (Expresson 12000XL, Seiko Epson Corp., Nagano, Japan). Scanned root images were analyzed using WinRhizo Pro system (WinRhizo Pro 2017a, Regent Instruments Inc., Sainte Foy, QC, Canada) to determine the total root length, total root surface area, and total root volume.
For soybean yield components, 10 plants from each plot were assessed to determine the number of pods and number of seeds. One hundred-seed weights were obtained for each plot. Grain yields were conducted by assessing a plot size of 3.6 m2 (4 m × 0.9 m) and adjusted for 14% moisture concentration.

2.4. Statistical Method

PROC UNIVARIATE function of SAS 9.4 software (SAS Institute Inc., Cary, NC, USA) was used to assess the normality of data distribution. All measurements were analyzed with ANOVA using PROC MIXED model. IRG cultivar (Kowinearly, Winterhawk) was treated as a fixed effect. In soybeans, treatment (F, Ko−CC, Ko+CC, Win−CC, Win+CC) was treated as a fixed effect. For seasonal responses (LAI, Chlorophyll content, total root length, surface area, volume), different seasons were considered as repeated measures. The block was treated as a random effect. Least significant difference (LSD) tests (significance threshold of p = 0.05) were performed for mean separation. To have an in-depth understanding of treatment effect between IRG-treated group and F, different IRG usages (F versus IRG-treated, F versus +CC, F vs. −CC) were compared using preplanned contrasts for root morphological responses [18].

3. Results

3.1. Soybean Yield Components and Grain Yield

Soybean yield components were compared for three years (Table 4). The number of pods and grains did not differ between the treatments for three years of study. Across the treatments during 2020, the average number of grains tended to have lower values compared to those of 2021 and 2022. There were no significant differences between the treatments in 100-grain weight both in 2020 and 2021, while in 2022, a significant difference was observed (p = 0.0163). In 2022, the Win+CC had the highest 100-grain weight value (31.4 g), while the Win−CC had the lowest value (27.8 g). The average 100-grain weight across the treatment was 26.0, 28.1, and 29.2 g in 2020, 2021, and 2022, respectively.
For soybean grain yield, there were no differences in 2020, but both 2021 and 2022 showed significant differences among treatments (Table 4). In 2020, the average grain yield for +CC was 2.22 Mg ha−1, while F yields were 1.83 Mg ha−1. In 2021, the grain yield was greatest for Ko+CC (2.40 Mg ha−1) and Win+CC (2.46 Mg ha−1), while it was least for Win−CC (1.83 Mg ha−1). When soybean yield was compared based on IRG usage (forage versus green manure), Ko+CC showed a 19% greater yield compared with Ko−CC, and Win+CC showed a 34% higher yield compared with Win−CC (Table 4). Furthermore, the average grain yield of the IRG-treated sample was 2.18 Mg ha−1 compared with 2.00 Mg ha−1 for F. The average of +CC (2.43 Mg ha−1) was 22 and 26% greater compared with F (2.00 Mg ha−1), and the average of −CC (1.93 Mg ha−1), respectively. This pattern of response was similar to 2021 LAI values at the R4 stage (See Section 3.4).
In 2022, Ko+CC (1.87 Mg ha−1) and Win+CC (1.89 Mg ha−1) had the highest grain-yield values, while Win−CC (1.30 Mg ha−1) had the lowest value. Grain yield for Win+CC was 45% greater than the Win−CC. The average of +CC (1.88 Mg ha−1) was 20 and 32% higher compared to F (1.57 Mg ha−1) and −CC (1.42 Mg ha−1), respectively. In the comparison between years, it was observed that 2020 received more rainfall in July compared to 2021. However, there was no significant difference in soybean grain yield, while the yield in 2022 was 24% lower than in 2021 (p = 0.0013).

3.2. IRG Above- and Below-Ground Biomass

The above- and below-ground biomass of two different ecotypes of IRG were compared for 3 years (Table 5). Only a year main effect occurred for IRG below-ground biomass (p = 0.0274). On average, IRG above-ground biomass yield was 6.6, 6.4, and 7 Mg ha−1 of dry matter for 2020, 2021, and 2022, respectively. This was slightly less than in a previous study (8.7 Mg ha−1 of dry matter) in Korea with the Kowinearly cultivar [19]. In 2022, IRG below-ground biomass was 46 and 41% lower than the average of 2020 and 2021 (average of 1.3 versus 2.4 and 2.2 Mg ha−1 of dry matter). However, if IRG was used as a green manure (+CC), the sum of biomass incorporated into the soil was 9.0, 8.6, and 8.3 Mg ha−1 of dry matter in 2020, 2021, and 2022, respectively. Thus, with different usage scenarios such as green manure (+CC) versus forage (−CC), dry-matter input to soil can differ by up to 7-fold.

3.3. IRG Above-Ground Biomass Nitrogen Content

To estimate the nitrogen supply to soybeans from IRG above-ground sources, IRG above-ground nitrogen content was measured (Table 6). Significant differences were observed in the main effect of Year (p < 0.0001). The IRG nitrogen content in 2020 (151 kg ha−1 of N) was 80 and 62% higher than in 2021 and 2022, respectively. No significant variations in IRG nitrogen content were found across different IRG cultivars. This may indicate that IRG above-ground incorporation did not affect soil organic matter (Table S1). Additional input of N from IRG above-ground may have contributed to the increased soybean grain yield of +CC treatments (Table 4) as compared to F or −CC.

3.4. Soybean LAI and Chlorophyll Content

To understand the photosynthetic capacity of soybean during the growing season, LAI and chlorophyll contents were measured during 2021 and 2022 (Table 7). For LAI, there was a treatment × growth-stage interaction in 2021 (p = 0.0388), while there was a growth-stage main effect only in 2022 (p < 0.0001). Hence, chlorophyll content showed growth-stage main effects for both years (p < 0.0001), and there was a treatment main effect in 2021 (p = 0.0061).
Specifically, Ko−CC treatment had the highest LAI value of 1.8 at V7 stage in 2021. The average LAI of IRG-treated plots was slightly higher than F at V7 (1.5 versus 1.3). There were no differences among the treatments at R2. The mean LAI values were 3.2, 3.1, and 3.6 for F with an average −CC, and +CC, respectively, at R4. In 2022, the average LAI values at R5 were the greatest and followed by R2 and R1 (5.3, 3.6, and 2.4, respectively). At R1, F tended to have the lowest LAI value (2.2), while the IRG-treated plots had an average LAI of 2.5. However, there were no statistical differences between the treatments.
In 2021, the chlorophyll content of Ko+CC was greatest (369 mg m−2), while Ko−CC had the lowest value (354 mg m−2) averaged across growth stages. The average value for each growth stage was greatest during R3, followed by R6 and R1 (398, 376, and 312 mg m−2, respectively). In 2022, the chlorophyll content was highest during R3, followed by R2 and R6 (374, 334, 288 mg m−2) across the treatments. Interestingly, the chlorophyll content at R6 in 2021 (376 mg m−2) was 31% higher than that of the R6 stage in 2022 (288 mg m−2), suggesting that the soybean stay-green period was maintained through the later reproductive stage in 2021. There was no difference in chlorophyll content between different usages of IRG in either 2021 or 2022.

3.5. Soybean Total Root Length, Surface Area, and Volume

To investigate the differences in root development in early (vigorous growth), middle (maximum development), and late (before major decline) plant developmental periods, measurements of total root length, surface area, and volume were conducted for 3 years. The total root length, surface area, and volume showed significant treatment × growth stage interactions in 2020 (p < 0.05). In 2021, treatment- and growth-stage main effects were observed (p < 0.05). In 2022, treatment- and growth-stage interactions were observed only for total root length and volume, while significant differences were observed in total root length, surface area, and volume under the main effect of growth stage (p < 0.0001).
In 2020, the total root length, surface area, and volume in the plants showed significant differences among the treatments at R3, with the highest values observed at this stage (avg. of 2030 cm, 286 cm2, 8.3 cm3, Table 8). Among the treatments at R3, the average total root length, surface area, and volume in the plants were highest for the −CC avg., measuring 2580 cm, 373 cm2, and 11.2 cm3, respectively. When different IRG usage was compared with the F using preplanned contrast at R3, the total root length was 62% greater for avg. of −CC (2580 cm) and 35% overall IRG-treated (2148 cm) than that of the F (1590 cm) (Table 9). Similarly, the total surface area was 70% greater for avg. of −CC (373 cm2) and 38% overall IRG-treated (303 cm2) than that of the F (219 cm2) (Table 9). Similarly, the total volume was 78% greater for avg. of −CC (11.2 cm3) and 40% overall IRG-treated (8.8 cm3) than that of the F (6.3 cm3) (Table 9).
In 2021, across the growth stages, total root length, surface area, and volume in the plants were the highest trend in Win−CC with values of 1980 cm, 382 cm2, and 6.4 cm3, respectively. Among the growth stages, R3 showed the largest average values for total root length (2620 cm) and surface area (429 cm2), followed by R6 and V7 (Table 8). When comparing F using preplanned contrasts at the R3 stage, total root length significantly increased by 8% (p = 0.0319) under an average of +CC (2475 cm) compared to F (2290 cm). At the R6 stage, total root volume showed a significant 33% increase (p = 0.0215) with an average of −CC treatment (8.8 cm3) compared to F (6.6 cm3).
In 2022, the total root length showed significant differences between the treatments at R3. The Win+CC had the greatest length (3720 cm), while Ko+CC had the smallest (2220 cm). The total root length of Ko−CC was 40% greater for Ko+CC (3100 versus 2220 cm), and Win+CC was 39% greater for the Win−CC (3720 versus 2670 cm). When comparing between growth stages within a treatment, Ko−CC and Win+CC had a greater total root length at R3. When different IRG usages were compared with F using preplanned contrast at the R3 stage, the IRG-treated (2928 cm) and the average of −CC (2885 cm) and +CC (2970 cm) resulted in total root length increases of 15% (p = 0.0008), 13% (p = 0.0152), and 16% (p = 0.0002) compared to that of the F (2550 cm). In the case of total root surface area, the average values across treatments were relatively higher at the R3 and R6 (Table 8). The total root volume at the R3 stage was greatest for Ko−CC, while Ko+CC had the smallest (7.5 versus 4.4 cm3). At the R6 stage, Win−CC had the highest volume, while Ko+CC had the lowest (11.9 versus 6.5 cm3). Unlike total root length, root volume had the largest value at R6 across the treatment. When different IRG usage was compared with F using preplanned contrast at the R6 stage, the average of the −CC group was of 12% greater root volume compared to F (10.9 versus 9.7 cm3) (p = 0.0028). Overall, the total root length, surface area, and volume in the plants for both R3 and R6 tended to have greater values in 2022 compared to 2021 (Table 8).

4. Discussion

To understand the effects on above- and below-ground soybean development, various IRG-soybean rotation regimes were compared for 3 years under field conditions. Soybean yield component analysis indicated IRG usage as a green manure (+CC) had generally greater grain yield than other treatments, while IRG for forage (−CC) was not different from F across IRG cultivars. This is in line with previous studies that found higher soybean grain yields when both the above-ground and below-ground parts were placed as cover crops in comparison to F [20]. In addition, the introduction of a cover crop increased soybean yield by 14% compared with no cover crop [9]. In contrast, it differed from previous research where the soybean grain yield following IRG cultivation was lower than that after winter fallow [21]. A previous cover crop treatment showed that there was no significant difference in soybean yield compared to no cover crop control [8]. It is likely that the increased input of organic matter and subsequent mineralization in +CC compared with −CC positively influenced soybean grain yield (Table 4). There was also a difference among years in soybean grain yield. The overall mean of the treatments in 2022 was significantly lower than in 2020 or 2021 (p = 0.0013). This significant decrease in grain yield can be attributed to the reduced rainfall in 2022, particularly during the reproductive stage (Table 2). This is in line with previous studies where yield reduction occurred due to water stress during the reproductive growth stage of soybean [22,23]. Particularly, the precipitation in August was reduced by 200 mm and 163 mm in comparison to 2020 and 2021, respectively (Table 2). This period corresponds to the developmental stages of pod development (R3–R4), during which drought stress has an impact on grain yield [24]. In addition, GDD in 2022 was lower by 6 and 77 °C compared to 2020 and 2021 in October, respectively (Table 2). Lee et al. (2022) suggested that conditions with higher GDD levels are favorable to an increase in soybean grain yield [25]. Therefore, it appears that the combination of drought conditions and lower GDD resulted in reduced grain yield. Thus, for 3 years of study indicated that even under unfavorable weather condition, +CC treatments showed greater yield compared to other treatments.
The above- and below-ground biomass of two different ecotypes of IRG showed that IRG below-ground biomass in 2022 was 43% lower than the average of 2020 and 2021. This was also due to a different weather pattern for each growing season (Table 2). Even though the above-ground biomass yield was not affected by the year, lower precipitation during the winter-growing season negatively affected root development. Specifically, the third-year winter growing season had lower precipitation than the previous two years (435, 434 versus 233 mm; November to May). Previous studies addressed that under moderate drought-stress conditions, wheat exhibited reduced root mass in both topsoil and subsoil compared to well-watered conditions [26]. Previous research indicated that as soil penetration resistance increased, root length density decreased in the compacted soil layer [27,28]. Under moderate water stress, the decrease in root weight was more pronounced than that of above-ground biomass [29]. Despite large differences in dry matter input among IRG-treated plots (Table 5), there was no difference in soil organic matter content among the treatments (Table S1). According to previous studies, only 10–20% of dry matter input becomes part of the soil organic matter [30]. Although the amount of biomass input to soil was significantly different, actual differences in the organic matter pool may have been unaffected among treatments.
Starter fertilizer to soybean is a common practice as prior research indicated that supplying 50 kg ha−1 of starter nitrogen fertilizer resulted in the highest soybean grain yield [31]. Based on the IRG above-ground biomass nitrogen content analysis, the amount of N supply from +CC exceeded suggested initial N fertilization of the previous study. Thus, to promote the initial growth of soybeans, implementing crop rotation with IRG as a cover crop may be an alternative method of using inorganic nitrogen starter fertilizer. This is in line with the recommendation of the previous study that use of a gramineous cover crop stored 25% more N on the soil surface than no cover crop control and may replace starter N fertilizer [32]. Above-ground IRG had 79–156 kg ha−1 of N, which subsequently decomposed; incorporated IRG could be served as a starter fertilizer. Previous studies also reported that N accumulation of 26 kg ha−1 from buried oat straw and 39 kg ha−1 from cereal rye residue could be supplied to following crops [33,34]. Sievers and Cook (2018) observed that cereal rye residue exhibited a slower and more gradual release of nitrogen compared to hairy vetch, emphasizing the need for optimal synchronization of cover crop nitrogen release with subsequent crop nitrogen uptake to reduce nitrogen fertilizer [35].
The soybean LAI of IRG incorporated (+CC) had relatively higher values than other treatments for 2021 at R4. This is similar to a previous study that LAI of soybean at the R4 stage was 41% higher when the cover crop was incorporated compared with the no-cover crop control [20]. It is reported that under abiotic stress conditions, rice exhibited higher LAI and yield when intercropped with green manure, compared to the control conditions [36]. Previous studies also indicated that when the LAI of soybean during the R1–R4 stage ranges from 3.5 to 4, the photosynthetic potential is maximized [37,38]. The chlorophyll content is a crucial indicator reflecting the photosynthetic activity of plants [39]. In this study, the chlorophyll content during the R3 and R6 stages decreased sooner in 2022 compared to that of 2021, likely due to reduced rainfall in July and August (p < 0.0001, Table 2). Elsalahy and Reckling (2022) reported a 7% reduction in chlorophyll content of drought-stressed soybeans during the vegetative and flowering stages compared with under rainfed conditions [40]. Gholamin et al. (2011) also observed that drought stress diminished chlorophyll content and yield while also revealing a strong correlation between chlorophyll content and harvest yield [41]. Therefore, the decrease in chlorophyll content during the R3 and R6 stages occurred due to drought conditions in 2022 regardless of IRG input regimes.
In 2020, the total soybean root length, surface area, and volume was greater for IRG-treated crops than that of the F across the IRG cultivars. It was reported that as the root length density of the cover crops (triticale and pearl millet) increases, there is a corresponding increase in soybean root length density in 5–10 cm of soil [42]. Additionally, it was noted that the vigorous root growth of triticale and pearl millet led to a reduction in soil-penetration resistance [42]. During favorable conditions in 2020 and 2021, −CC showed a tendency for greater soybean total root length and surface area than +CC. When plants had moderate nutrient depletion, they tend to develop excessive roots to scavenge the nutrients and water. It was reported that low phosphorus concentrations lead to a high density of long roots [43]. Lecompte et al. (2008) observed a 180% increase in root length when nitrogen was limited compared to when it was sufficient [44]. Additionally, they observed an enhanced root density extending into deeper soil layers under conditions of low-soil nitrogen levels, and they characterized root expansion as continuous across the entire soil profile [44]. In the current study, this is probably why there were root development differences in later growing seasons between −CC and +CC. Hence, due to the predominant contribution of fine roots at root length, the total root length was significantly influenced by fine root development [45]. Fine roots are directly associated with water uptake compared to main roots, and they enable stable crop production through root distribution and development [46]. In the current study, overall root length development was highest at R3 in 2022, and Win+CC had the highest total root length. This indicates fine root development reached maximum at R3, suggesting Win+CC probably had greater adaptability to unfavorable weather conditions, including drought. The previous research suggested that the substantial proportion of fine roots in the root domain allows for the optimization of the capacity to explore the soil in preparation for drought conditions [47]. Thus, the current study suggested that incorporating IRG in soybean production may enhance the root system of soybeans and soybean yield.
In later seasons (R3 and 6), the total root length, surface area, and volume tended to have greater values in 2022 compared to 2021 (Table 8). This can be attributed to an overall lower precipitation, particularly during the months of July and October in 2022, leading to the development of larger and elongated roots for enhanced water acquisition (Table 2). Fenta et al. (2014) reported that most cultivars had increased root length, surface area, and volume under drought conditions, excluding drought-sensitive varieties [48]. Hence, it was reported that ruzigrass was found to enhance the growth of soybean roots in compacted soil conditions compared with other preceding crops (maize, oat, and wheat) [49]. Additionally, it has been suggested that the continuous presence of biopores created by ruzigrass in the preceding crop can promote soybean root growth even under water-stressed conditions, potentially leading to increased yields [49]. According to the previous study, cover crops resulted in an approximately 80% increase in water infiltration compared with no cover crop [9]. Basche et al. (2016) reported that a previous cover crop treatment increased soil water content at a depth of 30 cm relative to the no-cover crop [8]. Therefore, it can be suggested that the increased water-holding capacity due to the cover crop may have contributed to enhanced soybean root growth and maintenance.
When overall yield was compared between years, the yield in 2022 was lower compared to the years 2020 and 2021 (Table 4). This is attributed to the extended development of root volume and LAI during later seasons (Table 7 and Table 8). This is most likely due to the drought in 2022, which disrupted nutrient flow as plants progressed from the vegetative stage to the reproductive stage. Islam et al. (2019) suggested that the decline in LAI during the reproductive stage could be attributed to a reduction in leaf nitrogen concentration required for grain filling in rice [50].

5. Conclusions

The soybean yield of +CC appears to be consistently high regardless of the IRG cultivar, and it demonstrates an increase in yield even under unfavorable weather conditions. Consequently, growers can select IRG varieties based on their specific objectives. For instance, to enhance soybean yield through early sowing, the early maturity IRG ecotype, such as “Kowinearly”, could be cultivated and incorporated as a green manure. On the other hand, for enhancing IRG biomass and soil fertility, the late maturity ecotype, such as “Winterhawk”, could be grown and harvested. Soybean root characteristic differences showed substantial variability depending on the year and treatments. However, when compared to the F treatment, no adverse effects were evident. As cover-crop decomposition rates vary, future research should focus on quantifying the decomposition rate and nitrogen release of IRG, estimating nutrient supply to subsequent crop growth stages.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture13102038/s1, Table S1: Soil chemical properties before and after Italian ryegrass cultivation in three years.

Author Contributions

Conceptualization, C.N.; methodology M.C., N.C. and J.L.; formal analysis M.C. and C.N.; investigation S.L. and Y.K.; writing—original draft preparation M.C. and C.N.; writing—review and editing Y.K., S.L. and C.N.; validation S.L. and Y.K.; funding acquisition C.N.; project administration C.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2021R1I1A3040330).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Authors would like to thank the Gyeongsang National University Seed Science Laboratory members and Research Farm staffs for data collection and field management.

Conflicts of Interest

The authors declare that there are no conflict of interest.

References

  1. Hungria, M.; Mendes, I.C. Nitrogen fixation with soybean: The perfect symbiosis? In Biological Nitrogen Fixation; de Bruijn, F.J., Ed.; John Wiley & Sons: Hoboken, NJ, USA, 2015; pp. 1009–1024. [Google Scholar] [CrossRef]
  2. Gentry, L.; Below, F.E.; David, M.B.; Bergerou, J. Source of the soybean N credit in maize production. Plant Soil 2001, 236, 175–184. [Google Scholar] [CrossRef]
  3. Rhine, M.D.; Stevens, G.; Shannon, G.; Wrather, A.; Sleper, D. Yield and nutritional responses to waterlogging of soybean cultivars. Irrig. Sci. 2010, 28, 135–142. [Google Scholar] [CrossRef]
  4. Mourtzinis, S.; Specht, J.E.; Conley, S.P. Defining Optimal Soybean Sowing Dates across the US. Sci. Rep. 2019, 9, 2800. [Google Scholar] [CrossRef] [PubMed]
  5. Kokubun, M. Genetic and cultural improvement of soybean for waterlogged conditions in Asia. Field Crops Res. 2013, 152, 3–7. [Google Scholar] [CrossRef]
  6. de Freitas, V.F.; Cerezini, P.; Hungria, M.; Nogueira, M.A. Strategies to deal with drought-stress in biological nitrogen fixation in soybean. Appl. Soil Ecol. 2022, 172, 104352. [Google Scholar] [CrossRef]
  7. Sainju, U.; Whitehead, W.; Singh, B. Cover crops and nitrogen fertilization effects on soil aggregation and carbon and nitrogen pools. Can. J. Soil Sci. 2003, 83, 155–165. [Google Scholar] [CrossRef]
  8. Basche, A.D.; Kaspar, T.C.; Archontoulis, S.V.; Jaynes, D.B.; Sauer, T.J.; Parkin, T.B.; Miguez, F.E. Soil water improvements with the long-term use of a winter rye cover crop. Agric. Water Manag. 2016, 172, 40–50. [Google Scholar] [CrossRef]
  9. Chalise, K.S.; Singh, S.; Wegner, B.R.; Kumar, S.; Pérez-Gutiérrez, J.D.; Osborne, S.L.; Nleya, T.; Guzman, J.; Rohila, J.S. Cover crops and returning residue impact on soil organic carbon, bulk density, penetration resistance, water retention, infiltration, and soybean yield. Agron. J. 2019, 111, 99–108. [Google Scholar] [CrossRef]
  10. Liu, S.; Ma, Z.; Zhang, Y.; Chen, Z.; Du, X.; Mu, Y. The impact of different winter cover crops on weed suppression and corn yield under different tillage systems. Agronomy 2022, 12, 999. [Google Scholar] [CrossRef]
  11. Siri-Prieto, G.; Reeves, D.W.; Raper, R.L. Tillage systems for a cotton–peanut rotation with winter-annual grazing: Impacts on soil carbon, nitrogen and physical properties. Soil Tillage Res. 2007, 96, 260–268. [Google Scholar] [CrossRef]
  12. Pietola, L.; Alakukku, L. Root growth dynamics and biomass input by Nordic annual field crops. Agric. Ecosyst. Environ. 2005, 108, 135–144. [Google Scholar] [CrossRef]
  13. Austin, E.E.; Wickings, K.; McDaniel, M.D.; Robertson, G.P.; Grandy, A.S. Cover crop root contributions to soil carbon in a no-till corn bioenergy cropping system. GCB Bioenergy 2017, 9, 1252–1263. [Google Scholar] [CrossRef]
  14. Kuo, S.; Sainju, U.; Jellum, E. Winter cover crop effects on soil organic carbon and carbohydrate in soil. Soil Sci. Soc. Am. J. 1997, 61, 145–152. [Google Scholar] [CrossRef]
  15. Kuo, S.; Jellum, E. Long-term winter cover cropping effects on corn (Zea mays L.) production and soil nitrogen availability. Biol. Fertil. Soils 2000, 31, 470–477. [Google Scholar] [CrossRef]
  16. He, H.-B.; Li, W.-X.; Zhang, Y.-W.; Cheng, J.-K.; Jia, X.-Y.; Li, S.; Yang, H.-R.; Chen, B.-M.; Xin, G.-R. Effects of Italian ryegrass residues as green manure on soil properties and bacterial communities under an Italian ryegrass (Lolium multiflorum L.)-rice (Oryza sativa L.) rotation. Soil Tillage Res. 2020, 196, 104487. [Google Scholar] [CrossRef]
  17. Rural Development Administration (RDA). Analysis Standard of Agricultural Test and Research; RDA: Suwon, Republic of Korea, 2003.
  18. Kiernan, K.; Tobias, R.; Gibbs, P.; Tao, J. CONTRAST and ESTIMATE statements made easy: The LSMESTIMATE statement. In Proceedings of the SAS Global Forum, Las Vegas, NV, USA, 4–7 April 2011; SAS Institute Inc.: Cary, NC, USA, 2011. [Google Scholar]
  19. Kim, K.; Choi, G.; Lee, S.; Hwang, T.; Lee, G.; Ji, H.; Park, S. Effect of harvest time of rice after seeding of Italian ryegrass on growth characteristics and dry matter yield of IRG in paddy field. J. Korean Soc. Grassl. Forage Sci. 2016, 36, 287–292. (In Korean) [Google Scholar] [CrossRef]
  20. Balbinot, A.A.; Santos, J.C.F.D.; Debiasi, H.; Yokoyama, A.H. Contribution of roots and shoots of Brachiaria species to soybean performance in succession. Pesqui. Agropecu. Bras. 2017, 52, 592–598. [Google Scholar] [CrossRef]
  21. Pedersen, J.; Rodriguez-Kabana, R. Winter grass cover crop effects on nematodes and yields of double cropped soybean. Plant Soil 1991, 131, 287–291. [Google Scholar] [CrossRef]
  22. Eck, H.; Mathers, A.; Musick, J. Plant water stress at various growth stages and growth and yield of soybeans. Field Crops Res. 1987, 17, 1–16. [Google Scholar] [CrossRef]
  23. Jumrani, K.; Bhatia, V.S. Impact of combined stress of high temperature and water deficit on growth and seed yield of soybean. Physiol. Mol. Biol. Plants 2018, 24, 37–50. [Google Scholar] [CrossRef]
  24. Wei, Y.; Jin, J.; Jiang, S.; Ning, S.; Liu, L. Quantitative response of soybean development and yield to drought stress during different growth stages in the Huaibei Plain, China. Agronomy 2018, 8, 97. [Google Scholar] [CrossRef]
  25. Lee, J.; Choi, M.; Choi, N.; Kim, G.; Lee, Y.; Bae, H.; Na, C. The effects of planting date and tillage practice on growth and yield of maize and soybean in rotation with winter onion. Agronomy 2022, 12, 2125. [Google Scholar] [CrossRef]
  26. Fang, Y.; Du, Y.; Wang, J.; Wu, A.; Qiao, S.; Xu, B.; Zhang, S.; Siddique, K.H.; Chen, Y. Moderate drought stress affected root growth and grain yield in old, modern and newly released cultivars of winter wheat. Front. Plant Sci. 2017, 8, 672. [Google Scholar] [CrossRef] [PubMed]
  27. Lin, L.R.; He, Y.B.; Chen, J.Z. The influence of soil drying-and tillage-induced penetration resistance on maize root growth in a clayey soil. J. Integr. Agric. 2016, 15, 1112–1120. [Google Scholar] [CrossRef]
  28. Rosolem, C.A.; Foloni, J.; Tiritan, C. Root growth and nutrient accumulation in cover crops as affected by soil compaction. Soil Tillage Res. 2002, 65, 109–115. [Google Scholar] [CrossRef]
  29. Nejad, T.S. Effect of drought stress on shoot/root ratio. World Acad. Sci. Eng. Technol. 2011, 81, 598–600. [Google Scholar]
  30. Lewandowski, A. Organic Matter Management; University of Minnesota Extension Service: St. Paul, MN, USA, 2000; Available online: https://hdl.handle.net/11299/51896 (accessed on 24 September 2023).
  31. Gai, Z.; Zhang, J.; Li, C. Effects of starter nitrogen fertilizer on soybean root activity, leaf photosynthesis and grain yield. PLoS ONE 2017, 12, e0174841. [Google Scholar] [CrossRef]
  32. Landriscini, M.R.; Galantini, J.A.; Duval, M.E.; Capurro, J.E. Nitrogen balance in a plant-soil system under different cover crop-soybean cropping in Argentina. Appl. Soil Ecol. 2019, 133, 124–131. [Google Scholar] [CrossRef]
  33. Mulvaney, M.J.; Wood, C.; Balkcom, K.S.; Shannon, D.; Kemble, J. Carbon and nitrogen mineralization and persistence of organic residues under conservation and conventional tillage. Agron. J. 2010, 102, 1425–1433. [Google Scholar] [CrossRef]
  34. Jahanzad, E.; Barker, A.; Hashemi, M.; Eaton, T.; Sadeghpour, A.; Weis, S. Nitrogen release dynamics and decomposition of buried and surface cover crop residues. Agron. J. 2016, 108, 1735–1741. [Google Scholar] [CrossRef]
  35. Sievers, T.; Cook, R.L. Aboveground and root decomposition of cereal rye and hairy vetch cover crops. Soil Sci. Soc. Am. J. 2018, 82, 147–155. [Google Scholar] [CrossRef]
  36. Prashanthi, B.; Suresh, K.; Ramulu, V.; Sridevi, S. Growth and Yield attributes of various rice varieties under saline irrigation water as affected by agronomic management practices. Int. J. Agric. Stat. Sci. 2020, 16, 599–606. [Google Scholar]
  37. Board, J.; Harville, B. Explanations for greater light interception in narrow-vs. wide-row. Crop Sci. 1992, 32, 198–202. [Google Scholar] [CrossRef]
  38. Acuña, J.C.; Villamil, M.B. Short-term effects of cover crops and compaction on soil properties and soybean production in Illinois. Agron. J. 2014, 106, 860–870. [Google Scholar] [CrossRef]
  39. Dong, S.; Jiang, Y.; Dong, Y.; Wang, L.; Wang, W.; Ma, Z.; Yan, C.; Ma, C.; Liu, L. A study on soybean responses to drought stress and rehydration. Saudi J. Biol. Sci. 2019, 26, 2006–2017. [Google Scholar] [CrossRef] [PubMed]
  40. Elsalahy, H.H.; Reckling, M. Soybean resilience to drought is supported by partial recovery of photosynthetic traits. Front. Plant Sci. 2022, 13, 971893. [Google Scholar] [CrossRef] [PubMed]
  41. Gholamin, R.; Khayatnezhad, M. The effect of end season drought stress on the chlorophyll content, chlorophyll fluorescence parameters and yield in maize cultivars. Sci. Res. Essays 2011, 6, 5351–5357. [Google Scholar]
  42. Calonego, J.C.; Rosolem, C.A. Soybean root growth and yield in rotation with cover crops under chiseling and no-till. Eur. J. Agron. 2010, 33, 242–249. [Google Scholar] [CrossRef]
  43. López-Bucio, J.; Cruz-Ramırez, A.; Herrera-Estrella, L. The role of nutrient availability in regulating root architecture. Curr. Opin. Plant Biol. 2003, 6, 280–287. [Google Scholar] [CrossRef]
  44. Lecompte, F.; Bressoud, F.; Pares, L.; De Bruyne, F. Root and nitrate distribution as related to the critical plant N status of a fertigated tomato crop. J. Hortic. Sci. Biotechnol. 2008, 83, 223–231. [Google Scholar] [CrossRef]
  45. Zobel, R.W. Tertiary root systems. In Roots and Soil Management: Interactions between Roots and the Soil; Zobel, R.W., Wright, S.F., Eds.; Agronomy Monograph 48; American Society of Agronomy: Madison, WI, USA, 2005; pp. 33–56. [Google Scholar] [CrossRef]
  46. Norby, R.J. Issues and perspectives for investigating root responses to elevated atmospheric carbon dioxide. Plant Soil 1994, 165, 9–20. [Google Scholar] [CrossRef]
  47. Komatsu, S.; Hossain, Z. Organ-specific proteome analysis for identification of abiotic stress response mechanism in crop. Front. Plant Sci. 2013, 4, 71. [Google Scholar] [CrossRef] [PubMed]
  48. Fenta, B.A.; Beebe, S.E.; Kunert, K.J.; Burridge, J.D.; Barlow, K.M.; Lynch, J.P.; Foyer, C.H. Field phenotyping of soybean roots for drought stress tolerance. Agronomy 2014, 4, 418–435. [Google Scholar] [CrossRef]
  49. Bertollo, A.M.; de Moraes, M.T.; Franchini, J.C.; Soltangheisi, A.; Junior, A.A.B.; Levien, R.; Debiasi, H. Precrops alleviate soil physical limitations for soybean root growth in an Oxisol from southern Brazil. Soil Tillage Res. 2021, 206, 104820. [Google Scholar] [CrossRef]
  50. Islam, M.M.; Urmi, T.A.; Rana, M.S.; Alam, M.S.; Haque, M.M. Green manuring effects on crop morpho-physiological characters, rice yield and soil properties. Physiol. Mol. Biol. Plants 2019, 25, 303–312. [Google Scholar] [CrossRef]
Table 1. Soil chemical properties of experimental site.
Table 1. Soil chemical properties of experimental site.
Exchangeable Cations
pHOMAv. P2O5KCaMgEC
(1:5)(g kg−1)(mg kg−1)(cmol+ kg−1)(dS m−1)
6.511940.34.10.50.2
Table 2. Monthly mean temperature, growing degree days (GDD), and precipitation during the research period.
Table 2. Monthly mean temperature, growing degree days (GDD), and precipitation during the research period.
Month2019–20202020–20212021–20222019–20202020–20212021–20222019–20202020–20212021–2022
Temperature (°C) GDD (°C) * Precipitation (mm)
November9.4 9.1 8.4 61 22 49 22 26 44
December2.9 1.3 2.5 0 0 0 42 9 2
January3.0 0.6 0.4 3 7 0 106 16 0
February4.5 4.8 1.4 7 18 0 46 25 0
March8.7 9.8 8.7 44 52 51 41 159 116
April11.4 13.6 14.3 61 174 218 68 82 70
May18.2 17.6 18.8 415 358 401 110 117 1
June23.0 22.2 22.7 405 376 393 234102 121
July22.7 26.2 26.5 413 516 526 588 359 218
August27.3 26.0 26.3 554 517 515 357 320 157
September20.7 21.9 21.8 332 369 365 200 122 167
October14.5 15.9 15.1 102 173 96 29 46 22
* Base temperatures for GDD were 5 and 10 °C for IRG (November–May) and soybean (June–October), respectively.
Table 3. Schedule of field management operations and agronomic trait measurements during IRG and soybean cultivations.
Table 3. Schedule of field management operations and agronomic trait measurements during IRG and soybean cultivations.
CropOperation2019–20202020–20212021–2022
IRG(before) Soil sampling6 November30 October4 November
Planting and preplant fertilizer input14 November7 November5 November
Additional N input8 February7 March9 March
Harvest1 May7 May11 May
Plowing1 May 18 May13 May
(after) Soil sampling 1 June24 May18 May
SoybeanPlanting3 June8 June8 June
Samplings for root characteristics 9 July (V4)22 July (V7)20 July (R1)
5 September (R3)18 August (R3)16 August (R3)
10 October (R5)8 October (R6)5 October (R6)
Harvest24 October21 October24 October
Table 4. Soybean yield components and grain yield after various Italian ryegrass cultivation treatments for three years.
Table 4. Soybean yield components and grain yield after various Italian ryegrass cultivation treatments for three years.
YearTreatmentPods No.Grain No.100-Grain WeightGrain Yield
(plant−1)(g)(Mg ha−1)
2020F *52 ns 40 ns25.0 ns1.83 ns
Ko−CC615025.52.03
Ko+CC554327.02.30
Win−CC594725.61.94
Win+CC473526.72.14
mean554326.02.05 A
2021F76 ns99 ns26.5 ns2.00 b
Ko−CC8912828.02.02 b
Ko+CC7310727.92.40 a
Win−CC7310528.01.83 b
Win+CC7410428.52.46 a
mean7711128.12.14 A
2022F66 ns76 ns28.5 bc1.57 ab
Ko−CC648228.6 bc1.53 ab
Ko+CC718329.8 ab1.87 a
Win−CC728127.8 c1.30 b
Win+CC688831.4 a1.89 a
Mean688229.21.63 B
* Fallow field as control, F; early-maturing cultivar “Kowinearly”, Ko; late-maturing “Winterhawk”, Win; a forage, −CC; a green manure cover crop, +CC. Within each year, values followed by different lowercase letters are significantly different between treatments at p ≤ 0.05; ns, not significant. Values followed by different uppercase letters are significantly different between years at p ≤ 0.05.
Table 5. Above- and below-ground biomass of two Italian ryegrass cultivars for 3 years.
Table 5. Above- and below-ground biomass of two Italian ryegrass cultivars for 3 years.
CultivarAbove-Ground Dry MatterBelow-Ground Dry Matter
(Mg ha−1)
202020212022Mean202020212022Mean
Kowinearly6.86.76.96.82.81.91.22.0
Winterhawk6.46.07.26.52.12.51.42.0
Mean6.66.47.0 2.4 A *2.2 A1.3 B
* Values followed by different uppercase letters are significantly different between years at p ≤ 0.05.
Table 6. Above-ground biomass nitrogen content of two Italian ryegrass cultivars for 3 years.
Table 6. Above-ground biomass nitrogen content of two Italian ryegrass cultivars for 3 years.
CultivarAbove-Ground Nitrogen Content (kg ha−1)
202020212022MEAN
Kowinearly15683107115
Winterhawk1478679104
Mean151 A *84 B93 B
* Values followed by different uppercase letters are significantly different between years at p ≤ 0.05.
Table 7. Soybean LAI and chlorophyll content in different growth stages after various Italian ryegrass cultivation treatments for three years.
Table 7. Soybean LAI and chlorophyll content in different growth stages after various Italian ryegrass cultivation treatments for three years.
YearTreatmentLAIChlorophyll Content
(mg m−2)
V7R2R4MeanR1R3R6Mean
2021F *1.3 C b 1.8 Ba3.2 Aab2.1 ns316399382365 ab
Ko−CC1.8 Ba1.6 Ba3.1 Ab2.1303391368354 c
Ko+CC1.4 Bab1.7 Ba 3.6 Aa2.2322405381369 a
Win−CC1.3 Bb1.6 Ba3.1 Ab2.0297397378357 bc
Win+CC1.5 Bab1.7 Ba3.5 Aab2.2320398371363 ab
Mean1.4 C1.7 B3.3 A 312 C §398 A376 B
R1R2R5 R2R3R6Mean
2022F2.2 ns3.7 ns5.3 ns3.7 ns331378296335 ns
Ko−CC2.43.55.33.7343383294340
Ko+CC2.33.45.33.7324371282326
Win−CC2.53.75.13.7340359281326
Win+CC2.83.95.34.0330379288332
Mean2.4 C3.6 B 5.3 A 334 B374 A288 C
* Fallow field as control, F; early maturing cultivar ‘Kowinearly’, Ko; late maturing ‘Winterhawk’, Win; a forage, −CC; a green manure cover crop, +CC. Within a treatment, values followed by different uppercase letters are significantly different between growth stages at p ≤ 0.05. Within a growth stage, values followed by different lowercase letters are significantly different between treatments at p ≤ 0.05; ns, not significant. § Values followed by different uppercase letters are significantly different between growth stages at p ≤ 0.05.
Table 8. Soybean total root length, surface area, and volume in different growth stages after various Italian ryegrass cultivation treatments for three years.
Table 8. Soybean total root length, surface area, and volume in different growth stages after various Italian ryegrass cultivation treatments for three years.
TreatmentTotal Root LengthTotal Root Surface AreaTotal Root Volume
(cm plant−1)(cm2 plant−1)(cm3 plant−1)
2020
V4R3R5MeanV4R3R5MeanV4R3R5Mean
F *664 B a 1590 Ab876 Ba1040 b77 Ca219 Ab152 Bb149 c1.6 Ba6.3 Ac4.5 Ab4.1 b
Ko−CC732 Ba2680 Aa992 Ba1470 a87 Ca361 Aa182 Bab210 ab1.9 Ca10.0 Aab5.9 Bab 5.9 ab
Ko+CC707 Ba1890 Ab1020 Ba1206 ab81 Ca257 Ab187 Bab175 bc1.7 Ba7.3 Abc5.8 Aab4.9 b
Win−CC794 Ca2480 Aa1290 Ba1521 a91 Ca385 Aa239 Ba238 a2.0 Ca12.3 Aa8.0 Ba7.4 a
Win+CC574 Ba1540 Ab909 Ba1007 b69 Ba207 Ab162 Aab146 c1.6 Ba5.6 Ac4.9 Aab4.0 b
Mean694 C2030 A1020 B 81 C286 A184 B 1.8 C8.3 A5.8 B
2021
V7R3R6MeanV7R3R6MeanV7R3R6Mean
F593 ns229014601450 bc121 ns409337289 b2.0 ns6.26.64.9 abc
Ko−CC567238014301460 bc123429366306 b2.26.78.05.6 ab
Ko+CC688210012701350 c131332271245 b2.04.34.93.7 c
Win−CC709349017401980 a135559452382 a2.17.59.66.4 a
Win+CC856285016301780 ab142418330296 b1.95.15.64.2 bc
Mean683 C2620 A1510 B 130 C429 A351 B 2.0 B6.0 A6.9 A
2022
R1R3R6MeanR1R3R6MeanR1R3R6Mean
F2100 Aa2550 Abc2100 Aa2250292 ns452500415 3.3 Ca6.5 Bab9.7 Aab6.5
Ko−CC1970 Ba3100 Aab1960 Ba23502755364894343.1 Ca7.5 Ba9.9 Aab6.8
Ko+CC1820 Aa2220 Ac2410 Aa21502643504383513.1 Ba4.4 ABb6.5 Ac4.7
Win−CC1980 Aa2670 Abc2260 Aa23002754615754373.1 Ca6.4 Bab11.9 Aa7.1
Win+CC1670 Ca3720 Aa2700 Ba26902475494984312.9 Ba6.5 Aab7.5 Abc5.6
Mean1910 C2850 A2290 B 271 B470 A500 A 3.1 C6.3 B9.1 A
* Fallow field as control, F; Early-maturing cultivar “Kowinearly”, Ko; Late-maturing “Winterhawk”, Win; a forage, −CC; A green manure cover crop, +CC. Within a treatment, values followed by different uppercase letters are significantly different between growth stages at p ≤ 0.05. Within a growth stage, values followed by different lowercase letters are significantly different between treatments at p ≤ 0.05; ns, not significant.
Table 9. Preplanned contrast p-value of soybean total root length, surface area, and volume in different growth stages after various Italian ryegrass cultivation treatments for 3 years.
Table 9. Preplanned contrast p-value of soybean total root length, surface area, and volume in different growth stages after various Italian ryegrass cultivation treatments for 3 years.
YearPreplanned ContrastTotal Root LengthTotal Root Surface AreaTotal Root Volume
V4R3R5V4R3R5V4R3R5
2020IRG vs. F0.4371 *0.0023 0.48040.64980.00350.39220.85110.01020.3802
−CC vs. F0.3721<0.00010.27280.5794<0.00010.17590.77630.00020.1465
+CC vs. F0.59870.34160.85120.78360.38210.84100.95340.40040.8895
V7R3R6V7R3R6V7R3R6
2021IRG vs. F0.42480.29520.55390.76710.76120.58110.87550.38660.1861
−CC vs. F0.46310.77790.86630.80680.15430.14160.85970.14130.0215
+CC vs. F0.46880.03190.36280.76710.37740.63180.91300.92200.9485
R1R3R6R1R3R6R1R3R6
2022IRG vs. F0.32080.00080.09630.59630.08500.96880.84980.77160.0465
−CC vs. F0.35280.01520.08470.64260.41760.58440.89000.67010.0028
+CC vs. F0.37600.00020.18760.61470.02080.63410.83570.34140.5730
* Significance evaluated at 0.05 probability level. Values in boldface are statistically significant.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Choi, M.; Choi, N.; Lee, J.; Lee, S.; Kim, Y.; Na, C. Effects of Italian Ryegrass (Lolium multiflorum) Cultivation for Green Manure and Forage on Subsequent Above- and Below-Ground Growth and Yield of Soybean (Glycine max). Agriculture 2023, 13, 2038. https://doi.org/10.3390/agriculture13102038

AMA Style

Choi M, Choi N, Lee J, Lee S, Kim Y, Na C. Effects of Italian Ryegrass (Lolium multiflorum) Cultivation for Green Manure and Forage on Subsequent Above- and Below-Ground Growth and Yield of Soybean (Glycine max). Agriculture. 2023; 13(10):2038. https://doi.org/10.3390/agriculture13102038

Chicago/Turabian Style

Choi, Miri, Nayoung Choi, Jihyeon Lee, Sora Lee, Yoonha Kim, and Chaein Na. 2023. "Effects of Italian Ryegrass (Lolium multiflorum) Cultivation for Green Manure and Forage on Subsequent Above- and Below-Ground Growth and Yield of Soybean (Glycine max)" Agriculture 13, no. 10: 2038. https://doi.org/10.3390/agriculture13102038

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop