Impact of Monoculture and Various Ratios of Intercropped Oats and Daikon Radish Cover Crops on Soil Properties, Weed Suppression, and Spinach Yield

Abstract

Optimizing seeding ratios in mixed cover crop species can maximize their ecological benefits, such as soil properties and weed suppression. A two-year field study assessed seven oat (O) and daikon radish (D) ratios (100:0 to 0:100) for their effects on soil quality, weed pressure, and subsequent spinach yield. Measured parameters included cover crop biomass, C:N ratio, land equivalence ratio (LER), soil organic carbon (SOC), microbial population, soil enzyme activities, bulk density, porosity, moisture, and water infiltration time. The impact of intercrop residues and two weeding strategies (hand weeding and no weeding) on weed pressure and spinach yield was also assessed. Oat monoculture produced the highest biomass (338.7 g m⁻²), while radish monoculture biomass was the lowest (256.1 g m⁻²). Yet the 30:70 (O:D) ratio contributed to the highest SOC (0.96). The C:N ratio of all intercropped combinations was below the critical threshold (25:1) that causes N immobilization, with oat monoculture having the highest value (23:1). The microbial population was highest with the 10:90 (O:D) ratio, with 12.8 × 10⁻⁴ most probable number per g⁻¹ soil. While urease and dehydrogenase enzyme activities were not affected by intercrop ratios, β-glucosidase and alkaline phosphatase activities were up to 30% higher in daikon radish-dominated intercrops. Bulk density decreased by 31.7% in oat monoculture, whereas infiltration time was shortened in daikon radish monoculture by 41.7% (4.6 s). Weed suppression was strongest in oat monoculture and the 90:10 (O:D) intercropping, reducing weed populations by over 30%. Spinach yield was highest in oat monoculture with hand weeding (842.9 g m⁻²), with a 40.2% increase over weeding alone. Overall, daikon radish-dominated intercropping ratios were more effective in enhancing soil properties, whereas oat-dominated intercropping improved spinach yield, mainly due to slower decomposition, thus better suppressing weeds.

1. Introduction

Spinach (Spinacia oleracea L.) is a widely cultivated leafy vegetable valued for its nutrient-rich foliage, which contains essential minerals, vitamins, antioxidants, and phenolic compounds that contribute significantly to human health [1,2,3]. Approximately 80% of spinach roots are concentrated within the top 15 cm of soil [4], making the crop highly sensitive to soil fertility. As a result, the physical, chemical, and biological properties of the upper soil layer, along with nutrient availability, are critical determinants of spinach productivity.

Weed management presents another major challenge in spinach cultivation. The crop’s slow initial growth, especially during early developmental stages, limits its competitiveness against weeds [2,5]. Weed interference can adversely affect germination, seedling vigor, plant survival, and ultimately yield [6]. The rise of herbicide-resistant weed species, combined with the limited number of approved herbicides for spinach, further constrains chemical weed control options [7]. Additionally, increasing concerns over chemical use and the high cost of hand weeding underscore the need for alternative weed management strategies.

Cover crops offer multiple agroecological benefits and align with sustainable agricultural practices [8,9]. To fully realize these benefits, it is essential to align cover crop selection with specific production goals and system requirements [10,11]. Traditionally, cover crops are grown either as monocultures or in species mixtures [12,13]. Monocultures often produce greater biomass, which is effective for weed suppression [14]. In contrast, monoculture can deplete soil nutrients, increase vulnerability to pests and diseases, and reduce soil biodiversity [15,16,17,18]. However, mixed species cover crops tend to offer a broader range of agroecological services, even if individual benefits are less pronounced than in monocultures.

One of the key challenges in integrating multi-species cover crops into cropping systems is determining optimal seeding ratios. Intercropping, including the use of cover crops, involves growing multiple species together to enhance ecological balance and land-use efficiency [13]. This practice can improve soil quality by boosting microbial diversity and nutrient availability [19] and may also suppress weed establishment more effectively through competitive and allelopathic interactions, potentially reducing reliance on chemical weed control.

Daikon radish (Raphanus sativus var. longipinnatus), a member of the Brassicaceae family, is widely recognized as an effective cover crop due to its deep, elongated taproot, which penetrates compacted soil layers, earning it the nickname “bio-drill” or “tillage radish” [20,21]. This root architecture improves soil tilth by breaking hardpans, enhancing aeration, facilitating water infiltration, and stimulating microbial and enzymatic activity [21,22]. Daikon radish also functions as a nutrient scavenger, efficiently retrieving residual nitrogen, calcium, sulfur, and magnesium from deeper soil layers and redistributing them to the upper profile, thereby improving fertility for subsequent crops [23]. Its rapid growth produces a dense canopy that suppresses weed emergence through shading and the release of allelopathic compounds with biofumigant properties that inhibit weed seed germination [21,24]. Following winter kill, daikon radish residues decompose quickly, releasing nutrients in a short window that can support early growth of subsequent cash crops. However, this rapid nitrogen release requires careful timing to avoid leaching losses [25,26].

Oat (Avena sativa L.), a cool-season cover crop from the Poaceae family, is known for its fast growth, high biomass production, and adaptability to diverse soil and climatic conditions [27]. Oats improve soil properties by increasing organic carbon content, enhancing enzymatic activity, promoting water infiltration, and reducing bulk density [28,29,30]. Their fibrous root system stabilizes soil particles and enhances soil structure [28]. Oats also act as nutrient-contributing catch crops, particularly for nitrogen, helping to reduce leaching losses [31]. Their rapid canopy development and allelopathic effects contribute to weed suppression [32]. However, oat residues decompose more slowly, potentially delaying nitrogen release, and their dense biomass can pose challenges for incorporation. Effective management of oat intercropping requires attention to compatibility, seeding rates, and timing to avoid competition that may reduce biomass and overall benefits.

Despite the individual advantages of oats and daikon radish, the optimal planting ratio between the two for maximizing weed suppression and soil improvement remains poorly documented. The effectiveness of intercropping systems depends significantly on species ratios, which influence resource complementarity, competition dynamics, biomass production, soil enhancement, and weed control. We hypothesized that varying the planting ratios of oat and daikon radish in intercropping systems would differentially affect soil properties, weed suppression efficacy, and spinach (Spinacia oleracea L.) performance. Oats, with their rapid establishment, may dominate competitive interactions at higher ratios, leading to stronger weed suppression and reduced need for hand weeding. This could also minimize early competition between spinach and weeds, potentially increasing spinach yield. In contrast, daikon radish is expected to have a greater influence on soil properties due to its robust taproot and rapid residue decomposition. We anticipate that the soil-enhancing effects of daikon radish will be driven more by its decomposition characteristics, particularly the carbon-to-nitrogen (C:N) ratio, than by its total biomass.

This study addresses a key research gap by systematically evaluating how varying oat and daikon radish seedling ratios influence soil quality, weed pressure, and spinach productivity. Although the benefits of cover crops grown as monocultures or mixtures are well documented, the specific effects of different intercrop seeding ratios on soil properties, and their implications for weed dynamics and spinach production, remain largely unexplored. By integrating the functional traits of cover crops into precision intercropping strategies, this work advances sustainable spinach cultivation aimed at reducing labor-intensive weed management while improving soil health.

2. Materials and Methods

2.1. Experimental Site

A two-year field study was conducted at the Research Farm of Mohaghegh Ardabili University in Ardabil, Iran (38° 19′ N, 48° 20′ E), in 2020–2021 and 2021–2022 growing seasons. In both years, experiments were conducted in the same field and experimental plots.

Table 1. Baseline characteristics of the soil at the experimental site (0–15 cm depth).

Soil Texture	Sand	Silt	Clay	OC	CaCO3	N	P	K	EC	pH
	------ (%wt) ------			------ (%) ------			------ (mg/kg−1) -----		dS/m
loam	35	42	23	0.6	14.5	0.06	8.2	202	2.6	8

OC, Organic carbon; CaCO₃, Calcium carbonate; N, Nitrogen; P, Phosphorus; K, Potassium.

provides baseline information on select physical and chemical properties of the top 15 cm of soil, and Figure 1 presents climatic data for the two years.

2.2. Experimental Layout and Treatments

This experiment consisted of two parts. The first experiment was laid out as a randomized complete block design with three replications. Experimental plots were 3 m × 4 m and consisted of 15 rows. Cover crop treatments included oat (Avena sativa L.) and daikon radish (Raphanus sativus var. Longipinnatus), intercropped in various sowing ratios based on the recommended sowing rate of the monoculture of the two cover crops. The ratios included: 100:0, 90:10, 70:30, 50:50, 30:70, 10:90, and 0:100 Oat: Daikon radish (O:D), respectively, and no cover crops as a control (

Table 2. Seed ratios in monoculture and intercropping.

Seedling Ratio	Oat (g per Plot)	Daikon Radish (g per Plot)
Oat (O)	120	0
Daikon radish (D)	0	24
90:10 (O:D)	108	2.4
70:30 (O:D)	84	7.2
50:50 (O:D)	60	12
30:70 (O:D)	36	16.8
10:90 (O:D)	12	21.6
Control	–	–

). Seeds were obtained from Pakan Seed Institute, Isfahan, Iran, and manually sown on 26 August 2020, and 20 August 2021. Seeding rates were based on 100 kg ha⁻¹ oats and 20 kg ha⁻¹ daikon radish. Seed quantities were calculated based on the recommended seedling rates for the two cover crop species as monoculture, with intercropping ratios determined according to the proportional contribution of each species (Table 2). To maintain focus on the impact of cover crops on soil properties, no fertilizer was applied to the cover crop. Fertilization of cover crops is not a common practice. Its omission ensured the results specifically reflected the influence of cover crop monocultures and intercropping ratios. In both experimental years, three irrigation cycles were carried out until cooler temperatures and fall rainfall began (Figure 1). The first irrigation was applied immediately after planting, and the subsequent irrigations were completed in mid-September and mid-October. No pests or diseases were observed during the cover crop growing period.

In both years, the aboveground biomass of cover crops was harvested 45 days after planting, before winter-kill. A 50 cm × 50 cm quadrat was used to harvest randomly selected areas from each plot. Harvested samples were dried in a forced-air oven at 70 °C to constant weight. The mean weight of three samples from each plot was used as the basis for calculating cover crop biomass per square meter. The Land Equivalence Ratio index (LER) for various ratios of O:D was calculated according to Glaze-Corcoran et al. [33] (Equation (1)).

$$\mathrm{LER}=\left({\displaystyle \frac{\mathrm{yab}}{\mathrm{yaa}}}+{\displaystyle \frac{\mathrm{yba}}{\mathrm{ybb}}}\right)$$

(1)

where a and b represent oats and daikon radish, respectively. Also, yab and yba denote biomass a and b in intercropping, and yaa and ybb denote biomass of species a and b in monoculture, respectively.

Selected soil properties within the 0–15 cm depth were measured on 17 and 18 March 2021 and 2022, respectively. The main reason for selecting the top 15 cm of soil was primarily due to the relatively shallow rooting depth of spinach that was planted following cover crop termination. From each experimental plot, three random soil cores were collected using soil augers and then combined to form a composite sample. All samples were sieved (0.5 mm) to remove plant residues.

Subsamples for microbial population and enzyme activity analyses were stored at −70 °C [34]. Soil organic carbon (SOC) and soil organic carbon stock (SOCS) were measured using the Walkley and Black method [35] (Equation (2)) and following established procedures for calculating carbon stocks at the landscape level [36] (Equation (3)). The soil microbial population was assessed via the most probable number method Ball [37]. Earthworm populations and water infiltration time were measured following the methods suggested by Moebius-Clune et al. [38]. Earthworm counts were performed at midday within a 30 × 30 × 30 cm³ (27,000 cubic cm⁻³) area at the center of each experimental plot. The soil moisture percentage was determined with the Klute [39] method (Equation (4)). Soil bulk density was calculated using the Dane and Topp [40] method (Equation (5)), and soil porosity percentage was assessed using the Bunzl et al. [41] method (Equation (6)). Enzymatic activities, including dehydrogenase (Tetrazolium salts (TTC) solution) [42], β-glucosidase (p-nitrophenyl-β-d-glucopyranoside (p-NG) substrate) [43], alkaline phosphatases (p-nitrophenyl phosphate (p-NPP) substrate) [44], and urease (urea substrate) [45], were analyzed across all treatments as biological indicators. Total N was measured using the Kjeldahl method [46]. Carbon was measured by dry combustion (LECO Carbon analyzer, LECO Corporation, St. Joseph, MI, USA).

$$\mathrm{SOC}={\displaystyle \frac{\mathrm{m} \times 0.39 \times (\mathrm{v}1 - \mathrm{v}2)}{\mathrm{s}}} \times 100$$

(2)

where m is the normality of Ferro ammonium sulfate based on equivalents per liter, v₁ and v₂ are the volumes of Ferro ammonium sulfate (mL) used for the control and cover crops, and s is air-dry weight (grams) of soil.

$$\mathrm{SOCS}=\mathrm{SOC}\left(\%\right) \times \mathrm{BD}\left(\mathrm{g} {\mathrm{cm}}^{-3}\right) \times \mathrm{soil} \mathrm{depth}\left(\mathrm{cm}\right) \times 10000$$

(3)

$$\mathrm{SM}={\displaystyle \frac{\mathrm{wet} \mathrm{soil} \mathrm{weight} \left(\mathrm{g}\right) - \mathrm{dry} \mathrm{soil} \mathrm{weight} \left(\mathrm{g}\right)}{\mathrm{dry} \mathrm{soil} \mathrm{weight} \left(\mathrm{g}\right)}} \times 100$$

(4)

$$\mathrm{BD}={\displaystyle \frac{\mathrm{wsd}}{\mathrm{v}}}$$

(5)

where BD is the bulk density, wsd is the soil dry weight, and v is the cylinder volume.

$$\mathrm{SPP}=\left[1 - \left({\displaystyle \frac{\mathrm{BD}}{2.65}}\right)\right]$$

(6)

The second experiment, which followed cover crop termination, was laid out as a factorial randomized complete block design with three replications. The treatments included cover crop residues left at various intercropping ratios, and two weeding strategies, including no weeding and hand weeding. An early maturity spinach (Spinach oleracea L.) seed, obtained from Sepahan Royesh Company, Isfahan Iran. Prior to planting, a germination test was conducted to ensure the viability of spinach seeds, and the results showed a 98% germination rate.

Spinach seeds were manually sown as no-till into cover crop residues on 19 and 20 March in 2021 and 2022, respectively. Seeds were planted 1.5 cm deep, 5 cm intra-row, and 20 cm inter-row spacing. In both years, the first irrigation was applied immediately after sowing. During the 2020–2021 season, irrigation was carried out every seven days for a total of eight applications due to insufficient precipitation (Figure 1). In contrast, during 2021–2022, significant rainfall in March and April reduced the number of irrigations to four. Hand-weeding treatment was held two times after spinach emergence (5 and 7 April 2021, and 2022, respectively) and continued two more times until the final harvest. The supplement hand weeding was held on 19 April and 3 May 2021 and 23 April and 7 May 2022. No pest or diseases incident was observed, and therefore, no control measures were implemented. Similarly, no fertilizer was applied during spinach growth to maintain focus on the impact of cover crops on spinach growth. Spinach was harvested at 3 cm above the soil surface on 18 and 24 May 2021 and 2022, respectively. Fresh weight was measured using a digital scale (A & D Company Limited, Tokyo, Japan; model GF-203awp; readability 0.001 g) and used to calculate fresh yield, expressed as g m⁻². Weed biomass was measured at each hand weeding using a 50 × 50 cm² quadrat. The dominant species (Chenopodium album, Anchusa azure, and Fumaria officinalis), were separated, dried in a forced-air oven at 70 °C to constant weight, and weighed separately.

2.3. Statistical Analyses

The dataset was analyzed using the PROC ANOVA procedure in SAS statistical software version 9.1.4 (SAS, The SAS Institute, Cary, NC, USA). The normality of the data distribution was evaluated with the Kolmogorov–Smirnov Test. When the treatment effect was significant based on the F-test, the least significant difference (LSD) was used at 0.05 for mean separation. Relationships among traits were assessed using Pearson’s correlation coefficient, implemented through the R corrplot package in RStudio Version 2025.09.0+387.

3. Results

3.1. Cover Crops Biomass, Carbon-to-Nitrogen Ratio (C:N), and Land Equivalence Ratio (LER)

There was a highly significant difference (p ≤ 0.01) in cover crop biomass between the two years of the experiment. The results showed that the effect of year on cover crop biomass production was highly significant (p ≤ 0.01;

Table 3. Cover crop ratio influence on biomass, LER, carbon and nitrogen content, and carbon-to-nitrogen ratio in both years.

Treatments		Total Cover Crops (g m−2)	Land Equivalence Ratio (LER)	Carbon-to-Nitrogen (C:N)
Years	2020–2021	242.7 ± 98.3 b	0.95 ± 0.08 a	19.1 ± 2.4 b
	2021–2022	264.5 ± 105.3 a	0.99 ± 0.05 a	20.2 ± 2.1 a
	LSD5%	9.0	0.04	0.9
Cover crops ratio	Oat (O)	338.7 ± 25.5 a	–	23.0 ± 1.4 a
	Daikon radish (D)	256.1 ± 10.4 e	–	19.1 ± 1.4 c
	90:10 (O:D)	312.6 ± 16.3 b	0.95 ± 0.07 b	21.2 ± 1.9 b
	70:30 (O:D)	292.7 ± 17.0 c	0.93 ± 0.03 b	19.8 ± 1.0 bc
	50:50 (O:D)	281.6 ± 16.9 cd	0.95 ± 0.04 b	19.5 ± 1.5 bc
	30:70 (O:D)	272.4 ± 22.7 de	0.97 ± 0.05 ab	18.2 ± 1.7 cd
	10:90 (O:D)	274.8 ± 26.2 cd	1.03 ± 0.1 a	16.7 ± 0.7 d
	Control	0.0 ± 0.0 f	–	–
	LSD5%	18.0	0.06	1.7
F Value	Year (Y)	5682.4 **	0.011 ns	13.3 *
	Cover crops (Cc)	67,021.0 **	0.010 *	24.8 **
	Y × Cc	228.3 ns	0.001 ns	0.5 ns
	CV (%)	6.0	5.6	7.3

ns—non-significant; *—significant at 0.05 level; **—highly significant at 0.01 level 1%. Values are means ± standard error, and columns with different letters are significantly different using the least significant difference (LSD) test (LSD; a = 0.05).

). Reducing the oat-to-daikon radish (O:D) seeding ratio led to decreased overall biomass production (Figure 2). However, oats consistently outyielded daikon radish in biomass under both monoculture and intercropping systems (

Table A1. Oat and Daikon radish ratio influence on biomass, and carbon and nitrogen content in both years.

Treatments		Oat (g m−2)	Daikon Radish (g m−2)	Carbon (mg g−1 Dry Matter)	Nitrogen (mg g−1 Dry Matter)
Years	2020–2021	135.5 ± 121.5 b	107.2 ± 96.6 b	399.9 ± 12.8 b	21.1 ± 2.3 a
	2021–2022	149.5 ± 128.2 a	117.9 ± 101.9 a	412.5 ± 18.5 a	20.5 ± 1.7 a
	LSD5%	5.9	5.8	3.6	1.0
Cover crops ratio	Oat (O)	338.7 ± 25.5 a	0.0 ± 0.0 g	421.8 ± 8.4 a	18.3 ± 1.0 d
	Daikon radish (D)	0.0 ± 0.0 g	256.1 ± 10.4 a	387.1 ± 8.0 d	20.2 ± 1.4 bcd
	90:10 (O:D)	282.3 ± 15.0 b	30.2 ± 3.0 f	419.0 ± 11.3 a	19.8 ± 1.8 cd
	70:30 (O:D)	222.6 ± 7.6 c	70.1 ± 10.8 e	419.5 ± 13.5 a	21.1 ± 1.1 bc
	50:50 (O:D)	156.0 ± 9.4 d	125.6 ± 8.7 d	411.6 ± 12.5 b	21.1 ± 1.7 bc
	30:70 (O:D)	91.1 ± 10.8 e	181.3 ± 13.2 c	395.8 ± 6.2 c	21.8 ± 2.1 ab
	10:90 (O:D)	37.7 ± 2.4 f	237.1 ± 25.0 b	388.8 ± 8.1 d	23.3 ± 1.3 a
	Control	0.0 ± 0.0 g	0.0 ± 0.0 g	–	–
	LSD5%	11.8	11.6	6.8	1.9
F Value	Year (Y)	1455.6 **	1385.9 **	1672.0 **	4.5 ns
	Cover crops (Cc)	101915.4 **	64240.5 **	1386.3 **	14.8 **
	Y × Cc	130.2 ns	117.3 ns	162.8 **	1.2 ns
	CV (%)	7.0	8.7	1.4	7.6

ns—non-significant; **—highly significant at 0.01 level 1%. Values are means ± standard error, and columns with different letters are significantly different using the least significant difference (LSD) test (LSD; a = 0.05).

). As shown in Table 3, oat monoculture yielded the highest total cover crop biomass (338.7 ± 25.5 g m⁻²), whereas daikon radish monoculture yielded the lowest (256.1 ± 10.4 g m⁻²). Overall, total cover crop biomass was 8.2% greater in the second year compared to the first (Table 3). Cover crop treatments significantly affected the land equivalent ratio (LER) (p ≤ 0.05), with the highest LER (1.03 ± 0.1) calculated at the 10:90 (O:D) ratio (Table 3, Appendix A). No significant year-to-year difference was found in LER values (Table 3). The effects of year and cover crops on the carbon-to-nitrogen ratio (C:N) were significant (p ≤ 0.05) and highly significant (p ≤ 0.01), respectively. Among all treatments, oats had the highest C:N ratio (23.0 ± 1.4), while differences among other cover crop ratios were not statistically significant. The C:N ratio was 5.44% higher in the second year than in the first year (Table 3). The interaction between year and cover crops was highly significant (p ≤ 0.01) for carbon content (C). Oat monoculture and oat-to-daikon radish intercropping ratios of 90:10 and 70:30 (O:D) exhibited the highest C content whereas daikon radish monoculture and the 10:90 (O:D) intercropping ratio had the lowest. Nitrogen content (N) was highly significantly affected by cover crop (p ≤ 0.01), but no significant difference was observed between monoculture and intercropping systems (Table A1).

3.2. Impact of Cover Crops on Soil Properties

As shown in

Table 4. Impact of cover crops on soil organic carbon, soil organic carbon stock, microbial populations, and earthworm populations.

Treatments		Soil Organic Carbon (%)	Soil Organic Carbon Stock (kg ha−1)	Soil Microbial Population (Most Probable Number per g−1 Soil)	Earthworm Populations (Number per Cubic−3)
Years	2020–2021	0.82 ± 0.1 b	149.5 ± 11.6 a	9.6 × 10−4 ± 2.1 × 10−4 b	2.16 ± 0.7 b
	2021–2022	0.84 ± 0.1 a	150.9 ± 10.6 a	10.3 × 10−4 ± 2.0 × 10−4 a	2.45 ± 0.7 a
	LSD5%	0.01	2.9	1.8 × 10−3	0.2
Cover crops ratio	Oat (O)	0.80 ± 0.018 d	161.2 ± 5.5 a	8.9 × 10−4 ± 3.5 × 10−3 e	2.00 ± 0.00 cd
	Daikon radish (D)	0.87 ± 0.015 c	133.0 ± 1.3 c	10.5 × 10−4 ± 4.7 × 10−3 d	2.66 ± 0.57 abc
	90:10 (O:D)	0.82 ± 0.011 d	159.9 ± 1.9 a	8.4 × 10−4 ± 4.2 × 10−3 f	2.33 ± 0.57 bc
	70:30 (O:D)	0.78 ± 0.024 e	145.0 ± 6.9 b	7.6 × 10−4 ± 1.0 × 10−4 f	2.00 ± 1.00 cd
	50:50 (O:D)	0.88 ± 0.022 c	156.4 ± 7.8 a	11.8 × 10−4 ± 4.8 × 10−3 c	3.00 ± 0.00 ab
	30:70 (O:D)	0.96 ± 0.016 a	159.4 ± 2.9 a	12.3 × 10−4 ± 4.0 × 10−3 b	3.33 ± 0.57 a
	10:90 (O:D)	0.94 ± 0.021 b	149.0 ± 1.7 b	12.8 × 10−4 ± 4.8 × 10−3 a	3.00 ± 0.00 ab
	Control	0.62 ± 0.014 f	137.7 ± 3.9 c	7.4 × 10−4 ± 3.1 × 10−3 g	1.33 ± 0.57 d
	LSD5%	0.01	5.9	3.7 × 10−3	0.8
F Value	Year (Y)	0.006 **	25.36 ns	5.64 × 10−8 **	1.02 *
	Cover crops (Cc)	0.072 **	700.89 **	2.78 × 10−9 **	2.35 **
	Y × Cc	0.0001 ns	8.08 ns	3.76 × 10−8 *	0.11 ns
	CV (%)	1.7	3.3	3.2	20.5

ns—non-significant; *—significant at 0.05 level; **—highly significant at 0.01 level 1%. Values are means ± standard error, and columns with different letters are significantly different using the least significant difference (LSD) test (LSD; a = 0.05).

,

Table 5. Impact of cover crops on dehydrogenase, β-glucosidase, Urease, and Alkaline phosphatase soil enzymes.

Treatments		Dehydrogenase Enzyme (µg Triphenylformazan g Soil−1 16 h−1)	β-Glucosidase Enzyme (µg p-Nitrophenol g Soil−1 h−1)	Urease Enzyme (µg N-NH4 g Soil−1 2 h−1)	Alkaline Phosphatase Enzyme (µg p-Nitrophenol g Soil−1 h−1)
Years	2020–2021	1351 ± 136.3 a	34.07 ± 2.0 b	827.8 ± 69.6 a	31.3 ± 4.0 b
	2021–2022	1351 ± 128.7 a	36.95 ± 2.6 a	836.5 ± 66.3 a	34.2 ± 4.0 a
	LSD5%	25.1	0.5	11.7	0.5
Cover crops ratio	Oat (O)	1217 ± 2.5 d	34.7 ± 0.6 c	841 ± 22.5 c	29.4 ± 0.8 d
	Daikon radish (D)	1427 ± 3.7 b	35.3 ± 1.1 c	883 ± 14.0 ab	33.72 ± 0.4 c
	90:10 (O:D)	1250 ± 4.1 cd	37.6 ± 0.7 b	846 ± 12.5 c	34.64 ± 0.7 c
	70:30 (O:D)	1341 ± 15.1 bc	38.4 ± 0.7 b	760 ± 36.0 d	36.21 ± 0.8 b
	50:50 (O:D)	1420 ± 16.4 b	38.3 ± 2.1 b	855 ± 16.0 bc	38.02 ± 0.1 a
	30:70 (O:D)	1533 ± 4.5 a	40.5 ± 1.2 a	907 ± 11.0 a	38.10 ± 1.2 a
	10:90 (O:D)	1438 ± 2.5 ab	38.1 ± 1.2 b	886 ± 9.2 ab	37.16 ± 0.6 ab
	Control	1183 ± 13.5 d	32.5 ± 0.5 d	711 ± 11.5 e	26.59 ± 0.9 e
	LSD5%	104.7	1.8	32.5	1.4
F Value	Year (Y)	1.68 ns	99.76 **	910.02 ns	100.94 **
	Cover crops (Cc)	102,096.66 **	32.12 **	28,525.59 **	104.18 **
	Y × Cc	2035.16 ns	0.65 ns	30.40 ns	0.96 ns
	CV (%)	3.1	2.5	2.3	2.6

ns—non-significant; **—highly significant at 0.01 level 1%. Values are means ± standard error, and columns with different letters are significantly different using the least significant difference (LSD) test (LSD; a = 0.05).

and

Table 6. Impact of cover crops on soil moisture, bulk density, soil porosity, and water infiltration time.

Treatments		Soil Moisture (%)	Bulk Density (g cm−3)	Soil Porosity (%)	Water Infiltration Time (s)
Years	2020–2021	17.6 ± 2.4 b	1.2 ± 0.1 a	53.8 ± 5.6 b	6.3 ± 1.1 a
	2021–2022	19.0 ± 3.0 a	1.2 ± 0.1 b	54.6 ± 5.8 b	6.0 ± 1.1 b
	LSD5%	0.6	0.01	0.6	0.2
Cover crops ratio	Oat (O)	21.0 ± 0.3 abc	1.3 ± 0.03 b	50.0 ± 1.1 e	7.0 ± 0.1 b
	Daikon radish (D)	18.0 ± 1.7 de	1.0 ± 0.01 f	61.8 ± 0.3 a	4.6 ± 0.5 d
	90:10 (O:D)	22.7 ± 0.8 a	1.2 ± 0.01 b	51.6 ± 0.3 e	6.9 ± 0.3 b
	70:30 (O:D)	21.5 ± 1.3 ab	1.2 ± 0.03 c	53.8 ± 1.1 d	6.0 ± 0.02 c
	50:50 (O:D)	19.6 ± 1.0 bcd	1.1 ± 0.04 d	55.9 ± 1.5 c	5.8 ± 0.09 c
	30:70 (O:D)	19.1 ± 1.1 cde	1.0 ± 0.01 e	58.8 ± 0.3 b	5.2 ± 0.1 d
	10:90 (O:D)	17.3 ± 1.1 e	1.0 ± 0.005 f	60.8 ± 0.2 a	4.8 ± 0.5 d
	Control	13.1 ± 1.0 f	1.4 ± 0.04 a	43.8 ± 1.5 f	7.9 ± 0.07 a
	LSD5%	2.1	0.04	1.8	0.5
F Value	Year (Y)	24.96 **	0.005 *	7.12 *	0.73 *
	Cover crops (Cc)	45.47 **	0.148 **	211.44 **	7.80 **
	Y × Cc	0.64 ns	0.0002 ns	0.38 ns	0.06 ns
	CV (%)	5.5	2.4	2.0	5.9

ns—non-significant; *—significant at 0.05 level; **—highly significant at 0.01 level 1%. Values are means ± standard error, and columns with different letters are significantly different using the least significant difference (LSD) test (LSD; a = 0.05).

, cover crops had a highly significant effect on soil properties in both monoculture and intercropping systems (p ≤ 0.01). Year effects were also highly significant (p ≤ 0.01) for soil organic carbon (SOC), soil microbial population, β-glucosidase enzyme, and alkaline phosphatase enzyme. In contrast, the effect of year on earthworm population, bulk density, soil porosity, and water infiltration time was significant (p ≤ 0.05). No significant year effect on soil organic carbon stock (SOCS) and dehydrogenase enzyme was observed. The interaction effect of year and cover crops was highly significant only for the soil microbial population (p ≤ 0.01).

3.2.1. Soil Organic Carbon (SOC) and Soil Organic Carbon Stock (SOCS)

The highest SOC (0.96 ± 0.016%) was recorded in the 30:70 (O:D) intercropping, while the control (no cover crops) had the lowest (0.62 ± 0.014%). As shown in Table 4, daikon radish monoculture contributed 8.04% more SOC than oat monoculture. Increasing the proportion of daikon radish in the intercropping further boosted SOC beyond that of daikon radish monoculture, with 30:70 and 10:90 (O:D) intercropping ratios increasing SOC by 9.3% and 7.4%, respectively (Table 4). SOCS followed a similar trend. The highest SOCS values were found in oat monoculture and intercropping systems with 30:70, 90:10, and 50:50 (O:D) ratios, reaching 161.2 ± 5.5, 159.4 ± 2.9, 159.9 ± 1.9, and 156.4 ± 7.8 kg ha⁻¹, respectively. In contrast, the control and daikon radish monoculture recorded the lowest SOCS (137.7 ± 3.9 and 133.0 ± 1.3 kg ha⁻¹). SOCS increased by 0.92% in the second year (Table 4). Although oat monoculture produced the highest biomass (Table 3), SOC levels did not increase accordingly. Instead, intercropping ratios with lower overall biomass than oat monoculture showed the highest SOC content. The pattern may be explained by the influence of the C:N ratio on the decomposition dynamics of oat and daikon radish residues. Our findings indicated that intercropping ratios exhibited lower C:N ratios than their monocultures counterparts (Table 3), suggesting a faster decomposition rate under the intercropped treatments. As demonstrated in Figure 3, SOC and SOCS were both highly significantly correlated with C:N ratio (r = 0.602 ** and r = 0.465 **, respectively).

3.2.2. Soil Microbial Population

The soil microbial population in oat monoculture (8.9 × 10⁻⁴ ± 3.5 × 10⁻³ most probable number per g⁻¹ soil) was 1.16% lower than in daikon radish monoculture (10.5 × 10⁻⁴ ± 4.7 × 10⁻³ most probable number per g⁻¹ soil) (Table 4). The highest soil microbial population (12.8 × 10⁻⁴ ± 4.8 × 10⁻³ most probable number per g⁻¹ soil) was recorded in the 10:90 (O:D) intercropping, while the control treatment (no cover crops) had the lowest value (7.4 × 10⁻⁴ ± 3.1 × 10⁻³ most probable number per g⁻¹ soil). Other intercropping ratios, such as 30:70 and 50:50 (O:D), also maintained high soil microbial levels (12.3 × 10⁻⁴ ± 4.0 × 10⁻³ most probable number per g⁻¹ soil and 11.8 × 10⁻⁴ ± 4.8 × 10⁻³ most probable number per g⁻¹ soil, respectively). Overall, microbial populations increased by 0.49% in the second year (Table 4). The findings indicated that decreasing the proportion of daikon radish seeds reduced the soil microbial population. However, even small amounts of oat biomass appeared critical for sustaining a robust microbial community, as oats contributed significantly to C content (421.8 ± 8.4 mg g⁻¹ dry matter) (Table A1). More than total cover crop biomass, the balance of C:N ratio, and C and N contents in the 10:90 (O:D) intercropping drives the abundance of the soil microbial population. Specifically, the 10:90 (O:D) ratio had a higher N content (23.3 ± 1.3 mg g⁻¹ dry matter) than to the 30:70 (O:D) ratio (21.8 ± 2.1 mg g⁻¹ dry matter) whereas, the 30:70 (O:D) ratio had a greater C content (395.8 ± 6.2 mg g⁻¹ dry matter) than the 10:90 (O:D) ratio (388.8 ± 8.1 mg g⁻¹ dry matter) (Table A1). Furthermore, soil microbial population was significantly and positively correlated (r = 0.523 **) with N content (Figure 3).

3.2.3. Earthworm Populations

Cover crops increased earthworm populations, and no significant differences were observed between monoculture and intercropping treatments. Earthworm populations were higher in the second year 11.8%, (2.45 ± 0.77 number per cubic⁻³), compared to the first year (Table 4). As expected, the control (no cover crops) had the lowest earthworm count (1.33 ± 0.57 number per cubic⁻³). Additionally, ratios with elevated soil microbial populations, such as 10:90, 30:70, and 50:50 O:D, also exhibited higher earthworm population, although the differences were not statistically significant.

3.2.4. Dehydrogenase, β-Glucosidase, Urease, and Alkaline Phosphatase Enzyme Activity

Dehydrogenase enzyme activity did not differ significantly among monocultures and intercropping ratios, nor between years when comparing yearly means. However, dehydrogenase activity peaked in the 30:70 and 10:90 (O:D) intercropping ratios (1533 ± 4.58 and 1438 ± 2.51 µg triphenylformazan g soil⁻¹ 16 h⁻¹, respectively), while the control and oat monoculture showed the lowest activity (1183 ± 13.52 and 1217 ± 2.51 µg triphenylformazan g soil⁻¹ 16 h⁻¹, respectively) (Table 5).

β-glucosidase enzyme activity was 7.8% higher in the second year than in the first year (Table 5). β-glucosidase activity was highest in the 30:70 (O:D) system (40.56 ± 19.88 µg p-nitrophenol g soil⁻¹ h⁻¹), significantly higher than the control (32.50 ± 0.50 µg p-nitrophenol g soil⁻¹ h⁻¹), with 19.8% increase (Table 5). Soil organic carbon and soil microbial population were higher in the 30:70 (O:D) ratio than in the intercropping treatments. Those factors appeared to contribute to the increased activity of the β-glucosidase enzyme (Figure 3).

Urease activity did not differ significantly among intercropping ratios or between monocultures but was lowest in the control (711 ± 11.53 µg N-NH₄ g soil⁻¹ 2 h⁻¹). A modest 1.04% increase was recorded in the second year (Table 5). Alkaline phosphatase activity increased with higher proportions of daikon radish in intercropping, reaching 38.10 ± 1.21, 38.02 ± 0.18, 37.16 ± 0.68 µg p-nitrophenol g soil⁻¹ h⁻¹ in the 30:70, 50:50, and 10:90 (O:D) treatments, respectively, representing 26% to 30% higher activity than the control. Alkaline phosphatase activity also showed an 8.47% increase in the second year (Table 5). Even a slight increase in soil enzyme activities may result from the direct influence of the C:N ratio on decomposition, subsequently enhancing SOC and soil microbial population.

3.2.5. Soil Moisture

There were no significant differences in soil moisture percentage among the monoculture and intercropping treatments with varying oats and daikon radish ratios (Table 6). However, the ratios of 90:10 and 70:30 (O:D) had the highest soil moisture percentage, with values of 22.78 ± 0.84% and 21.55 ± 1.39%, respectively. In contrast, the control plot had the lowest soil moisture percentage (13.16 ± 1.00%). Comparison across the two experimental years indicated a 7.55% increase in soil moisture in the second year (Table 6). Oat monoculture and intercropping with high oat ratios (90:10 and 70:30 O:D) appeared to promote slightly higher soil moisture, potentially due to enhanced soil surface-coverage from oat residues.

3.2.6. Bulk Density and Soil Porosity

The lowest soil bulk densities were recorded in the daikon radish monoculture (1.01 ± 0.01 g cm⁻³) and the 10:90 (O:D) intercropping treatment (1.03 ± 0.005 g cm⁻³), reflecting reductions of 31.7% and 30.4%, respectively, compared to the control (Table 6). In contrast, the oat monoculture and the 90:10 ratio (O:D) intercropping showed higher bulk densities (1.32 ± 0.03 and 1.28 ± 0.01 g cm⁻³, respectively), second only to the control. These findings indicate the beneficial effect of increasing the proportion of daikon radish in reducing compaction, possibly due to its thick roots and low C:N ratio (Table 3). Additionally, soil bulk density decreased by 1.63% in the second year. Correspondingly, soil porosity increased as bulk density declined, with the highest soil porosity observed in daikon radish monoculture and 10:90 (O:D) intercropping (61.88 ± 0.37 and 60.88 ± 0.21%, respectively), an increase of 1.40% in the second year (Table 6).

3.2.7. Water Infiltration Time

Cover crops had a highly significant effect on water infiltration time. Daikon radish monoculture demonstrated a faster infiltration rate (4.6 ± 0.5 s), compared to oat monoculture (7.0 ± 0.1 s). As shown in Table 6, daikon radish monoculture, along with the 30:70 and 10:90 (O:D) intercropping treatments, resulted in the shortest infiltration times (5.2 ± 0.1 s, and 4.8 ± 0.5 s, respectively). In contrast, the control had the slowest infiltration (7.9 ± 0.07 s). Overall, cover crop treatments led to a 4.08% reduction in infiltration time in the second year (Table 6). Compared to daikon radish monoculture, 30:70 and 10:90 (O:D) intercropping increased water infiltration time by 11.5% and 4.1%, respectively, potentially due to pore reduction caused by the daikon radish and added effect of oat roots. However, oat roots alone, or combined with a low daikon radish seed ratio, were insufficient to reduce water infiltration time substantially. Specifically, the 90:10 and 70:30 (O:D) intercropping ratios decreased by only 1.4% and 14.2%, respectively, compared to oat monoculture. These findings suggested that daikon radish, even at low ratios, plays an important role in reducing water infiltration time.

3.3. Impact of Cover Crops on Weed Population and Biomass and Spinach Yield

3.3.1. Weed Population and Biomass

The findings revealed that year, cover crops, hand weeding, and their interactions had a highly significant effect on weed population (p ≤ 0.01;

Table 7. The impact of cover crops and hand weeding on dominant weed population in both years.

Treatments		C. album (Plants m−2)	A. azurea (Plants m−2)	F. officinalis (Plants m−2)	Total Weeds (Plants m−2)
Years	2020–2021	14.5 ± 3.9 b	13.8 ± 4.6 b	12.1 ± 3.6 b	40.5 ± 11.4 b
	2021–2022	17.8 ± 4.2 a	19.8 ± 4.7 a	17.0 ± 4.5 a	54.7 ± 13.1 a
	LSD5%	0.4	0.6	0.5	1.1
Cover crops ratio × Weed strategy	Cover crops × Hand weeding
	Oat (O)	11.3 ± 1.7 hg	11.0 ± 2.3 h	8.8 ± 3.3 g	31.1 ± 7.0 i
	Daikon radish (D)	14.6 ± 1.0 f	14.0 ± 2.3 f	11.1 ± 2.7 f	39.8 ± 5.5 g
	90:10 (O:D)	12.3 ± 1.0 g	12.1 ± 2.9 gh	9.0 ± 2.3 g	33.5 ± 5.9 i
	70:30 (O:D)	10.5 ± 1.8 h	14.0 ± 2.3 f	12.1 ± 2.1 ef	36.6 ± 5.8 h
	50:50 (O:D)	14.1 ± 1.4 f	14.1 ± 3.2 f	12.0 ± 3.2 ef	40.3 ± 7.6 g
	30:70 (O:D)	16.1 ± 1.4 e	17.0 ± 3.7 e	13.0 ± 2.4 de	46.1 ± 7.3 f
	10:90 (O:D)	17.0 ± 2.3 de	17.6 ± 4.1 de	15.5 ± 1.8 c	50.1 ± 8.2 de
	Control	21.0 ± 2.3 b	23.6 ± 4.1 b	16.3 ± 3.1 c	61.0 ± 9.2 b
	Cover crops × No Hand weeding
	Oat (O)	14.0 ± 2.0 f	13.5 ± 2.8 fg	13.0 ± 2.3 de	40.5 ± 6.9 g
	Daikon radish (D)	17.3 ± 1.6 cd	15.0 ± 4.9 f	15.1 ± 1.9 c	47.5 ± 7.9 ef
	90:10 (O:D)	14.0 ± 2.3 f	14.1 ± 3.1 f	13.6 ± 1.6 d	41.8 ± 6.7 g
	70:30 (O:D)	14.6 ± 2.1 f	17.5 ± 3.5 de	15.1 ± 3.3 c	47.3 ± 8.4 f
	50:50 (O:D)	16.8 ± 2.6 de	18.0 ± 3.7 de	16.0 ± 3.4 c	50.8 ± 9.5 d
	30:70 (O:D)	18.3 ± 3.1 c	19.0 ± 5.5 cd	18.5 ± 3.9 b	55.8 ± 12.3 c
	10:90 (O:D)	20.0 ± 4.4 b	20.3 ± 5.2 c	19.5 ± 5.0 b	59.8 ± 14.4 b
	Control	26.5 ± 1.0 a	28.8 ± 1.7 a	24.3 ± 4.3 a	79.6 ± 6.7 a
	LSD5%	1.1	1.5	1.3	2.6
F Value	Year (Y)	256.76 **	864.00 **	580.16 **	4830.84 **
	Cover crops (Cc)	169.17 **	233.73 **	120.21 **	1493.37 **
	Y × Cc	4.51 *	7.38 *	3.80 ns	31.08 **
	Weed strategy (W)	225.09 **	192.66 **	522.66 **	2677.59 **
	Cc × W	4.45 *	5.04 *	6.92 *	35.21 **
	CV (%)	7.3	8.9	9.7	6.0

ns—non-significant; *—significant at 0.05 level; **—highly significant at 0.01 level 1%. Values are means ± standard error, and columns with different letters are significantly different using the least significant difference (LSD) test (LSD; a = 0.05).

). Year and cover crops also had a highly significant effect on weed biomass (p ≤ 0.01), while the interaction between year and cover crops was significant (p ≤ 0.05). In contrast, the interaction between cover crop and weeding strategy did not significantly affect weed biomass (

Table 8. The impact of cover crops and hand weeding on dominant weed biomass in both years.

Treatments		C. album (g m−2)	A. azurea (g m−2)	F. officinalis (g m−2)	Total Weeds (g m−2)
Years	2020–2021	4.3 ± 1.7 b	4.8 ± 1.4 b	5.4 ± 2.3 b	14.7 ± 4.9 b
	2021–2022	5.6 ± 2.1 a	6.2 ± 0.9 a	6.6 ± 2.6 a	18.6 ± 6.3 a
	LSD5%	0.4	0.3	0.3	0.7
Cover crops ratio	Oat (O)	3.2 ± 1.0 d	4.4 ± 1.0 c	4.6 ± 1.4 d	12.3 ± 2.9 f
	Daikon radish (D)	5.4 ± 1.3 b	5.8 ± 1.0 b	6.1 ± 0.7 b	17.4 ± 2.4 b
	90:10 (O:D)	3.9 ± 1.0 cd	4.6 ± 1.1 c	5.3 ± 1.1 bcd	14.0 ± 2.8 de
	70:30 (O:D)	4.4 ± 1.0 c	4.3 ± 1.0 c	4.8 ± 0.8 d	13.6 ± 2.1 ef
	50:50 (O:D)	4.4 ± 1.1 c	5.0 ± 1.1 bc	4.9 ± 0.9 d	14.4 ± 2.3 de
	30:70 (O:D)	4.8 ± 1.6 cb	5.5 ± 1.3 b	5.1 ± 0.8 cd	15.4 ± 2.7 cd
	10:90 (O:D)	4.8 ± 0.9 cb	5.4 ± 1.1 b	5.7 ± 0.7 bc	16.0 ± 1.8 bc
	Control	8.8 ± 2.1 a	9.1 ± 1.9 a	11.9 ± 2.2 a	29.8 ± 5.5 a
	LSD5%	0.9	0.7	0.7	1.4
Weed strategy	Hand weeding	4.6 ± 1.9 b	5.1 ± 1.6 b	5.7 ± 2.3 b	15.5 ± 5.5 b
	No hand weeding	5.3 ± 2.1 a	5.9 ± 1.9 a	6.4 ± 2.6 a	17.7 ± 6.2 a
	LSD5%	0.4	0.3	0.3	0.7
F Value	Year (Y)	42.00 **	46.34 **	34.34 **	366.67 **
	Cover crops (Cc)	33.29 **	28.06 **	68.99 **	368.12 **
	Y × Cc	2.14 ns	1.09 ns	2.23 *	12.18 *
	Weed strategy (W)	12.68 *	16.91 **	9.74 *	116.55 **
	Cc × W	0.24 ns	0.75 ns	0.49 ns	3.54 ns
	CV (%)	23.1	17.0	16.0	10.8

ns—non-significant; *—significant at 0.05 level; **—highly significant at 0.01 level 1%. Values are means ± standard error, and columns with different letters are significantly different using the least significant difference (LSD) test (LSD; a = 0.05).

).

In both years, the dominant weed species were included lamb’s quarters (Chenopodium album), Italian bugloss (Anchusa azurea), and common fumitory (Fumaria officinalis) (Table 7 and Table 8).

The lowest total weed population was recorded in oats monoculture and the 90:10 (O:D) intercropping ratio with hand weeding (31.1 ± 7.0 plants m⁻² and 33.5 ± 5.9 plants m⁻²). Compared to the control with and without hand weeding, oats monoculture and the 90:10 (O:D) intercropping reduced weed populations by 49.0% and 60.9% and 45.0% and 57.9%, respectively (Table 7). Despite these reductions, weed populations increased in the second year by 25.9% (Table 7), and weed biomass increased by 20.9% compared to the first year (Table 8). The lowest total weed biomass (12.3 ± 2.9 g m⁻²) was recorded in the oat monoculture, showing a 58.7% reduction compared to the control (Table 8). Furthermore, hand weeding contributed to a 12.4% decrease in total weed biomass.

Species-specific population and biomass reduction were also observed (Table 7 and Table 8). The lowest weed populations of C. album (10.5 ± 1.8 plant m⁻² and 11.3 ± 1.7 plant m⁻²), A. azurea (11.0 ± 2.3 plant m⁻² and 12.1 ± 2.9 plant m⁻²), and F. officinalis (8.8 ± 3.3 Plant m⁻² and 9.0 ± 2.3 plant m⁻²) were recorded in the oat monoculture and the 90:10, and 70:30 (O:D) intercropping (Table 7), while control with and without hand weeding consistently had the highest weed population (Table 7). The mean results of the year effect demonstrated that the populations of C. album, A. azurea, and F. officinalis increased by 18.5%, 30.3%, and 28.8%, respectively, in the second year.

No significant differences in biomass of these three weed species were detected among the cover crop treatments, whereas the control plots showed the highest weed biomass. Hand weeding reduced the biomass of C. album, A. azurea, and F. officinalis by 13.2%, 13.5%, and 10.9%, respectively, compared to plots without hand weeding. Oat biomass was highest in intercropping ratios with greater oat seed proportions (Table 3 and Table A1). The observed reduction in weed population and biomass in oat monoculture and intercropping systems (e.g., 90:10 and 70:30 O:D) appears to be associated with higher cover crop biomass. Furthermore, hand weeding significantly contributed to suppressing dominant weed populations and biomass.

3.3.2. Spinach Yield

As shown in

Table 9. The impact of cover crops and weeding strategies on spinach yield.

F Value	Spinach Yield (g m−2)
Year (Y)	7341.77 **
Cover crops (Cc)	192,903.07 **
Y × Cc	2739.26 **
Weed strategy (W)	37,459.03 **
Cc × W	662.58 *
CV (%)	2.5

*—significant at 0.05 level; **—highly significant at 0.01 level 1%.

, year, cover crops, weed strategy, and their interaction (Y × Cc, and Cc × W) had a highly significant effect on spinach yield. The interaction between year and cover crops indicated that the highest spinach yield was obtained in the first year from oat monoculture (855.1 ± 23.8 g m⁻²), representing a 46.5% increase over the control (457.2 ± 57.0 g m⁻²). The lowest yields in both years were recorded in control plots (Figure 2a). Spinach yield in oat monoculture decreased by 5.7% in the second year, despite the highest cover crop biomass (Table 3), likely due to decreased weed pressure (Table 7 and Table 8). In the first year, spinach yield in the 90:10 (O:D) intercropping ratio did not differ significantly from oat monoculture. Similarly, in the second year, daikon radish monoculture yield was not significantly different from the 10:90 (O:D) intercropping ratio across both years (Figure 2a). Decreasing the oat seed ratio in intercropping reduced spinach yield across both years, likely due to lower weed suppression by oats, as suggested by weed survey data, demonstrating a stronger correlation of weed reduction with oat biomass than with daikon radish (Figure 3).

Regarding the interaction between cover crops and weeding practices, oat monoculture coupled with hand weeding yielded the highest spinach yield (842.9 ± 36.1 g m⁻²), a 40.2% increase over the hand-weeding control (503.6 ± 6.7 g m⁻²). Oat monoculture without hand weeding exhibited a slight 2.8% reduction compared to the hand-weeded treatment. The results indicated that oats could enhance spinach yield even without hand weeding, by effectively suppressing weeds.

The study’s findings indicated that no significant difference was observed between the 90:10 (O:D) intercropping ratio with hand weeding and oat monoculture without hand weeding (Figure 2b). This highlighted the strong weed-suppressive effect of oats on spinach yield. However, the higher C:N ratio of oats compared to daikon radish may have limited nutrient release to the spinach. Figure 2b illustrates that spinach yield in a daikon radish monoculture was 15.5% and 19.7% higher than the control with and without hand weeding, respectively, indicating that daikon radish in intercropping systems did not significantly improve spinach yield by reducing the C:N ratio. Therefore, overall, oats had a more significant impact than daikon radish on increasing spinach yield in intercropping systems through their effect on weed suppression.

3.4. Correlation

Pearson correlation analysis revealed a significant negative correlation between oat and daikon radish biomass (r = −0.604 **), reflecting the dominance of oats due to the higher proportion. Total cover crop biomass (CCs) was positively and significantly correlated with C content (r = 0.975 **), N content (r = 0.882 **), C:N ratio (r = 0.970 **), and LER index (r = 0.432 **). Additionally, CCs showed significant associations with multiple soil health indicators (Figure 3), including positive correlations with SOC (r = 0.647 **), SOCS (r = 0.550 **), soil microbial population (r = 0.296 *), earthworm population (r = 0.492 **), dehydrogenase enzyme (r = 0.351 *), β-glucosidase enzyme (r = 0.534 **), urease enzyme (r = 0.691 **), alkaline phosphatase enzyme (r = 0.602 **), soil moisture (r = 0.850 **), and soil porosity percentage (r = 0.495 **). Conversely, CCs were negatively correlated with bulk density (r = −0.495 **) and water infiltration time (r = −0.376 **). Similarly, the C:N ratio exhibited comparable correlations with soil properties, indicating its strong association with enhanced soil health. Cover crops also negatively correlated with weed population (r = −0.636 ** with hand weeding, r = −0.670 ** without hand weeding) and weed biomass (r = −0.819 ** with hand weeding, r = −0.850 ** without hand weeding). Positive correlations were observed between CCs and spinach yield, both with hand weeding (r = 0.699 **) and without hand weeding (r = 0.734 **) (Figure 3).

Spinach yield positively correlated with C:N ratio (r = 0.725 ** and r = 0.747 **, respectively), SOCS (r = 0.664 **), and soil microbial population (r = 0.835 **), reflecting the contribution of cover crop biomass. Despite these benefits, weed population (r = −0.715 ** and r = −0.672 ** for hand weeding and no hand weeding, respectively) and weed biomass (r = −0.685 ** and r = −0.652 ** for hand weeding and no hand weeding, respectively) demonstrated a negative correlation with spinach yield (Figure 3).

4. Discussion

4.1. Impact of Cover Crops on Soil Properties

Cover crops can enhance crop yield by improving physical, chemical, and biological soil properties, suppressing weeds, and cycling nutrients [47,48,49]. Our findings indicated that oats produced higher biomass when grown as a monoculture. The consistent dominance of oats in biomass production across monoculture and intercropping systems reflected their inherently vigorous growth habit, denser canopy, and higher seed sowing rates, which probably enhance resource capture above and belowground. We hypothesized that biomass dominance generally translates into higher residue input, soil surface cover, and potentially organic carbon contributions to the soil. In contrast, daikon radish produced considerably less biomass overall but had a distinct impact on residue quality by its lower C:N ratio. Numerous studies indicated that a low C:N ratio in plant tissue is a key factor in the rapid decomposition of cover crop residues [11,50]. While intercropping reduced total biomass as oat proportion declined, certain intercropping systems maintained near-equivalent productivity (e.g., 90:10 O:D ratio). The LER exceeding 1 at a 10:90 (O:D) ratio suggested some complementarity or facilitation between cover crop species at these proportions, allowing more efficient total resource use than monocultures. This facilitation could arise through reduced intra-specific competition, niche differentiation in root zones or nutrient uptake timing, and improvements in soil structure, enhancing resource availability. For instance, it has been reported that additive design intercropping (maize/mung bean and maize/soybean) has shown higher productivity than substitutive design, as evidenced by significantly higher LER values [51].

The C:N ratio differences between oats and daikon radish residues are crucial in explaining the SOC dynamics. Oat residues with a higher C:N ratio (approximately 23) tend to decompose more slowly, resulting in a longer-lasting surface cover and slower nutrient release [52]. This can reduce nutrient availability to the succeeding crop (spinach) in the short term but enhance longer-term SOC formation and stock (Table 4). In contrast, daikon radish residues with lower C:N ratios (around 16–19) probably decompose more rapidly, favoring quicker nutrient turnover and microbial mineralization processes [11].

Interestingly, intercropping combinations with lower overall biomass and lower C:N ratios, such as 70:30, 50:50, 30:70, and 10:90 (O:D) ratios, resulted in higher levels of SOC and SOCS (Table 3 and Table 4). This indicates that the quality of crop residues and how quickly they decompose can have a greater impact on SOC than the total amount of biomass produced. We believe that the rapid breakdown of daikon radish residues in these intercropping stimulates microbial activity, which helps stabilize organic matter within soil aggregates and mineral-associated pools. This process enhances SOC and SOCS even when residue inputs are relatively small. Notably, the 30:70 (O:D) intercropping ratio showed a significant contribution from oats. Compared to oat monoculture, this intercropping increased SOC by 16.6%, and compared to daikon radish monoculture, it showed a 9.3% increase. Although daikon radish alone performed similarly to the intercropped treatments, the inclusion of oats appears to improve SOC outcomes. These findings highlighted the importance of residue decomposition dynamics in intercropping systems and suggested that strategic combinations of cover crops can enhance soil health more effectively than monocultures.

In the current study, higher microbial population, enzyme activities, and earthworm abundance in monocultures and intercropping highlighted certain biological responses that may enhance SOC or SOCS and improved soil properties. Our findings revealed that daikon radish exhibited a strong positive correlation with SOC, soil microbial population, and enzyme activity. In contrast, oat biomass failed to demonstrate a similar positive relationship with the measured soil indicators. Cover crop species uniquely influence soil microbial population via rhizosphere modification during their growth, primarily due to variations in root structure and exudates [53]. Decomposition and nutrient release from cover crop residue also impact soil microbes, altering community diversity and size [54]. Our findings showed that there was a high correlation between C and N content, which influenced the soil microbial population (Figure 3 and Table A1). The 10:90 (O:D) intercropping ratio, likely due to its high N content relative to C content, significantly impacted the soil microbial population. The decomposition of high-nitrogen residues accelerated nutrient mineralization, supplying microbes with both C and N substrates needed for their metabolism and growth [55]. Additionally, sufficient N availability prevents microbial nutrient limitation, allowing for a more diverse and active microbial community [56].

Soil enzyme activities, such as dehydrogenase, β-glucosidase, urease, and alkaline phosphatase, are enhanced by organic matter composition, temperature, moisture, and pH, all of which are affected by cover crop residues left on the soil surface [57]. Our findings supported the correlation between factors affecting the improvement of enzyme activities, including cover crop biomass, especially daikon radish, C, N, C:N ratio, SOC, microbial population, and soil moisture (Figure 3). Intercropping treatments with higher daikon radish ratios (e.g., 30:70, 10:90 O:D), demonstrated the highest dehydrogenase activity. This is likely due to increased microbial populations and activity stimulated by the quantity and quality of organic inputs from cover crop residues (N and C contents of plant tissue). Positive correlations with cover crop biomass, SOC, C content, and microbial population reinforce that increased organic matter availability fuels microbial growth and enzyme production, especially dehydrogenase activity [58,59]. Also, our findings indicated that soil moisture content was highest in monoculture and intercropping systems with a high proportion of oats. Adequate soil moisture in treatments with high oat biomass likely support microbial and enzyme activity, as water availability influences enzyme-substrate interactions [60]. However, the decrease in dehydrogenase activity in oat monoculture and control treatments may be due to the higher C:N ratio of oat residues and their slower decomposition or low N content.

β-Glucosidase enzyme plays a key role in carbon cycling by hydrolyzing cellulose and other carbohydrates into glucose [61]. β-Glucosidase enzyme activity was highest in intercropping treatments with intermediate C:N ratios (30:70 (O:D) and related intercropping), suggesting these ratios optimized residue decomposition rates for carbohydrate availability. These results were supported by the low C:N ratios obtained in those intercropping ratios (Table 3). In contrast, oat monoculture with a high C:N ratio may slow decomposition, thus lowering β-glucosidase activity.

Our findings showed that treatments with higher nitrogen content (such as daikon radish monoculture and larger proportions of daikon radish in intercropping) increased urease activity (Table 5 and Table A1), indicating stimulation of N mineralization enzymes by available N substrates [62]. As the correlation results confirmed, urease enzyme activity was more dependent on N (r = 0.731 **) than on C content (r = 0.671 **). However, lower activity in oat-dominated systems was possibly due to lower N input or fewer labile N substrates in residues. Additionally, soil microbial populations and soil moisture positively affected urease production. The correlation results between soil microbial populations, soil moisture, and urease enzyme activity support this. Cover crop roots and exudates support soil microbial activity by providing enzymes such as urease, phosphatase, and carbon source [62,63].

Intercropping had a higher impact on alkaline phosphatase activity than monocultures. Increased phosphatase activity suggested enhanced organic phosphorus mineralization, thus supporting plant and microbial phosphorus uptake [64]. Although the phosphorus element in cover crop tissues and soil was not examined in the current study, it has been proven that daikon radish is a rich source of phosphorus [65]. A significant correlation between daikon radish biomass and alkaline phosphatase enzyme (r = 0.634 **) supports the evidence that daikon radish enhances the activity of this enzyme. In contrast, results from correlation analysis indicated that the oat biomass had no impact on alkaline phosphatase activity. It has been stated that increased crop residue on the soil surface may promote the transformation of organic matter into mineral phosphorus, thus increasing phosphorus availability [66]. However, our findings do not support such a statement.

Increased earthworm populations, especially in intercropping treatments, indicated improved soil porosity and organic carbon availability, which appeared to create favorable microhabitats and food resources [67,68]. The strong correlations between oat biomass, daikon radish, total cover crop biomass, C content, N content, C:N ratio, key soil biological indices, and earthworm populations suggested a significant and complex influence of these factors on earthworm abundance (Figure 3). Although the exact relationship between C:N ratio and earthworm response remains unclear, previous studies confirm that cover crops generally boost earthworm populations [69,70].

Reduced soil bulk density and increased porosity, particularly in intercropping with high daikon radish, indicated root activity breaking up compacted layers and improving aeration and water infiltration. This aligns with the known bio-drilling root system of daikon radish, which creates pores and channels, positively affecting infiltration [71]. Oat roots can also positively impact soil bulk density and porosity. Our study found that a 50:50 (O:D) intercrop led to a 15. 3% decrease in soil bulk density and a 10.0% increase in soil porosity compared to oat monoculture (Table 6). Conversely, compared to daikon radish monoculture, the same intercropping ratio resulted in a 9.09% increase in soil bulk density and an 8.3% decrease in soil porosity (Table 6). In a 50:50 (O:D) intercropping system, oats showed a stronger effect in reducing soil bulk density and increasing porosity than daikon radish, despite its finer root system. This suggested a synergistic relationship between different intercropping ratios, warranting further research to optimize seeding ratios. The impact of cover crop biomass on reduced bulk density and increased porosity is among the most important factors in reducing water infiltration time [72,73].

4.2. Impact of Cover Crops on Weed Population and Biomass

In this study, cover crops effectively reduced the population and biomass of dominant weeds present in experimental plots. Oat monoculture and 90:10 (O:D) intercropping significantly suppressed weeds, largely due to the high biomass produced, which was influenced by seeding rate and planting density. Specifically, a 5:1 (O:D) seed ratio resulted in higher overall biomass in both monoculture and intercropping systems (Table 3). Dense cover crop biomass limits weed establishment and growth by physically occupying space and forming mulch, which restricts light, water, and nutrient access, lowers soil temperature, and inhibits weed seed germination [74].

A significant negative correlation was observed between oat and total cover crop biomass and between weed population and biomass, indicating that increased crop biomass effectively suppresses weeds (Figure 3). Residue decomposition, governed by C:N ratio, also influenced weed control. Oat residues (C:N ≈ 23) decompose more slowly than daikon radish residues (C:N ≈ 16–19), remaining on the soil surface longer and providing extended weed suppression. Additionally, oats may exert allelopathic effects, reducing weed germination and establishment. For example, Ahmadnia et al. [32] reported that oat extract inhibited wild mustard (Sinapis arvensis L.) germination due to its phenolic compounds. In contrast, daikon radish monoculture and daikon-dominant intercropping poorly suppressed the weed population, likely due to lower aboveground biomass despite benefits to soil quality.

Hand weeding further reduced weed biomass by approximately 12.4% (Table 8). Although the interactive effect of cover crops and hand weeding was not statistically significant on weed biomass, it demonstrated a synergistic effect in reducing weed populations and enhancing overall weed control. The increase in weed populations and biomass in the second year suggested a potential buildup of weed seed banks, highlighting the need for continuous integrated weed management strategies. Overall, these findings emphasize that effective weed suppression in cover crop systems depends primarily on the quantity and quality of cover crop biomass.

4.3. Impact of Enhanced Soil Properties and Weeding Strategy on Spinach Yield

Spinach yield was increased by soil health improvement and reduced weed pressure [7,75]. Insufficient early-season weed suppression can cause irreversible yield losses, a common challenge in leafy vegetable cultivation [76]. While both soil quality and weed pressure affect spinach performance, their relative importance may vary depending on management intensity and system conditions.

Our results indicated that cover crops with a high proportion of daikon radish improved soil physical and biological properties; however, these enhancements alone did not result in increasing spinach yield. In fact, daikon radish monoculture produced the lowest yield, slightly higher than the control treatment (Figure 2a,b). In contrast, oat-dominated cover crop systems generated higher biomass and more effectively suppressed weeds, which resulted in the highest spinach yield (Figure 2a,b). The results suggested that, at least in the short to medium term, weed suppression is the dominant factor regulating spinach productivity. Strong negative correlations between weed population and biomass and spinach yield further support that reduced competition for light, water, and nutrients significantly benefits spinach growth (Figure 3).

Once spinach is established, hand weeding further enhances spinach yield by removing remaining weeds, thus minimizing competition. Improved soil quality also contributes positively to spinach growth, as indicated by correlation analysis results (Figure 3), but enhanced soil properties alone may not fully offset weed pressure. Therefore, spinach yield improvements can be attributed primarily to two factors: effective reduction in weed population and biomass, and enhancement of soil biological and physical properties. These findings are consistent with previous studies emphasizing the role of cover crops and their residues in suppressing weeds and improving crop performance [77,78,79].

5. Conclusions

The findings of this study indicated that intercropping oats (Avena sativa L.) and daikon radish (Raphanus sativus var. longipinnatus) creates a synergistic system in which the strengths of each species complement one another, leading to significant improvements in soil quality and spinach productivity. The two key benefits, enhanced soil properties and effective weed suppression, are driven by distinct mechanisms and optimized at different seeding ratios.

Daikon radish-dominated mixtures improved soil properties primarily because of their low C:N ratio, which promotes rapid residue decomposition. Consequently, treatments with higher radish proportions exhibited the greatest soil organic carbon, microbial populations, and enzyme activities (dehydrogenase, β-glucosidase, urease, and alkaline phosphatase), as well as enhanced physical properties, such as lower bulk density, shorter water infiltration time, and greater porosity. The 30:70 (O:D) ratio was particularly effective, achieving the highest soil organic carbon and strongest biological indicators. In contrast, oat monoculture and the 90:10 (O:D) mixture produced the highest biomass, enabling the most effective suppression of dominant weed species (Chenopodium album, Amaranthus azurea, and Fumaria officinalis).

The choice of an optimal seeding ratio is a strategic decision guided by the farmer’s primary goal. For enhancing soil health, such as increasing organic carbon and stimulating biological activity, a 30:70 (O:D) intercropping ratio is recommended. This combination balances the rapid decomposition and soil-biopore formation of daikon radish root with sufficient oat biomass to contribute to long-term soil carbon. Conversely, for maximum weed suppression and short-term yield, particularly under high weed pressure, oat monoculture or a 90:10 (O:D) mixture is preferable. This approach can substantially reduce hand-weeding requirements. Notably, oat monoculture without weeding produced only 2.8% lower spinach yield than the weeded treatment.

Future research should include economic analyses and mechanistic studies, such as clarifying the potential allelopathic role of oat in weed suppression and examining how different intercrop residue qualities shape microbial community structure. Such insights will strengthen the development of precision intercropping strategies for sustainable vegetable production.