Indica-Japonica rice intercropping enhances rice productivity by efficiently utilizing the resources

Abstract

Intercropping is widely practiced to improve crop yield and resources use efficiency. However, its effect on rice, especially the subspecies rice such as Indica and Japonica intercropping is elusive. A two-year field experiment (2021–2022) was conducted to assess the effects of Indica-Japonica intercropping on rice growth, yield, and quality. Results showed that intercropping increased the leaf area and efficient leaf area of Indica by 45% and 13.5%, and Japonica by 46% and 19% as compared to monocropping. At the system level, Indica-Japonica intercropping improved the yield indices including the number of effective panicles and panicles, spikelet fertility, and 1000-grain weight, leading to higher crop yield (18.5% and 39.5%) and biomass dry matter (51% and 20%) compared to Indica or Japonica under monocropping. The improved photosynthetic rate due to better light environments also contributed to higher intercropping crop yield. Though intercropping reduced the brown rice quality and chalkiness, but improved head mild rice rate. The higher LER (1.25), LEC (0.36), SPI (13.2), ATER (1.22), and LUC (186.86) values confirmed higher productivity and efficient land use under intercropping. The crowding index (K = 3.71) favoured intercropping, with Indica (aggressivity A_IR = 3.55) dominant over Japonica (aggressivity A_JR = -3.55). The competitive ratio (CR > 0) indicated minimal competition for resources. This indicates that Indica-Japonica intercropping could improve the growth, yield and quality of rice by efficiently utilizing resources, thus offer a more sustainable rice production system compared to monocropping.

Introduction

Global food demand is rising, yet arable land continues to shrink due to urbanization and degradation [1, 2]. While chemical inputs boost yields, they harm ecosystems, and traditional methods often waste resources [3, 4]. Genetically modified crops can offer high yields but often lack nutritional quality [4, 5]. To sustainably increase yield and quality, agriculture must shift toward resource-efficient systems. Intercropping offers a promising solution, enhancing productivity, improving grain quality, and conserving environmental resources.

Intercropping, the simultaneous cultivation of two or more crops on the same land, is one of the oldest and most promising approaches to enhance resource use efficiency and crop productivity [4, 6, 7]. By growing complementary crops that differ in resource demands or growth periods, intercropping can optimize the capture and utilization of water, light, nutrients, and land, reducing competition and fostering mutual facilitation among component crops [5, 8, 9]. This interaction often leads to higher total yields than monocropping of each species alone [3, 10, 11]. Temporal separation of crops through relay intercropping, where one crop is sown before the other is harvested, can further minimize competition and improve resource partitioning [4, 12]. For example, in maize-soybean relay intercropping, early-sown maize exploits early-season resources while later-sown soybean efficiently uses remaining resources after maize harvest, resulting in greater overall productivity despite transient shading effects during co-growth [13–15]. Similar patterns of complementarity and resource optimization have been documented in maize-alfalfa and other cereal-legume intercropping systems, with land equivalent ratios (LER) often exceeding 1, indicating more efficient land use compared to monocropping [3, 5].

Although intercropping is widely practiced between cereals and legumes, especially in resource-limited regions worldwide [16], its application in rice production remains limited and less studied. In China, intercropping is common in various provinces but mostly involving non-rice crops [17]. Existing rice intercropping research primarily focuses on combinations with aquatic vegetables or dryland crops (e.g., rice-water spinach, rice-watermelon), targeting soil quality improvement and disease control [18–20]. However, intercropping within rice subspecies, specifically between Indica and Japonica, has recently gained attention as a novel approach to boost productivity and resource use efficiency.

A recent study on Indica-Japonica intercropping with staggered sowing demonstrated improved total rice yield by optimizing resource use, Indica exploits early-season light and nutrients, while Japonica uses late-season resources [21]. This complementary growth reduces competition, improves photosynthesis, and achieves high land equivalent ratios (LER > 1.2) [21]. This suggests that intercropping these subspecies leverages their genetic and physiological differences to create a synergistic and more productive system.

Rice (Oryza sativa L.) feeds over half of the global population and is a staple in Asia, Sub-Saharan Africa, and South America [22]. Despite recent production increases, hunger persists, emphasizing the need to improve rice yield and resource efficiency [23]. China, the world’s largest rice producer, accounts for 25% of global production and feeds 65% of its population [22, 24]. The Northern Jiang Huai region, spanning the Yangtze and Huaihe River basins, is a major rice-producing area in Southeastern China, where Indica and Japonica are the dominant single-season rice subspecies. However, rice yields in this region are declining due to shrinking planting areas and inefficient resource use, with significant natural resource waste during early and late cropping seasons. Thus, modifying the rice production system is essential. Introducing Indica-Japonica intercropping offers a sustainable solution to boost production and improve resource utilization. The two subspecies differ in growth duration, resource requirements, and environmental adaptability, making their intercropping a promising strategy to enhance yield, resource use efficiency, and rice quality. Early-growing Indica can capture early-season resources, while later-planted Japonica exploits residual resources in the late season, reducing competition and increasing overall system productivity.

This study aims to evaluate the effects of Indica-Japonica intercropping on rice growth, yield, and quality, with the hypothesis that temporal and spatial resource complementarity will improve system productivity and efficiency over monocropping. Additionally, intercropping these two rice subspecies with distinct qualities may improve the overall rice quality. By exploring this novel intercropping combination, the findings will contribute valuable insights for developing sustainable and resource-efficient rice production systems, helping to meet increasing food demands while conserving natural resources.

Materials and methods

Site description

Field experiments were conducted in 2021 and 2022 at the Pingqiao and Guangshan rice production bases of Henan Agricultural University in Xinyang, respectively. Both sites featured paddy soil with pH 6.8. At Pingqiao, the 0–20 cm soil layer contained 148.2 mg/kg available potassium, 2.19 g/kg total nitrogen, 15.95 mg/kg available phosphorus, and 31.35 g/kg organic Matter. At Guangshan, the corresponding values were 153 mg/kg, 2.97 g/kg, 7.2 mg/kg, and 38.3 g/kg, respectively.

Experimental design and management

Indica (IR) (Xiang Liangyou 900: XLY900) and Japonica (JR) (Yongyou No. 9: YY9) rice species were grown as a monocropping and intercropping in a randomized complete block design (RCBD) on plots size of 20 m², and replicated thrice. The treatments comprised: MCI (monocropping Indica), MCJ (monocropping Japonica), ICI (intercropping Indica), ICJ (intercropping Japonica), and ICIJ (Indica-Japonica intercropping). Under MCI and MCJ, the row spacing was 30 cm respectively, and, the plant spacing was 20 cm for MCI and 13.3 cm for MCJ. For intercropping, a 2:2 Indica-Japonica relay system was used, alternating two rows of Indica with two rows of Japonica. The row spacing was Maintained at 25 cm for ICI and ICJ, and 30 cm between the component species. However, the plant spacing was 13.3 cm for ICI and 10 cm for ICJ (Fig. 1). The different plant spacing was adjusted to efficiently utlize the resource such as light, nutrients, and land, based on the distinct growth characteristics of Indica and Japonica.

Fig. 1.

Experimental design of Indica-Japonica rice intercropping and monocropping systems: In the intercropping system, row spacing was 25 cm within Indica and Japonica rows, and 30 cm between them, while Plant spacing was 13.5 cm for Indica and 10 cm for Japonica. In monocropping, row spacing was 30 cm for both species, with plant spacing of 13.5 cm for Indica and 20 cm for Japonica

The rice seeds were sown using a plastic floppy disk and Manually transplanted to the Main field at 4 leaf stage, with two seedlings per hole for IR and four per hole for JR. The detailed growth period from sowing to maturity are provided in Table 1. A base dose of nitrogen fertilizer (23.5 kg N ha⁻¹) was applied in three stages (4:4:2): 4.5 kg N ha⁻¹ at the tillering of Indica, 10.5 kg N ha⁻¹ at the ear-pumping stage of Indica, and 8.5 kg N ha⁻¹ at the ear-pumping stage of Japonica. Average daily temperature and rainfall were recorded from transplanting to harvest for both years (Fig. 2). Other field management practices, including irrigation, weed control, and pest and disease management, were carried out in accordance with high agricultural standards.

Table 1.

Growth period of Indica and Japonica 

Year	Rice Species	Sowing date	Transplanting date	Heading date	SD-HD/d	Maturity date	HD-MD/d	Growth period/d
2021	Indica (XLY900)	20/3	6/5	28/7	130	9/3	37	167
	Japonica (YYL)	12/5	4/6	14/9	125	11/8	55	180
2022	Indica (XLY900)	20/3	6/5	28/7	130	9/1	35	165
	Japonica (YYL)	12/5	4/6	14/9	125	10/28	45	170

SD Sowing date, HD Heading stage, MD Maturity stage

Fig. 2.

Daily temperature and rainfall data of the experimental site from rice transplanting to harvesting During the 2021 and 2022 growing season

Data collection and measurements

Physio-agronomic indices

Plant height and steam sheath

The plant height (cm) and head of stem sheath (%) of rice species were measured at the tillering, heading and maturity stage with a measuring tape, and the average was calculated.

Leaf area

The leaf area index (LAI, cm²) and efficient leaf area index (ELAI, cm²) of rice species were estimated at the tillering, heading and maturity stage, and calculated with the formulas (Eqs. 1 and 2) [25].

1

2

Yield components

The rice species (IR and JR) were harvested from representative areas of 5 m² at full maturity. The yield components such as the number of effective panicles (10⁴/ha), number of panicles, 1,000-grain weight (g), spikelet fertility (%), and grain yield (GY, t h⁻¹) of IR and JR species were measured under monocropping and intercropping.

Biomass dry matter (BDM)

Rice plants of Indica and Japonica species, including effective panicle, stem sheath, upper leaves, green leaves, and empty panicles, were collected from 5 m². Samples were sun dried, packed in kraft paper bags and oven-dried at 105 °C for 0.5 h, then further dried at 80 °C for at least 48 h to constant weight. Biomass dry matter (BDM) was then measured using an electronic scale.

Percent change of GY and BDM

The percent changes of grain yield (GY) and biomass dry matter (BDM) over the two years was used to assess the performance improvement of different planting patterns. This was calculated using the following formula (Eq. 3).

3

Where PGYC is the percent change in grain yield, Y₁GY is the grain yield of year 1 and Y₂GY is the grain yield of year 2 of rice species under different planting patterns.

Assessment of productivity and resources use efficiencies of Indica-Japonica intercropping

Land equivalent ratio

The land equivalent ratio (LER) is an index used to measure the efficiency of intercropping compared to mononcropping. It indicates how much land would be required under monocropping to produce the same yield as intercropping system. LER is calculated according to Eq. 4 [5].

4

The Y_ICI and Y_ICJ are the relative yields of IR and JR rice species under intercropping, and Y_MCI and Y_MCJ are the yields of the same species under monocropping, respectively.

Land equivalent coefficient (LEC)

The Land Equivalent Coefficient (LEC) is the product of the Land Equivalent Ratios (LER) of Indica (LER_IR) and Japonica (LER_JR) rice. It measures intercropping efficiency by accounting both land use proportion and crop yields [26]. It is commonly used to assess the overall advantage of intercropping systems and is calculated using Eq. 5.

5

Area time equivalent ratio (ATER)

The Area Time Equivalent Ratio (ATER) is an index used to evaluate the efficiency of intercropping systems by accounting for both land use and the time duration each crop occupies that land [27–29]. It is used to assess the yield advantage of intercropping over monocropping for the full duration from planting to harvest. ATER is calculated using Eq. 6.

6

The t_IR and t_JR signify the growth periods (in days) of IR and JR from planting to maturity, respectively, while T is the longest growth period duration of the crop.

Land use efficiency (LUE)

Land Use Efficiency (LUE) refers to how effectively available land resources are utilized for crop production. It measures the efficiency of growing multiple crops simultaneously on the same land compared to growing them separately in monocropping [29, 30]. It is calculated using Eq. 7.

7

System productivity index (SPI)

The System Productivity Index (SPI) assesses the overall productivity of an intercropping system by converting one crop’s yield into the equivalent of the other. It is used to compare the productivity and stability of intercropping systems to monocropping by standardizing the yield of the secondary crop (Japonica) relative to the primary crop (Indica) [31–33]. SPI is calculated using Eq. 8.

8

Y_ICI and Y_ICJ represent the yields of Indica (IR) and Japonica (JR) rice under intercropping, while Y_MCI and Y_MCJ denote their respective yields under monocropping.

Competitive indices

Relative crowding index (K)

The Relative Crowding Index (K) measures the benefit and advantages of intercropping species (Eqs. 9–11). A K > 1 indicates an advantage for intercropping, while K < 1 indicates a disadvantage (Eqs. 9, 10 and 11).

9

10

11

K_ICI and K_ICJ represent the relative crowding indices for Indica and Japonica under intercropping, respectively, while Z_ICI and Z_ICJ denote the area of Indica and Japonica under intercropping.

Aggressivity (A)

Aggressivity (A) was used as a competitive index to assess how much one crop’s relative yield exceeds that of the other in the mixture (Eqs. 12–13) [32, 34].

12

13

If A_IR or A_JR = 0, both crops are equally competitive. A positive A_IR indicates Indica dominates Japonica, while a negative A_IR shows Japonica as the dominant species.

Competitive ratio (CR)

The Competitive Ratio (CR) was used to evaluate the competitive ability of crops in an intercropping system and calculated using Eqs. 14–15 [35, 36].

14

15

When CR_IR < 1, intercropping offers a positive benefit, suggesting Indica can be intercroped with Japonica. However, if CR_JR >1, it indicates a negative benefit. If the difference between CR_IJ and CR_IR is 0, both crops are equally competitive [37, 38]. A positive difference shows Indica dominates, while a negative value means Japonica is the dominant species.

Photosynthetic rate

The photosynthetic rate was measured from the fully expanded uppermost flag leaf at the heading stage (10th leaf stage) with slight adjustments (Eq. 16). In the intercropping system, measurements were taken from both outer and inner rows of each crop species to account for variations in light exposure and canopy position. Using a Yaxin-1101 photosynthetic analyzer, CO₂ Changes in the plants were monitored for 60 s in a closed-circuit system within a 60 cm L × W photosynthetic chamber. These measurements were Made between 0900 and 1100 h under clear sky conditions to ensure maximum photosynthetic activity [39].

16

Where N₁ and N₂ denote the initial and final concentration of CO₂ at 60 s, respectively.

Light transmittance

Light transmittance through the rice canopy was measured at key development stages such as tillering, panicle initiation, heading, and grain filling to evaluate changes in canopy structure and light distribution over time. At each stage, light transmission was measured at ground level and various canopy heights using a UA-002-64 quantum sensor, following the calculation in Eq. 17. The sensor was placed between the rows of Indica and Japonica rice for the intermediate crop treatment. These measurements were taken between 09:00 and 11:00 a.m. under clear sky conditions to minimise environmental variability.

17

Rice quality

Rice quality was evaluated based on the brown rice rate (BRR), milled rice rate (MRR), and head mild rice rate (HMRR), following the national standard “GB/T17891-1999 High-Quality Rice” of the People’s Republic of China.

Brown rice rate

Approximately 40 g of whole rice (for both IR and JR) was dehulled using a JGMJ8098 laboratory detector, then re-weighed (W₂). The brown rice rate was calculated using the formula in Eq. 18.

18

Mild rice rate

The collected brown rice was milled using a JGMJ8098 rice polisher for 90 s (IR) and 40 s (JR). The milled rice was then passed through a 2.0 mm sieve, and the weight (W₃) was recorded to calculate the milled rice rate using the formula in Eq. 19.

19

Head mild rice rate

Milled rice grains longer than or equal to four-fifths of the full grain length were selected, and the weight (W₄) was recorded. The head mild rice rate (HMRR) was then calculated using the formula in Eq. 20.

20

Appearance quality

Rice appearance quality was assessed based on chalky rice rate and chalkiness degree. Polished rice grains were scanned using a CanoScan 5600 F scanner, with each indicator measured in triplicate for each sample.

Statistical analyses

Data were compiled in MS Excel 2016 and analyzed using SPSS 22.0 and MS statistix 8.1 with a randomized complete block design (RCBD). Mean comparisons were made using the LSD test at p ≤ 0.05. Graphs were created with GraphPad Prism 8.1.

Results

Daily temperature and rainfall trends after rice transplanting

The average daily temperatures and rainfall in both years followed a similar trend, rising from May to mid-August and then gradually declining until late November (Fig. 2). However, 2022 had higher temperatures and lower rainfall compared to 2021.

Physio-agronomic indices

Indica-Japonica intercropping significantly influenced (p ≤ 0.05) the physio-agronomic indices such as head of stem sheath, leaf area index (LAI), and effective leaf area index (ELAI) of IR and JR, but did not affect their plant height (Table 2). Compared to monocropping (MCI and MCJ), intercropping (i.e., ICI and ICJ) increased the head of stem sheath of IR by 9%, but decreased that of JR by 4%. Intercropping (i.e., ICI and ICJ), increased the LAI and ELAI of IR by 45% and 46%, and JR by 13.5% and 19%, respectively, as compared to their corresponding monocropping (i.e., MCI and MCJ).

Table 2.

Growth indices of Indica and Japonica rice under different planting patterns

Year	PP	Plant height (cm)	Leaf area index	Efficient leaf area index	Height of stem sheath (%)
2021	MCI	119.67 ± 3.51	7.03 ± 0.82 b	4.41 ± 0.28 b	28.72 ± 1.53 b
	MCJ	117.00 ± 2.89	8.80 ± 0.14 a	4.76 ± 0.28 b	32.21 ± 0.95 ab
	ICI	122.00 ± 1.00	8.86 ± 0.62 a	6.37 ± 0.22 a	32.36 ± 3.31 a
	ICJ	119.67 ± 2.50	9.24 ± 0.19 a	4.94 ± 0.61 b	22.16 ± 3.45 c
Sig		0.31ns	0.00***	0.00***	0.00***
2022	MCI	127.00 ± 1.73 a	8.38 ± 1.25 b	5.31 ± 0.58 bc	29.72 ± 1.53 a
	MCJ	130.33 ± 3.00 a	10.00 ± 0.74 b	6.09 ± 0.15 b	31.21 ± 2.14 a
	ICI	127.33 ± 0.57 a	13.76 ± 0.46 a	7.82 ± 0.57 a	31.36 ± 3.38 a
	ICJ	119.00 ± 3.05 b	8.23 ± 1.13 b	4.29 ± 0.77 c	23.82 ± 2.33 b
Sig		0.01**	0.00***	0.01**	0.01**

The mean values ± SD with dissimilar lower case letters are different from each other at LSD test (p ≤ 0.05) level of probability

PP Planting patterns, MCI Monocropping Indica, MCJ Monocropping Japonica, ICI Intercropping Indica, ICJ Intercropping Japonica

** P ≤ 0.01

*** P ≤ 0.0001

^nsNon-significant (P > 0.05)

Yield and yield components

Indica-Japonica intercropping (ICIJ) significantly affected (p ≤ 0.05) the yield and yield components of IR and JR (Table 3; Fig. 3). Intercropping (i.e., ICI and ICJ) had lower yields and yield indices compared to monocropping (i.e., MCI and MCJ). Specifically, the lowest number of effective panicles of IR (202.15) and JR (123.3) was observed in ICI and ICJ, yet, achived 65% and 51.2% of the numbers of MCI and MCJ, respectively. Similarly, ICI and ICJ produced lower number of panicles for IR (216.3) and JR (164.9), respectively, yet achived 91.7% and 90.6% of the number of MCI and MCJ.

Table 3.

Yield indices of Indica and Japonica rice under different planting patterns

Year	PP	No. of Effective panicles(104/ha)	No. of Panicles	1000-grain weight (g)	Spikelet fertility (%)
2021	MCI	216.67 ± 16.65 b	266.53 ± 19.04 a	23.68 ± 0.81 b	82.38 ± 3.12 a
	MCJ	258.97 ± 14.46 a	158.80 ± 6.76 c	23.51 ± 0.27 b	81.60 ± 1.10 a
	ICI	173.80 ± 10.64 c	227.36 ± 14.18 b	24.67 ± 0.10 a	71.38 ± 4.01 b
	ICJ	133.33 ± 11.54 d	143.94 ± 16.22 c	24.37 ± 0.19 a	83.97 ± 4.01 a
	Sig	0.00***	0.00***	0.00***	0.01*
2022	MCI	266.53 ± 16.66 b	250.24 ± 3.64 a	23.28 ± 0.23 b	71.81 ± 4.53 c
	MCJ	334.00 ± 14.46 a	205.20 ± 3.55 b	23.31 ± 0.16 b	58.69 ± 3.59 b
	ICI	230.80 ± 8.67 c	245.79 ± 5.34 a	24.73 ± 0.22 a	72.92 ± 6.91 b
	ICJ	113.33 ± 11.55 d	186.00 ± 8.98 c	24.65 ± 0.56 a	76.46 ± 4.01 a
	Sig	0.00***	0.00***	0.00***	0.00***

The mean values ± SD with dissimilar lower case letters are different from each other at LSD test (p ≤ 0.05) level of probability

PP Planting patterns, MCI Monocropping Indica, MCJ Monocropping Japonica, ICI Intercropping Indica, ICJ Intercropping Japonica

*** P ≤ 0.0001

Fig. 3.

Yield and biomass dry of Indica and Japonica under monocropping and intercropping, and the changes in these indices across years. Grain yield a and biomass dry matter b, PGYC; percent changes in grain yield c, and PBDMC; percent changes in biomass dry matter d. MCI; Monocropping Indica, MCJ; Monocropping Japonica, ICI; Intercropping Indica, ICJ; Intercropping Japonica, ICIJ; Indica-Japonica intercropping. Lowercase letters on the bars indicate significant differences at LSD test p ≤ 0.05

Regarding spikelet fertility, IR showed a 15% hcr, where ICI outperformed MCI by 2%. Conversely, JR had (3–30%) higher spikelet fertility under ICJ than MCJ. Intercropping (i.e., ICI and ICJ) had the highest 1000-grain weight for IR (24.7 g) and JR (24.6 g) compared to MCI and MCJ.

In terms of grain yield, monocropping (i.e., MCI and MCJ) produced higher grain yeild for IR (10.55 t ha⁻¹) and JR (9.0 t ha⁻¹) than ICI and ICJ (IR: 8.5 t ha⁻¹; JR: 4.0 t ha⁻¹) respectively, yet ICI and ICJ achived 80.4% and 45.1% of the yields of MCI and MCJ. However, at the system level, ICIJ achieved 18.5% and 39.5% higher grain yields than MCI and MCJ, respectively. Additionally, ICIJ showed a notable improvement over time, with a 21% higher grain yield in the second year compared to the first year.

Biomass dry matter

Indica-Japonica intercropping influenced (p ≤ 0.05) the biomass dry matter (BDM) of IR and JR. Results showed that intercropping (i.e., ICI and ICJ) had lower BDM compared to monocropping (i.e., MCI and MCJ), however, at the system-level (i.e., ICIJ), the BDM was higher than that of MCI and MCJ.

Specifically, MCI and MCJ produced the highest BDM (IR; 10.7 t ha⁻¹ and JR: 13.6 t ha⁻¹), compared ICI and ICJ (IR: 9.2 t ha⁻¹ and JR: 7.1 t ha⁻¹), respectively, yet ICI and ICI achived 83.2% and 48.5% of the BDM of MCI and MCJ for IR and JR, respectively. At the system level, however, BDM under ICIJ was 51% and 20% higher than that of MCI and MCJ, respectively. Furthermore, ICIJ exhibited a 26% increase in BDM in the second year compared to the first year.

Light transmittance and photosynthetic rate

Intercropping of Indica-Japonica affected (p ≤ 0.05) the light transmittance and photosynthetic rate (Pn) of Indica (IR) and Japonica (JR) (Fig. 4). Intercropping (i.e., ICI and ICJ) had 108% and 128% higher canopy light transmittance, respectively, as compared to monocropping (i.e., MCI and MCJ). Similarly, basal Light transmittance was 243% and 109% higher under ICI and ICJ than MCI and MCJ, respectively. The photosynthetic rate (Pn) of IR was higher under intercropping (ICI) than monocropping (MCI), but that of JR was lower under intercropping (ICJ) than monocropping (MCJ). Specifically, the Pn of IR under ICI was 40% higher than under MCI, while the Pn of JR was 26% lower under ICJ compared to MCJ.

Fig. 4.

Light transmittance and photosynthetic rate of Indica and Japonica under monocropping and intercropping in 2021 and 2022. Canopy light transmittance a, basal light transmittance b and photosynthetic rate c. MCI; Monocropping Indica, MCJ; Monocropping Japonica, ICI; Intercropping Indica, ICJ; Intercropping Japonica, ICIJ; Indica-Japonica intercropping. Lowercase letters on the bars indicate significant differences at LSD test p ≤ 0.05

Productivity and resources use efficiencies of Indica-Japonica intercropping intercropping

The resource use efficiency indices were used to assess the advantages and productiveness of Indica-Japonica intercropping (Figs. 5 and 6). The results revealed that Indica-Japonica intercropping had improved efficiency indices such as LER, partial LER (i.e., LER_IR and LER_JR), LEC, SPI, ATER, and LUE. The LER of ICIJ was greater than 1 (1.25), with LER_IR and LER_JR recorded as 0.81 and 0.45, respectively, indicating that intercropping utilized cultivable land more efficiently with minimal competition for resources as compared to monocropping (MCI and MCJ). Likewise, LEC (0.36 > 0) of Indica-Japonica intercropping (ICIJ), suggests that intercropping was more advantageous in terms of resource use with reduced competition for resources. However, LEC_IR (0.9) and LEC_JR (0.4), signify that Indica was more competitive than Japonica under intercropping.

Fig. 5.

Land use efficieny of Indica-Japonica intercropping. a Land Eqviualent ratio (LER), b Land Eqviualent Coefficient (LEC). LER_IR; Land Eqviualent ratio of Indica, LER_JR; Land Eqviualent ratio of Japonica and LER; Land Eqviualent Ratio of Indica-Japonica intercropping system, LEC_IR; Land Eqviualent Coefficient of Indica, LEC_JR; Land Eqviualent Coefficient of Japonica, and LEC; Land Eqviualent Coefficient of Indica-Japonica intercropping. Lowercase letters on the bars indicate significant differences at LSD test p ≤ 0.05

Fig. 6.

Resources use efficiency indices of Indica-Japonica intercropping. a Area Time Equivalent Ratio (ATER), b Land use efficiency (LUC), and c System Productivity Index (SPI). MCI; Monocropping Indica, MCJ; Monocropping Japonica, ICI; Intercropping Indica, ICJ; Intercropping Japonica, ICIJ; Indica-Japonica intercropping. Lowercase letters on the bars indicate significant differences at LSD test p ≤ 0.05

Additionally, the values of ATER, SPI, and LUE under ICIJ over the two years were recorded as 1.22, 24.60, and 188.69, respectively. These findings suggest that Indica-Japonica intercropping (ICIJ) was more efficient in resource utilization, and achieved higher and more stable productivity compared to monocropping (MCI and MCJ).

Competitiveness indices

The competitive indices were analyzed to evaluate the interaction and competition between the two species under intercropping (Fig. 7). These indices included the relative crowding coefficient (K), Aggressivity (A), and competitive ratio (CR). The K value for ICIJ was 3.71 (K > 1), with K_IR at 5.9 (K > 1) and K_JR at 0.65 (K < 1), indicating that ICIJ was more advantageous than monocropping (MCI and MCJ). Additionally, the Aggressivity index of IR (A_IR) was positive (3.55), while that of JR (A_JR) was negative (−3.55), demonstrating that IR was dominant over JR under intercropping (ICIJ). The competitive ratio (CR) of IR (CR_IR) was 1.85 (> 1), whereas that of JR (CR_JR) was 0.57 (< 1), suggesting that there was minimal competition between Indica and Japonica for available resources under intercropping. Overall, these results confirm that Indica-Japonica intercropping (ICIJ) was more productive than their respective monocropping systems and that IR can be effectively intercropped with JR (Figs. 8 and 9).

Fig. 7.

Competitive indices of Indica-Japonica intercropping. a relative crowding index (K), b Aggressivity (A), c competitive ratio (CR). K_ICI; crowding index of intercropping Indica, K_ICJ; crowding indix of intercropping Japonica, A_IR; Aggressivity of Indica, A_JR; Aggressivity of Japonica, CR_IR; competitive ratio of Indica, CR_JR; competitive ratio of Japonica. Lowercase letters on the bars indicate significant differences at LSD test p ≤ 0.05

Fig. 8.

Appearrance quality of Indica and Japonica rice under monocropping and intercropping. a brown rice rate, b mild rice rate, c head mild rice rate. MCI; monocropping Indica, MCJ; monocropping Japonica, ICI; intercropping Indica, ICJ; intercropping Japonica. Lowercase letters on the bars indicate significant differences at LSD test p ≤ 0.05

Fig. 9.

Chalkiness rate and chalkiness degree of Indica and Japonica rice under monocropping and intercropping. a Chalkness rate, b chalkiness degree. MCI; monocropping Indica, MCJ; monocropping Japonica, ICI; intercropping Indica, ICJ; intercropping Japonica. Lowercase letters on the bars indicate significant differences at LSD test p ≤ 0.05

Quality of rice

Indica-Japonica intercropping affected (p ≤ 0.05) the quality and appearance quality of rice over the two years (Fig. 8 and 9). The rice quality indices included brown rice quality, milled rice quality, and head mild rice rate quality, while appearance quality was assessed based on the chalky rice rate and chalkiness degree. Compared to MCI and MCJ, ICI and ICJ resulted in 0.2% and 0.6% lower brown rice quality, respectively. While the milled rice rate showed no significant difference across planting patterns, it was 1% higher in MCI than ICI for IR, and 2% higher in ICJ than MCJ for JR. However, the head mild rice rate of IR and JR increased by 2% and 3%, respectively, under ICI and ICJ compared to MCI and MCJ. In terms of appearance quality, the chalky rice rate and chalkiness degree of IR under ICI were 18% and 20% lower, respectively, than in MCI. Conversely, for JR, these indices were 17% and 39% higher under ICJ than in MCJ.

Discussion

Intercropping is a more efficient and diverse farming system that maximizes the use of natural resources such as water, nutrients, land, and light by allowing different crop sepcies to share ecological niches across sepace and time [4, 40, 41]. In this study, the Indica-Japonica intercropping system significantly improved rice growth, yield, and grain quality by efficiently utilizing resources and promoting spatial and temporal complementarity between the two varieties. For instance, the early-sown Indica rice effectively captured early-season resources (light, nutrients, and land), leading to increased panicle number, panicle density, spikelet fertility, and grain weight. Subsequently, the later-sown Japonica benefited from reduced competition and greater access to residual resources During the seed-filling stage, improving its grain quality and 1000-grain weight. This temporal partitioning of resource use allows both crops to thrive with minimized competition, thereby improving total system yield [4, 42].

Notably, intercropping enhanced LAI of rice, which are vital for photosynthesis, transpiration, and gas exchange [43]. However, excessively high LAI values (i.e., 7.03–13.76) could lead to overly dense canopies. This may reduce light penetration to lower leaves, increase humidity, and raise the risk of lodging during the grain-filling stage. The elevated LAI likely resulted from increased planting density, prolonged vegetative growth due to varietal overlap, and enhanced nutrient uptake from complementary root systems [3, 44]. While a denser canopy improves light interception and biomass accumulation, careful management is needed to balance productivity with structural stability [45, 46].

Despite this, the improved canopy structure and inter-row ventilation under intercropping likely enhanced light penetration and lowered canopy temperature, which, in turn, increased photosynthetic efficiency and promoted crop development. Similar mechanisms have been documented in maize-soybean relay intercropping, where early-sown maize exploits early-season resources while later-sown soybean recovers post-maize harvest and utilizes late-season inputs [17]. Despite temporary shading and reduced growth during co-growth, soybean ultimately contributes to higher system-level yield [17]. Likewise, wheat-maize and maize-alfalfa intercropping systems have shown spatial and temporal resource partitioning that reduces competition and increases system productivity [5, 47].

The enhanced productivity in the Indica-Japonica intercropping system is further supported by efficiency indices [48, 49]. The LER exceeded 1, confirming that intercropping utilized land more efficiently than monocropping. Additional indices such as the LEC and LUE were also higher under intercropping, indicating strong interspecific facilitation. These results align with other intercropping systems, such as maize-soybean (LER: 1.22–1.55) [50], peanut-corn (LER: 1.15–1.16) [51], and maize-alfalfa (LER: 2.1–2.3) [10], where improved resource capture and yield advantage over monocropping have been reported. Similarly, potato-bean intercropping has shown superior LER, LEC, and LUE values, supporting the present findings [49].

Beyond land use, time-related efficiency was evident through higher ATER and SPI in the Indica-Japonica intercropping system. These indices reflect the system’s ability to optimize resource use over time and space, confirming that relay intercropping is not only more productive but also more stable than monocropping [49, 52]. Comparable results have been seen in oat-common vetch and potato-bean intercropping, where higher ATER and SPI values indicated improved productivity and sustainability [33].

Competitive dynamics further reinforce the advantage of this intercropping system [11, 53]. The Relative Crowding Coefficient (K) was greater under intercropping, indicating an overall advantage in resource capture. Indica, sown earlier, showed a higher K value and positive aggressivity index, establishing it as the dominant competitor during co-growth. Japonica, with negative aggressivity values, played a more complementary role by utilizing late-season resources after Indica harvest. Both varieties showed positive Competitive Ratios (CR), suggesting mutual coexistence with minimal interference. These findings mirror maize-alfalfa intercropping, where maize initially dominates, but after harvest, alfalfa quickly recovers, contributing significantly to system productivity [3].

In addition to yield improvements, Indica-Japonica intercropping may also enhance grain quality. Interactions between species with different physiological traits could influence grain characteristics through root exudates, nutrient exchange, or microclimatic modification [10]. Similar quality improvements have been observed in cereal-legume systems, where legumes improve nutrient availability and grain composition in cereals [7, 10, 16].

This suggests that Indica–Japonica intercropping enhances yield, resource efficiency, and grain quality by promoting complementary growth. This system offers a practical, sustainable approach for improving rice production, benefiting researchers seeking innovation, farmers aiming for higher productivity, and policymakers pursuing food security and land-use efficiency.

Conclusions

The findings of this study demonstrate that Indica-Japonica intercropping significantly enhances rice growth, yield, and quality, primarily due to more efficient resource utilization. Improved ventilation and light absorption within this intercropping system boosted photosynthetic rates and promoted crop growth, resulting in higher rice yields and quality. Additionally, the higher land equivalent ratio (> 1), land equivalent coefficient, and land use efficiency values suggest that Indica-Japonica intercropping outperforms monocropping in productivity and land use efficiency. The elevated area time equivalent ratio and system productivity index values further confirm that this intercropping system is not only more productive but also more stable than monocropping. The relative crowding index (K) values exceeding 1 indicate that intercropping provides clear advantages over monocropping. The aggressivity and interspecific competitiveness indices for Indica and Japonica show minimal competition for resources, highlighting the complementary nature of the two species in this system. These results suggest that Indica-Japonica intercropping is an effective strategy for maximizing rice yields, quality, and optimizing resource use. Adopting Indica-Japonica rice intercropping in areas where rice is the primary crop and resources are limited could significantly improve resource utilization and contribute to sustainable rice production, thereby supporting food security in these regions.

Abbreviations

A_IR

Aggressivity of Indica rice

A_JR

Aggressivity of Japonica rice

ATER

Area time equivalent ratio

BDM

Biomass dry matter

BRR

Brown rice rate

CR

Competitive ratio

CR_IR

Competitive ratio of Indica rice

CR_JR

Competitive ratio of Japonica rice

ELAI

Efficient leaf area index

GY

Grain yield

HD

Heading date

HMRR

Head mild rice rate

ICI

Intercropping Indica

ICJ

Intercropping Japonica

ICIJ

Indica-Japonica intercropping

IR

Indica rice

JR

Japonica rice

K

Relative crowding index

K_ICI

Crowding index of Indica rice

K_ICJ

Crowding index of Japonica rice

LAI

Leaf area index

LER

Land equivalent ratio

LER_IR

Land equivalent ratio of Indica rice

LER_JR

Land equivalent ratio of Japonica rice

LUE

Land use efficiency

LUC

Land use coefficient

MCI

Monocropping Indica

MCJ

Monocropping Japonica

MD

Maturity date

MRR

Mild rice rate

PGYC

Percent change in grain yield

Pn

Photosynthetic rate

RCBD

Randomized complete block design

SD

Sowing date

SPI

System productivity index

t

Growth period

t_IR

Growth period of Indica rice

t_IR

Growth period of Indica rice

T

Longest growth period

Z_ICI

Planting area of intercropping Indica

Z_IJ

Planting area of intercropping Japonica

Authors’ contributions

J.N. Data curation, investigation, Writing- original draft. J.L. Data curation, investigation. J.Q. Investigation. H. G. Review & editing. T.P. Conceptualisation, supervision, investigation. Q.Z. conceptualization and supervision.

Funding

This work was supported by the Natural Science Foundation of China, China (grant number: 32272209), Key Laboratory of Functional Agriculture, Guizhou Province ([2023]007), Key Laboratory of Molecular Breeding for Grain and Oil crops, Guizhou Province ([2023]008), Congjiang Terraced Wetland Ecosystem Observation and Research Station of Guizhou Province (Qian-Ke-He YWZ[2024]004); Innovative Talent Team in Rice Crop Science and Technology in Karst Mountainous Areas of Guizhou Province (Qian-Ke-He-Platform-talent BQW[2024]001); Xiligongmi Innovative Talent Workstation of Guizhou Province (Qian-Ke-He-Platform-talent KXJZ[2024]038). We also appreciate the help we received from farmers and students.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent of participate

The present study involving plant materials were the local crop varieties produced by Henan Agricultural University, and the experiment and sampling was conducted on the experimental land of Henan Agricultural University.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.