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Article

Crop Productivity, Economic Advantage, and Photosynthetic Characteristics in a Corn-Peanut Intercropping System

1
Yantai Academy of Agricultural Sciences, Yantai 265500, China
2
Yantai Agricultural Technology Extension Center, Yantai 264000, China
3
State Key Laboratory of Crop Biology, Agronomy College of Shandong Agricultural University, Taian 271018, China
*
Authors to whom correspondence should be addressed.
Agronomy 2023, 13(2), 509; https://doi.org/10.3390/agronomy13020509
Submission received: 11 January 2023 / Revised: 30 January 2023 / Accepted: 1 February 2023 / Published: 10 February 2023
(This article belongs to the Section Innovative Cropping Systems)

Abstract

:
Corn-peanut intercropping is an important element of China’s agricultural planting model as it confers ecological benefits and increases yield. The aim of this study was to explore the productivity differences between intercropping and monoculture by using the 13C isotope tracer labelling method. Corn hybrid Denghai 618 (DH618) and peanut variety Huayu 22 (HY22) were used as test materials under three planting methods, single corn, SM; single peanut, SP; and corn-peanut intercropping, IM and IP, respectively, during two growing seasons. The results showed that IM increased yield by 59.7% and 62.3% compared with SM, respectively. IP reduced yield by 31.3% and 32.3% compared with SP, respectively. IM significantly increased the photosynthetic rate, leaf area, 13C assimilation distribution, and dry matter accumulation of summer corn, which led to an increase in the kernel number and grain yield. The decrease in intercropped peanut yield was mainly caused by a decrease in the full-pod rate and number of pods per plant. The decrease in peanut yield did not affect the production of intercropping benefit due to the larger intercropping advantage and land equivalence ratio. Corn-peanut intercropping yielded greater economic benefits than monoculture. These results showed the utility of the peanut-corn intercropping model.

1. Introduction

The rapid industrialization of the agricultural sector is conducive to increased labor productivity and crop yields, meanwhile it also brings many ecological problems, including loss of biodiversity, reduced soil fertility, and increased pollution caused by the intensive use of chemical fertilizers and pesticides [1]. In recent years, the Chinese government has paid more and more attention to the ecological benefits of agriculture, requiring the reduction in the use of fertilizer and pesticide in agricultural production and prohibition of straw burning. To ensure both food security and ecological benefits, it is essential to seek best management practices, which include appropriate cropping systems that can efficiently utilize solar and soil resources with minimum nutrient inputs.
Intercropping is a farming practice involving two or more crop species, or genotypes, growing together and coexisting for a time with a definite row arrangement [2,3]. Compared with its component monocrops, it is reported to deliver pest control, optimize field microclimate, produce similar yields with reduced inputs, pollution mitigation, greater or more stable aggregate food or forage yields per unit area, and complementary use of scarce resources, while N fixation is also very important principles of intercropping [4,5,6]. However, not all intercropping systems provide benefits in terms of all possible metrics. For example, legume-cereal mixtures often provide higher biomass and protein yields than sole cropped cereals [7], and the inability to apply certain herbicides can cause greater weed control issues with intercropping compared to monocrops [8]. When intercropping benefits do occur, they emerge from more complete exploitation of resources, such as solar radiation, water, soil, fertilizers, from beneficial neighbor interactions, and in some cases from continuous soil cover [9,10]. Therefore, it is helpful to improve the intercropping effect by co-allocating crops with different planting types and growing periods, and via unequal plant spacing in the field.
Cereals and legume intercropping have been widely used in the world in virtue of its interspecific promotion and niche complementation among numerous intercropping combinations [11]. Almost all published reports on legume-cereal intercropping documented yield advantages compared with the corresponding monocultures [12,13]. In addition, legume-cereal intercropping is a practical method to conserve soil and to increase economic returns [14,15,16]. Furthermore, the intercropping agroecosystem has greater production stability than conventional monocultures [17,18]. Studies on crop strip intercropping showed that system productivity can be efficiently improved because the demand of intercropping crops for inputs (e.g., N fertilizer and pesticides) is often lower [19].
In China, corn (Zea mays L.) is the first major grain crop, and peanut (Arachis hypogaea L.) is one of the most used oilseed crops, accounting for 30% of the total oilseed production in the country [20]. The Huanghuaihai Plain is a major crop producing region in China. In order to ensure the food security for the increasing population while reducing environmental impacts, intercropping has been widely practiced in this region and can have multiple benefits for food production and environmental sustainability [21]. Corn-peanut intercropping is a typical intercropping combination between grasses and legumes, which can significantly alleviate the competition for land between grain and oil and achieve synchronous increases in the yields of grain crops and oil crops [22,23]. In addition, these systems that can combine the production of oil seeds (peanut) with grain for stable food and oil. According to previous study, the higher efficient use of light was one of the main reasons for the over-yielding mechanisms in corn-peanut intercropping [24]. Corn and peanut, as tall and short plants, can be alternately planted to form an umbrella structure that is conducive to improving light transmittance and light energy interception rates [25,26]. As the crops grew higher, the available space, light intensity, and the photosynthetic rate of functional leaves of the intercropped corn increased significantly more than that of monoculture corn; moreover, intercropping increases the chlorophyll content and changes the chlorophyll composition, which is mainly manifested in the significant increase in the content of chlorophyll and carotenoids prolonged the active photosynthetic duration of functional corn leaves [27]. Thus, the model of crop planting influences photosynthetic characteristics which, in turn, affect crop productivity and stability.
However, yield in corn-peanut intercropping varies from study to study and there is little information on physiological traits, yields, assimilate distributions, and dry matter accumulation characteristics in corn-peanut intercropping system in the Huagnhuaihai Plain. The objectives of this work were (i) to determine the yield and economic benefits associated with corn-peanut intercropping; (ii) to investigate the influence of intercropping on the photosynthetic productivity of corn, and (iii) to evaluate the accumulation and distribution of 13C-photosynthate with the 13CO2 stable isotope tracer to obtain an improved understanding of the effect of intercropping on corn yield. This study will provide valuable information for the adjustment of agricultural structure and sustainable development of agriculture.

2. Materials and Methods

2.1. Experimental Design and Crop Management

This study was conducted at the State Key Laboratory of Crop Biology and the Experimental Farm of Shandong Agricultural University, China (36°11′ N, 117°06′ E, 151 m above sea level) in 2015 and 2016. This region is characterized by brown loamy soils and a temperate continental monsoon climate, with an average annual temperature of approximately 13 °C, an average frost-free period of 195 d, and an average annual precipitation of 697 mm, mainly from June to August. The changes in the climate observed during the corn growing season are shown in Figure 1.
The soil physical and chemical parameters were measured in the top 0–20 cm soil layer before sowing in 2015 according to Page’s method [28] and shown in Table 1. The early maturing corn hybrid Denghai 618 (DH618, a widely planted corn cultivar in China), and the early maturing and high-yielding peanut cultivar Huayu 22 (HY22), were the test crops in this study.
There were three kinds of planting methods that were used, i.e., the sole corn (SM), sole peanut (SP), and corn-peanut intercropping (intercropped corn, IM; intercropped peanut, IP), which were applied in two consecutive years. SP was planted in equally spaced rows with a density of 180,000 holes ha−1; there were two seeds per hole, with a row spacing of 35 cm and plant spacing of 16 cm. The SM planting density was 105,000 plants ha−1, with row spacing of 60 cm and plant spacing of 15.9 cm. For the intercropping system, there was an intercrop comprised of alternating strips of four rows for corn and six rows for peanut. In this intercrop, both corn and peanut were grown on the same piece of ground in the same year and with this row-–ratio design and the two crops covered a similar area which facilitates rotation of the two crops to eliminate continuous peanut obstacles. The corn and peanut were planted at the same density in the intercropping system as used in their respective monocultures. The spacing between crops in the intercropping system was 50 cm, and the bandwidth was 455 cm (Figure 2). The plot size was 6 m in width by 30 m in length in SM, 7 m in width by 30 m in length in SP, and 13.65 m in width by 30 m in length in the corn-peanut intercropping system. The row orientation was north-south, the experimental design was a completely randomized design with three repetitions. Furthermore, the spacing between the single crop system was 300 cm. In the pure crop plots, we discarded the external two rows of both corn and peanut due to potential border effects. To eliminate differences among duplications, six rows of peanut and then several rows of corn were planted at the left of the corn-peanut intercropping system, and four rows of corn and then several rows of peanut were planted at the right of the intercropping system. In both growing seasons, corn and peanut were supplied with 200 and 45 kg N ha−1 in resin–coated urea (43% N), respectively, and both crops were supplied with 100 kg P2O5 ha−1 in calcium superphosphate (12% P2O5) and 120 kg K2O ha−1 in potassium chloride (62% K2O). All N, P, and K fertilizers for both crops were applied as basal fertilizers. Corn and peanut were sown and harvested at the same time; they were sown on 10 June 2015 and 2016 and harvested on 5 October 2015 and 2016. The soil tillage method was shallow tillage (tilled to a depth of 10 cm using a disc harrow with an 89 kW tractor). The previous crop was winter wheat.
Weeds were controlled chemically (refined iso-alachlor, a pre-emergence herbicide can be used for corn and peanuts) before corn and peanut emergence. Diseases and insect pests of corn and peanut were controlled by conventional techniques using an isolation belt spraying machine. Supplementary water was applied during the growing season according to the estimation of weekly plant water demand (evapotranspiration) and precipitation. Actual irrigation was conducted before sowing (75 mm) depending on the amount of precipitation because the precipitation was greater during growth stages in 2015 and 2016.

2.2. Sampling and Measurements

The corn yield was estimated through the average kernel numbers per ear and the average 1000-grain weight, and the peanut yield was calculated by estimating the average pod numbers per plant and the average 100-kernel weight [29].
Corn and peanut intercropping performance was assessed according to the land equivalent ratio (LER):
LER = ( Y i m / Y s m ) + ( Y i p / Y s p )
where Y i m   and Y i p indicate the actual yield of intercropped corn and intercropped peanut, respectively. Y s m and Y s p are the yield of SM and SP, respectively. An LER value > 1 indicates that intercropping is advantageous and LER < 1 indicates that intercropping is disadvantageous.
Intercropping   advantage = Y i ( Y s m × F m + Y s p × F p )
Y i indicates the yield of the intercropping system, and Y i = Y i m + Y i p ; F m and F p represent the proportion of area between the intercropped corn and peanut, respectively.
Economic benefit (USD ha−1) was calculated according to:
Economic   benefit =   Y   ×   P LF   FF SF PF
where Y is yield (kg ha−1), P is grain price (USD ha−1), LF is labor fees and brokerage costs (USD ha−1), FF is fertilizer fees (USD ha−1), SF is seed costs (USD ha−1), and BF is pesticide expenses (USD ha−1). USD is U.S. dollars.
A total of four representative corn plants in each plot were sampled on 43 d (12th leaf stage; V12), 53 d (tasselling stage; VT), 68 d (blister stage; R2), 90 d (dough stage; R4), and 117 d (harvest maturity stage; R6) after sowing, and four representative peanut plants were sampled in each plot on 30 d (beginning peg stage), 58 d (full pod stage), 88 d (full seed stage), and 117 d (harvest maturity stage,) after sowing to determine dry matter. These corn plants (aboveground) and peanut plants (including aboveground, roots, and pods) were dried at 80 °C in a forced-draft oven (DHG-9420A; Bilon Instruments Co., Ltd., Shanghai, China) to a constant weight.
The photosynthetic rate (Pn) was measured with a portable gas exchange system (CIRAS-2, PP Systems, Hitchin, UK) equipped with a square (2.5 cm2) chamber. The photosynthetic photon flux density (PPFD), provided by an internal light source from the leaf chamber, was 1600 μmol m−2 s−1, and the leaf temperature was a relatively constant 30 °C. The measurements were done at the V12, VT, R2, R4, and R6 stage for corn and at the beginning peg, full pod, full seed, and harvest maturity stage for peanut on cloudless days.
A total of ten plants showing similar growth were selected during the corn growing season to determine leaf area index (LAI) during V12, VT, R2, R4, and R6.
LAI = ( Single   plant   leaf   area × plot   number ) / plot   area
The leaf area of peanut was determined by the specific leaf weight method.
S = ( M 1 + M 2 ) ( M 1 S 1 )
where S1 is green blades of a fixed area, M1 is the dry weight of green blades with a fixed area, M2 is the dry weight of the remaining leaf area, and S is the total leaf area.
A total of ten representative plants were selected during the 2015 and 2016 corn silking periods. Their ear leaves were sealed and 13CO2 feeding was carried out immediately to maintain photosynthesis for 60 min. There were five plants that were obtained after 24 h and during R6, and the organs were dried in the oven and weighed with an electronic balance. The 13C abundance was determined by a stable isotope mass spectrometer (ISOPRIME100) and the accumulation and distribution of 13C assimilates in the aboveground organs were calculated.

2.3. Sampling and Measurements Statistical Analysis

Data were analyzed using Microsoft Excel (Microsoft Co., Redmond, WA, USA), SigmaPlot (ver. 11.0; Systat Software, San Jose, CA, USA) and SPSS (ver. 16.0; SPSS Inc., Chicago, IL, USA) software. All the measured and calculated features were analyzed as dependent variables, and cropping treatments were analyzed as fixed factors. Significant differences among means were determined by Duncan’s multiple range test at the 5% level.

3. Results

3.1. Yield and Economy Advantage of Intercropping System

Compared to monoculture, corn-peanut intercropping systems had intercropping advantages in yield and economy (i.e., promoted crop yield and farmers’ income) (Table 2). The effects of year and planting model on yield were significant, while there was no significance between year and planting model. Under the same planting area, IM increased production by 59.7% and 62.3% in 2015 and 2016, respectively, compared with SM, while IP reduced production by 31.3% and 32.3% in 2015 and 2016, respectively, compared with SP. Corn-peanut had the highest economic benefit among all the cropping systems with 385.5 USD ha−1 greater than SM and 585.5 USD ha−1 greater than SP over the two growing seasons. In addition, the intercropping system had an LER value that was greater than that in both growing seasons.

3.2. Yield Composition of Corn and Peanut

Intercropping significantly affected the yield components of corn and peanut (Table 3). The effects of year and planting model on yield components were significant, and the interaction year × fertilization also affected the grain weight. Ear number (expressed per unit area of the whole system) was significantly lower in intercrops than in SM, while kernel number and 1000-grain weight were significantly greater in intercrops than in SM, which indicated that the advantage of intercropping was due mainly to the increase in corn yield per plant. After averaging the two growing seasons, the kernel number and 1000-grain weight of IM were increased by 20.0% and 8.0% compared to SM, respectively. The pod number per plant, 100-pod weight, and percent of plump pod of the peanut grown in intercrops treatment were lower than that in monoculture, which decreased by 2, 12.9, and 28.6% over the two years.

3.3. Dry Matter Accumulation and LAI

IM significantly increased the accumulation of dry matter after anthesis compared with SM, which was more evident during the corn late filling stage (R4–R6). Dry matter accumulation per corn of IM at the R6 stage significantly increased by 20.9% compared with SM in 2015, whereas dry matter accumulation per corn was 16.9% significantly greater in IM compared with SM during 2016 (Figure 3). IP significantly reduced dry matter accumulation per peanut compared with SP in 2015. Dry matter accumulation per peanut at the harvest stage significantly decreased by 13.4% with IP compared with SP, while dry matter accumulation per peanut in 2016 significantly decreased by 11.7% with the former method.
LAI significantly increased by 15.2% with IM at R6 stages during 2015 compared with SM, while there was little difference in 2016 with only a 5.3% increase. The LAI of peanut at the harvest stage significantly decreased by 16.5% with IP during 2015 compared with SP, while the LAI decreased significantly by 13.8% with IP during 2016 compared with SP (Figure 4).

3.4. Net Photosynthetic Rate (Pn)

Intercropping increased the Pn of corn significantly in different growing stages in both seasons (Figure 5). With the development of the growing stage, the Pn of ear leaves of SM and IM showed a single-peak trend, reaching its maximum at R2, and then decreasing. Averaged over the two seasons, the Pn of IM at R2 significantly increased by 6.5% compared with SM. The photosynthetic rate of peanut tended to decrease as growth proceeded. IP significantly reduced the photosynthetic rate of peanut during the entire growth period, which was due to the shading effect of corn, as a high-stalk crop, on the photosynthetic rate of peanut.

3.5. Distribution and Accumulation of Assimilated Matter

Intercropping treatment altered the model of distribution of 13C-photosynthates among different organs (Table 4). At the silking and after 24 h of isotope tracer labelling, the maximum ratio of distribution was recorded in the stem followed by leaves. At R6, the distribution of 13C-photosynthates was mainly concentrated in the grains. Relative to the SM, 13C-photosynthates distribution in grain increased by 3.6% in IM averagely over the two growing seasons.

4. Discussion

Intercropping improved resource acquisition and productivity compared to monoculture [30]. Complementarity is likely as intercropped corn uses N from the soil for growth whilst the legume can rely more on atmospheric N2 fixation for growth. These can be influenced by soil fertility status, spatial planting arrangements, and choice of intercrop components [31]. The main reason for farmers in China to practice intercropping is that it can increase land productivity and profitability [32,33]. This study clearly demonstrated that the planting model affected grain yield significantly and intercropping systems presented advantage over corn or peanut monoculture. The corn-peanut system showed intercropping advantages in yield, economy, and land utilization ratio. Previous studies had also reported beneficial effects of intercropping systems on yield, economy, and the environment [34,35,36,37], which stresses the importance of using intercropping in sustainable agriculture to alleviate pressure in intensive farming systems with high inputs and outputs [38]. In this study, we found that land use efficiency, measured by the LER, varied from 1.15 to 1.16 over the two growing seasons (Table 2). LER values of the intercropping system were larger than 1, indicating that intercropping had greater advantages in the use of environmental resources. Furthermore, intercropping of corn and peanut was found to improve nutrient uptake in both crops compared with sole cropping. The increasing yields were possibly due to mitigating continuous cropping constraints by promoting nutrient uptake as a result of positioned rotation under intercropping [39]. The continuous cropping constraint is a phenomenon that is typified by growth degeneration, yield decreases, and quality deterioration after continuous cropping of the same crop. Under monocultures, both cotton and peanut yields under continuous cropping decreased significantly compared with non-continuous cropping. Crop rotation could reduce the continuous cropping constraints effectively. Corn and peanut rotation have been usually adopted to mitigate the constraints and increase crop productivity [40]. Therefore, intercropping greatly increased land use efficiency, which indicated that corn and peanut intercropping is a compound system with high quality, high yield, and high efficiency. It can not only increase grain yield, but also increase farmers’ income, alleviating the contradiction between grain and oil.
The light interception by the leaf area of a plant and the intensity of CO2 assimilation in the leaves are the core element of increasing plant productivity. Differences in leaf area or intensity of photosynthesis have an important effect on growth and development. Sufficient light is important for high and steady yields, particularly in corn, which is a typical C4 plant [41]. Previous studies reported that the advantage of intercropping was probably derived from high light use efficiency above-ground and nutrients (e.g., N) below-ground [42]. Corn-peanut intercropping can improve the population structure, which make the leaves of corn on different levels acquire appropriate sun radiation, delay the aging of leaves, and increase the chlorophyll content of ear leaves as well as net photosynthetic rate. Similar results were obtained in this study; the ability of intercropped corn to capture sunlight was enhanced, which was manifested by the increased LAI, Pn and dry matter accumulation. However, affected by the shading of corn, the intercropping peanut was under low light for a long time. The improvement of photosynthetic physiology (Pn and LAI) in intercropped corn was related to productivity. This was closely associated with the decreased light compensation point and light saturation point of the functional leaf in intercropped peanut. As a result, the corn yield of the intercropping system was significantly increased, while the pod yield of IP decreased over the 2-year study period. Intercropped legumes probably facilitated the growth of grass by transferring the fixed N [43,44,45], which may be another reason for the increased corn yield in the intercropping system.
An efficient way to assess the contribution of each part of a corn plant to grain yield is by assessing the amount of 13CO2 that is fixed in the plant and transferred to each of its parts, although the total 13C fixed was underestimated in a previous study because the amount of 13C that was lost to the soil was not measured [46]. The results of a 13C tracer study showed that assimilates were mainly concentrated in the grains during the mature period of corn, and that stem and leaf assimilation products were transferred to the grains (Table 4). Under the intercropping system, corn was more assimilated to grain than under the SP system, which laid the foundation for an increase in the intercropped corn yield and had a positive effect on grain filling.
China is one of the largest producers of peanut and corn in the world. Since most major corn growing areas are also the dominant production bases for peanut in the country, corn-peanut intercropping could be an effective method to achieve a simultaneous harvest of corn and peanut [47]. In our study, intercropping improved crop colony structure, enhanced the land utilization ratio, and enhanced resistance at the group level; it also reduced fertilizer and had remarkable economic (Table 2), environmental, and social benefits. More and more benefits of the corn-peanut intercropping system could be gained by farmers because this system combines the production of oil seeds (peanut) with grain. The net profit is also greater because of the significant increase in productivity without additional input. Intercropping is thus valuable for food security at the national level and helps to improve the market competitiveness of agricultural products. Our next step will be to conduct detailed studies on the effects of the intercropping system on the soil microenvironment and community structure.

5. Conclusions

Planting models affect crop yields significantly. Corn played an important role in determining the yields in the intercropping system; it was the superior crop and had a stronger ability to obtain resources than peanut when intercropped. Compared to conventional monoculture of corn, the corn-peanut intercropping had significant advantages in yield and land utilization ratio due to the improved canopy structure of crop population, which make the leaves of corn on different levels receive appropriate sun radiation, and the optimized distribution and utilization of assimilation during the later stages of crop production. In contrast, the model of the intercropped peanut method significantly decreased yield compared with the model of sole peanut, primarily because of the long-term exposure to corn shading. Corn-peanut intercropping systems yielded greater economic benefits and land use efficiency than monoculture systems.

Author Contributions

Conceptualization, S.D. and D.S.; methodology, Y.L.; validation, Y.L. and D.S.; investigation, Y.L., L.W., B.Z., P.L., J.Z. and S.D.; writing-original draft preparation, Y.L. and D.S.; writing-review and editing, Y.L., D.S. and S.D.; funding acquisition, S.D. and D.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Modern agricultural industrial Technology System construction Project of Shandong Province of China (SDAIT-02-15); Sci-tech Development Program of Yantai of China (2021NYNC012);the National Key Research and Development Program of China (2017YFD0301001), the Natural Science Foundation of China (31301274 and 31171497) and the Shandong “Double Tops” Program (SYL2017XTTD14).

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Annual meteorological data from 2015 to 2016.
Figure 1. Annual meteorological data from 2015 to 2016.
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Figure 2. Sketch map of the corn-peanut intercropping model.
Figure 2. Sketch map of the corn-peanut intercropping model.
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Figure 3. Effects of planting model on dry matter accumulation of corn and peanut. Note: PS, pegging stage; PSS, pod setting stage; PFS, pod filling stage; HS, harvest stage.
Figure 3. Effects of planting model on dry matter accumulation of corn and peanut. Note: PS, pegging stage; PSS, pod setting stage; PFS, pod filling stage; HS, harvest stage.
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Figure 4. Effects of planting model on the LAI of corn and peanut. Note: PS, Pegging stage; PSS, Pod setting stage; PFS, Pod filling stage; HS, Harvest stage.
Figure 4. Effects of planting model on the LAI of corn and peanut. Note: PS, Pegging stage; PSS, Pod setting stage; PFS, Pod filling stage; HS, Harvest stage.
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Figure 5. Effects of planting model on the net photosynthetic rate (Pn) of corn and peanut. Note: PS, pegging stage; PSS, pod setting stage; PFS, pod filling stage; HS, harvest stage.
Figure 5. Effects of planting model on the net photosynthetic rate (Pn) of corn and peanut. Note: PS, pegging stage; PSS, pod setting stage; PFS, pod filling stage; HS, harvest stage.
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Table 1. The soil physical and chemical parameters in the top 0–20 cm soil layer in the experimental plots.
Table 1. The soil physical and chemical parameters in the top 0–20 cm soil layer in the experimental plots.
pHOrganic Matter
(g kg−1)
Total Nitrogen
(g kg−1)
Available Phosphorus (mg kg−1)Available Potassium
(mg kg−1)
6.35 ± 0.0711.22 ± 0.520.91 ± 0.0247.18 ± 1.6784.24 ± 2.18
Table 2. Crop yield, economic benefit, intercropping advantage, and land equivalent ratio (LER) in different crop systems at harvest of both growing seasons.
Table 2. Crop yield, economic benefit, intercropping advantage, and land equivalent ratio (LER) in different crop systems at harvest of both growing seasons.
YearPlanting ModelYield EconomyIntercroppingLand Equivalent
(t ha−1)(USD ha−1)Advantage (t ha−1)Ratio (LER)
CornPeanutCornPeanut
2015Monoculture10.68 ± 0.20 a4.37 ± 0.18 a22341943
Intercropping8.62 ± 0.18 b1.49 ± 0.07 b21134662.58 ± 0.01 a1.15 ± 0.01 a
2016Monoculture10.04 ± 0.21 a4.34 ± 0.13 a20271918
Intercropping8.23 ± 0.17 b1.46 ± 0.11 b19924412.50 ± 0.03 a1.16 ± 0.01 a
ANOVAYear (Y)nsns
Planting model (PM)****
Y × PMnsns
Data are presented on a basis of per hectare monoculture/intercropping area. Cost: Labor 436.68 USD ha−1 for corn and 545.85 USD ha−1 for peanut, Pesticides and herbicides 101.9 USD ha−1 for corn and 94.6 USD ha−1 for peanut, corn seed 1.90 USD kg−1, peanut seed 0.87 USD kg−1, resin-coated urea 480.3 USD t−1, calcium superphosphate 109.2 USD t−1, potassium chloride 320.2 USD t−1; procurement price: corn grain 0.31 USD kg−1 in 2015 and 0.25 USD kg−1 in 2016, peanut pod 0.73 USD t−1 in both years. Note: Different letters in the same column within each year indicate significant differences at the 5% probability level. ns: non-significant, ** represent significance at p ≤ 0.01.
Table 3. Effect of planting model on the yield components of corn and peanut.
Table 3. Effect of planting model on the yield components of corn and peanut.
YearPlanting ModelCorn StripPeanut Strip
Ear Number
(No. m−2)
Kernel Numbers
(No. Ear−1)
1000-Grain Weight (g)100-Kernel Weight (g)Pods Per PlantPercent of Plump Pod (%)
2015Monoculture8.65 ± 0.15 a373.97 ± 9.05 b217.80 ± 3.35 b73.52 ± 6.35 a27.34 ± 1.41 a64.26 ± 3.21 a
Intercropping5.12 ± 0.09 b454.34 ± 8.96 a238.94 ± 2.89 a66.04 ± 4.21 b26.32 ± 2.08 a45.48 ± 4.28 b
2016Monoculture8.23 ± 0.14 a344.95 ± 11.12 b207.15 ± 2.02 b64.84 ± 4.44 a26.21 ± 1.97 a60.47 ± 5.05 a
Intercropping4.84 ± 0.07 b408.61 ± 10.87 a219.96 ± 2.58 a54.56 ± 3.95 b26.05 ± 1.85 a43.69 ± 2.97 b
ANOVAYear (Y)nsnsnsns***
Planting mode (PM)**********
Y × PMnsns**nsns
Data are presented on a basis of per hectare monoculture/intercropping area. Note: Different letters in the same column within each year indicate significant differences at the 5% probability level. ns: non-significant, * and ** represent significant at p ≤ 0.05 and p ≤ 0.01, respectively.
Table 4. Effects of planting model on 13C-photosynthates distribution in different organs (%) at 24 h after labelling (24 h) and physiological maturity (R6) in both of the growing seasons.
Table 4. Effects of planting model on 13C-photosynthates distribution in different organs (%) at 24 h after labelling (24 h) and physiological maturity (R6) in both of the growing seasons.
YearGrowth StagesTreatment13C-photosynthates Distribution in Different Organs (%)
Ear LeafStemOther LeavesCobEar BractsTasselGrain
2015DASSM3.60 ± 0.08 b50.32 ± 0.05 b28.55 ± 0.04 a 5.91 ± 0.03 a9.65 ± 0.03 b1.97 ± 0.01 a -
IM4.14 ± 0.07 a52.85 ± 0.02 a22.96 ± 0.09 b 4.56 ± 0.02 b13.85 ± 0.04 a 1.64 ± 0.02 b-
R6SM2.50 ± 0.05 a18.17 ± 0.02 a11.73 ± 0.08 a7.64 ± 0.03 a5.69 ± 0.02 a0.42 ± 0.01 b53.86 ± 0.01 b
IM2.06 ± 0.04 b17.20 ± 0.03 b10.81 ± 0.05 b7.89 ± 0.04 a5.91 ± 0.01 a0.76 ± 0.01 a55.37 ± 0.02 a
2016DASSM3.87 ± 0.10 b50.97 ± 0.06 b28.23 ± 0.01 a3.56 ± 0.04 b11.73 ± 0.05 b1.64 ± 0.03 a-
IM4.14 ± 0.02 a52.85 ± 0.10 a23.52 ± 0.02 b4.55 ± 0.03 a13.25 ± 0.03 a1.68 ± 0.02 a-
R6SM1.88 ± 0.01 a20.03 ± 0.04 a12.03 ± 0.04 a7.28 ± 0.04 b4.52 ± 0.08 a1.65 ± 0.04 a52.63 ± 0.05 b
IM1.57 ± 0.01 b18.69 ± 0.01 b10.77 ± 0.05 b8.13 ± 0.02 a4.61 ± 0.04 a1.26 ± 0.01 b54.98 ± 0.15 a
Note: Different letters in the same column within each year indicate significant differences at the 5% probability level.
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Li, Y.; Wang, L.; Zhao, B.; Liu, P.; Zhang, J.; Dong, S.; Shi, D. Crop Productivity, Economic Advantage, and Photosynthetic Characteristics in a Corn-Peanut Intercropping System. Agronomy 2023, 13, 509. https://doi.org/10.3390/agronomy13020509

AMA Style

Li Y, Wang L, Zhao B, Liu P, Zhang J, Dong S, Shi D. Crop Productivity, Economic Advantage, and Photosynthetic Characteristics in a Corn-Peanut Intercropping System. Agronomy. 2023; 13(2):509. https://doi.org/10.3390/agronomy13020509

Chicago/Turabian Style

Li, Yanhong, Lei Wang, Bin Zhao, Peng Liu, Jiwang Zhang, Shuting Dong, and Deyang Shi. 2023. "Crop Productivity, Economic Advantage, and Photosynthetic Characteristics in a Corn-Peanut Intercropping System" Agronomy 13, no. 2: 509. https://doi.org/10.3390/agronomy13020509

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