Next Article in Journal
Genome-Wide Identification and Expression Analysis of Bx Involved in Benzoxazinoids Biosynthesis Revealed the Roles of DIMBOA during Early Somatic Embryogenesis in Dimocarpus longan Lour
Next Article in Special Issue
Planting Geometry May Be Used to Optimize Plant Density and Yields without Changing Yield Potential per Plant in Sweet Corn
Previous Article in Journal
PGPB Consortium Formulation to Increase Fermentable Sugar in Agave tequilana Weber var. Blue: A Study in the Field
Previous Article in Special Issue
Evaluation of the Productivity and Potential Utilization of Artemisia dubia Plant Biomass for Energy Conversion
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 13
Issue 10
10.3390/plants13101372
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Comprehensive Assessment of the Effect of Multi-Cropping on Agroecosystems

by
Jovita Balandaitė
*,
Kęstutis Romaneckas
,
Rasa Kimbirauskienė
and
Aušra Sinkevičienė
Agronomy Faculty, Agriculture Academy, Vytautas Magnus University, Studentu Str. 11, 53361 Akademija, Kaunas District, Lithuania
*
Author to whom correspondence should be addressed.
Plants 2024, 13(10), 1372; https://doi.org/10.3390/plants13101372
Submission received: 28 March 2024 / Revised: 2 May 2024 / Accepted: 9 May 2024 / Published: 15 May 2024
(This article belongs to the Special Issue Sustainable Mechanisms for Crop Development, Productivity and Quality Promotion)
Browse Figures
Versions Notes

Abstract

:
Multi-cropping is becoming an increasingly popular technique in agriculture to tackle major and complex agroecosystem problems such as biodiversity and soil fertility loss, erosion and degradation, increased greenhouse gas emissions, etc. Comprehensively assessing the impact of multi-cropping intensity on agroecosystems is a new and still under-researched approach that can provide a better understanding of the impact of individual indicators on the overall functioning of biodiverse agroecosystems. Data from a stationary field experiment using multi-cropping at the Vytautas Magnus University Experimental Station between 2020 and 2022 were used to carry out this study. The study included maize, hemp, and faba bean as single, binary, and ternary crops. A complex assessment approach (CEI value) was used to determine the impact of these crops on the agroecosystem, the interrelationships between the main indicators, and the strength of their effects. It was found that the ternary maize–hemp–faba bean crop had the most positive effect on the agroecosystem. The effectiveness of other crops was 2 to 35% less. The lowest value was calculated for the maize–faba bean crop.

1. Introduction

Intensive farming is still popular worldwide and in Lithuania, but it requires large investments without considering the problem of environmental pollution to maximize yields and profits [1]. Multi-cropping allows for the development of sustainable agriculture, in which high yields can be achieved with less investment in terms of money and time, and, with the right choice of crops, on less fertile soils. For example, 70–90% of faba beans in Latin America are grown as intercrops with maize or potato [2].
Multi-cropping can involve several agricultural crops that are grown in the same field but differ in their biological and agrotechnical characteristics, as well as the length of their growing season [3]. Studies have shown that mixed cropping systems have a higher yield potential than individually grown crops [4]. Maize is a major source of food for humans and livestock in many developing countries [5]. As the climate warms, maize will be increasingly grown in Lithuania to produce not only grain but also green biomass [6]. Hemp is mostly grown for its fiber or seeds, which are rich in starch, protein, and oil [7]. Hemp produces a sufficiently high biomass and can therefore be used for energy purposes [8]. Faba beans are a source of protein; thus, their nutritional and feed value is of particular importance [9]. One of the most important functions of these crops is to fix atmospheric nitrogen, which helps maintain soil fertility. Faba beans can adapt to a wide range of climatic conditions, as shown by their worldwide distribution [10].
Most multi-crops are annuals, which have clear advantages over perennials; for example, annual crops, due to their short growing season, enable farmers to produce more goods to meet market demand [11]. In addition to their main production, these crops also produce by-products, such as harvesting residues that can be used for energy purposes or in animal husbandry. Growing multiple crops in the same field at the same time can lead to more sustainable agricultural systems, making it possible to increase biodiversity; reduce damage from diseases, pests, and weeds; reduce the need for mineral fertilizers; prevent the effects of waterlogging; and maintain the fertility and quality of the soil [12,13]. Purpose-grown multi-cropping systems (agroecosystems) offer the potential to increase organic carbon, nutrient content, soil bioactivity, etc. [14]. Multi-cropping is a valuable tool for nutrient management in crop rotations, as nutrients, such as nitrogen, taken up by one plant can be utilized by other plants in the system. It has been shown that more root biomass is produced by multi-cropping compared to single-cropping. This is due to interspecific synergy between plants [15]. Multi-cropping also stabilizes and restores soil fertility by reducing the leaching of nutrients into deeper soil layers and protects the soil from wind and water erosion [14]. Multi-cropping affects the whole soil biota by increasing the abundance, diversity, and activity of soil microorganisms [16]. When multiple crops are grown, plants compete with weeds and use solar energy more efficiently [17,18]. Regardless of all the positive aspects of multi-cropping, when following the principles of sustainable agriculture, it is necessary to gradually move to non-arable farming systems and thus increase environmental protection [19].
In our study, in a multi-functional maize–hemp–faba bean agroecosystem, the role of maize is to produce abundant biomass, the role of hemp is to produce biomass and protect against diseases and pests, and the role of faba bean is to provide ecological services. The question arises as to which agroecosystem—single, binary, or ternary—is the most efficient.
The aim of this study was to perform a comprehensive assessment in order to reveal the impact of crop diversification on agroecosystems and the interrelationships between the indicators assessed and to ascertain which indices have the greatest impact on the agroecosystem and at what level of the agroecosystem.

2. Results and Discussion

To produce as much crop biomass per area unit as possible with minimal damage to nature, many authors recommend multi-cropping. To achieve maximum results, it is important to take advantage of the strengths of each crop grown in a multifunctional crop. This involves selecting the appropriate combinations, placement, and proportions of crop species [20]. A comprehensive multi-crop agroecosystem evaluation model is presented in Figure 1.

2.1. Level 1: Total Dried Crop Biomass

The total dried crop biomass (system level 1) scores did not reach the assessment threshold. The highest score was obtained for the ternary crop of maize, hemp, and faba bean. There was also a marked advantage in terms of dried biomass scores for binary crops over single crops (Figure 2). The results show that the dried biomass of faba bean decreased at higher temperatures (r = −0.47; p > 0.05) because faba bean is a moderate-climate crop [22]. Tahir et al. [23] indicated that growing faba bean as an intercrop increases the biomass productivity of the crop and improves yield quality. Cai et al. [24] noted that faba bean increases the concentration of nutrients at the soil surface, leading to increased productivity of multi-crops. In their experiment, when maize was grown with rice and vetch, a significant increase in soil organic carbon was found, which was 4.12% higher than when maize was grown with rice (p < 0.05).
Crop productivity in any type of cropping system relies primarily on the interception of photosynthetically active radiation (PAR) at the crop canopy and the conversion of intercepted radiation into biomass, known as radiation use efficiency (RUE) [25]. Photosynthetically active radiation scores at the soil surface were found to be above the assessment threshold for hemp in a single crop and in a binary crop with maize. The assessment scores for single-cropped maize and faba bean did not reach the assessment threshold but were close to it.
The highest total crop density scores at the end of the vegetative season were obtained for the binary maize–faba bean and hemp–bean crops and the ternary crop.
The average crop height was highly affected by the cultivation of single crops, as the scores for single crops of maize and hemp were well above the assessment threshold, whereas the score for the single faba bean crop was significantly lower (Figure 2).
A correlation analysis by Litvinova et al. [26] revealed a significant effect of maize height on green biomass yield. They found that as maize height increased, the cob biomass decreased, which significantly decreased the total green biomass.
The precipitation assessment scores were below the assessment threshold for single crops of maize and hemp and the ternary crop. According to Birthal et al. [27], multi-cropping has a positive effect on the distribution of precipitation over the soil surface, and thus soil moisture is retained longer.
The scores for the crop development indicators were unevenly distributed. The leaf chlorophyll index scores were above the assessment threshold due to the influence of the ternary crop. In the case of single and binary crops, the leaf chlorophyll index scores were below the assessment threshold. The leaf assimilated area scores for the ternary and binary crops were not above the assessment threshold, except for the binary maize and faba bean crop, for which the scores were higher and above the assessment threshold.
At system level 1, the highest CEI values were found for the ternary crop, proving that the ternary crop had the greatest impact on the dried canopy biomass (Figure 2).

2.2. Level 2: CO2 Emission from the Soil

Soil respiration is a good proxy for soil biological activity, as it releases carbon dioxide (CO2) to the atmosphere because of the decomposition of soil organic matter [28]. Increased CO2 concentrations lead to increased photosynthesis and thus higher crop biomass [29].
In our experiment, regarding the agrobiological characteristics of the soil under multi-cropping, the single hemp crop, and the binary maize–hemp crop had the greatest influence. The assessment scores for these crops were above the threshold. The CO2 score for the single maize crop was very close to the assessment threshold but did not exceed it (Figure 3). Hu et al. [30] found that integrating a binary maize–wheat crop with ploughless agriculture could effectively increase crop yield while reducing CO2 emissions from the soil and improve water use efficiency in arid areas. The scores for our tested binary crops with faba bean did not reach the assessment threshold. A study by Lupwayi et al. [31] found that, due to the ability of faba bean to fix atmospheric nitrogen, there were lower greenhouse gas emissions from the soil compared to single crops or diversified crops without faba bean.
In terms of the effect of average daily air temperature, the scores for the binary crops were above the assessment threshold. The highest precipitation effect scores were obtained for the single faba bean crop and the binary crops with faba bean (Figure 3).
The cultivation of binary crops had a greater effect on the agrophysical properties of the soil. The highest soil megastructure content scores were obtained with the single faba bean crop and the ternary crop, which were well above the assessment threshold. The soil macrostructure score was above the assessment threshold in the case of the binary maize–hemp crop. However, it should be noted that the macrostructure score for the ternary crop was also very close to the assessment threshold. Similar results were obtained by Rudinskienė, who reported that the macroaggregate content was positively affected by growing caraway in binary and ternary crops. According to the integrated assessment system, the indicators of these crops were above the assessment threshold [32,33]. In our experiment, the microstructure content scores was also influenced by the cultivation of binary crops, but these scores were only slightly above the assessment threshold, and the score for the binary crop of maize and hemp was equal to the threshold. The lowest microstructure content score was obtained with the single faba bean crop. Li et al. [34] carried out a meta-analysis of 1924 observations and reported that compared to single-cropping, multi-cropping led to increased soil macroaggregate content, while microaggregate content decreased. In our experiment, it was found that increasing the amount of megastructure in the soil decreased the amount of microstructure (r = −0.80; p < 0.01), while increasing the amount of macrostructure had an influence on increasing the microstructure (r = 0.46; p < 0.05) [22].
There was an uneven distribution of scores for soil aggregate stability. The highest soil aggregate stability scores were obtained for the single crops of maize and hemp and the binary crop of hemp–faba bean. The score for the ternary crop on the soil aggregate stability was close to, but not above, the assessment threshold. More abundant and dense crop roots improve soil stability; Hauggaard-Nielsen et al. [16] noted that interactions between crops and competition between species promote crop rooting, and the cultivation of multi-crops has a positive effect on the stability of the soil structure.
CEI calculations showed that the ternary crop was the most effective for the retardment of gas respiration.

2.3. Level 3: Total Number of Weeds at the End of the Vegetative Season

As well as increasing the productivity of the total crop biomass per unit area, intercropping protects the main crop from the spread of weeds, diseases, and pests as biodiversity increases. Cover crops and intercrops are fast-growing and therefore able to compete well with weeds [35,36]. It should be noted that when assessing the weediness of a crop, the reverse principle of the comprehensive assessment system applies, i.e., high CEI values take on a negative meaning and indicate higher weediness of the crop.
In our experiment, binary and ternary crops had the greatest effect on reducing the number of weeds. The lowest weed scores were observed in the binary maize–hemp and maize–faba bean crops and the ternary crop. The total weed score was above the assessment threshold for the single maize crop and the score for the single faba bean crop was very close to the threshold (Figure 4).
The advantage of binary crops with faba bean was established by a comprehensive assessment of average daily air temperature. The assessment scores for the binary crops were significantly above the assessment threshold. In the case of the single faba bean crop, the precipitation distribution score was the highest above the threshold. Our pilot study showed that faba bean canopy height was mainly dependent on precipitation rates (r = 0.42; p > 0.05), as precipitation was scarce during the year of the study [22].
The highest crop density scores, which were above the assessment threshold, were obtained for the binary hemp and faba bean crop and the ternary crop. The lowest crop density score was obtained for the single maize crop. The cultivation of the single maize and hemp crops and the binary maize and hemp crop had the greatest influence on increased crop height. These crops had the highest evaluation scores, which were above the evaluation threshold. The lowest crop height assessment score was for the single faba bean crop. Livingstone et al. [37] reported that hemp sown at lower densities produced thicker and taller stems, increasing the overall green biomass of the crop. Similar results were obtained by Schafer et al. [38], showing that a denser hemp crop led to longer stems.
The scores for the assessment of radiation at the soil surface were not evenly distributed. For this indicator, single crops had an advantage over the ternary crop. The lowest radiation scores were obtained for the binary maize and hemp crop with faba bean intercropping and the ternary crop. The highest scores were obtained for single crops and the binary maize and hemp crop.
In terms of soil agrochemical properties, the scores were unevenly distributed, but there was a marked advantage of single crops over binary and ternary crops. The highest scores for total nitrogen change were found for all single crops and the binary hemp and faba bean crop. The opposite results were obtained by Rudinskienė [32], who reported that the influence of binary and ternary crops led to a significant increase in total nitrogen above the assessment threshold. The mobile phosphorus change scores were very similar for all single crops, as well as the binary and ternary crops, and the scores were very close to the assessment threshold, although they did not reach it, except for the single crop of maize, which scored well above the threshold. The scores for the change in mobile potassium for all single, binary, and ternary crops were either above or very close to the assessment threshold. Similar trends were observed for the change in mobile magnesium. Vanino et al. [39] found that crop diversification improved soil quality. In an experiment, they found increased soil organic carbon, nitrogen, and phosphorus with multi-cropping.
As in the previous level, the ternary crop had the least effect on weed number. This means that using ternary crops may be an effective method to limit the spread of weeds in agroecosystems.

2.4. Level 4: Total Weed Dried Biomass at the End of the Vegetative Season

The scores for weed competition showed that the binary and ternary crops had an advantage over the single crops. In the case of dried weed biomass, the evaluation scores were not above the evaluation threshold, except for the single faba bean crop. The decreased dried weed biomass was positively influenced by the cultivation of the binary maize and hemp and maize and faba bean crops and the single hemp crop, as these had the lowest evaluation scores. The cultivation of binary and ternary crops had a positive effect on reducing the weed score (Figure 5).
The crop density scores were above the assessment threshold for the binary maize and hemp crop with faba bean intercropping and the ternary crop. The cultivation of single maize and hemp crops influenced the lowest crop density scores. The average height of the crop showed the opposite results, with the highest scores for the single crops of maize and hemp. It was found that the maize grew to a lower height at higher temperatures (r = −0.45; p > 0.05) [22].
The precipitation scores did not reach the assessment threshold for the single maize and hemp crops and the ternary crop. Higher average daily air temperatures had a positive effect on the growth of all binary crops and the ternary crop.
When assessing the agrochemical properties of soils under multi-cropping, the total nitrogen, mobile phosphorus, potassium, and magnesium scores for single crops tended to be above the assessment thresholds and were higher compared to the scores for binary and ternary crops. Among the multi-crops, only the binary hemp and faba bean crop stood out, with scores above or close to the assessment threshold. The soil macronutrient scores for the ternary crop and the binary maize and hemp crop were below the threshold.
According to the CEI value, the ternary crop had the lowest impact on increasing weed biomass; in other words, the ternary crop stopped weed biomass growth.

2.5. Comprehensive Overall Assessment of All Four Levels

In the case of total crop dried biomass, the scores were unevenly distributed and did not reach the assessment threshold. The score for the ternary crop, although it did not reach assessment threshold, was close to it. The scores for the binary crops ranged from 2.22 to 2.61, and the scores were lowest for the single crops.
The highest CO2 emission scores, which were above the assessment threshold, were obtained for the single crop of hemp and the binary crop of maize and hemp. The assessment score for the single maize crop was close to the threshold (Figure 6).
The most positive effects on weed numbers and dried biomass were observed with the single hemp crop and the binary maize–hemp and maize–faba bean crops. These crops had the lowest evaluation scores, which were within the evaluation threshold. In terms of the number of weeds and their dried biomass, the highest scores, which were above or close to the threshold, were obtained for the single maize and faba bean crops. Slightly lower scores, but close to the threshold, were obtained for the ternary crop and the binary hemp and faba bean crop. Thus, the cultivation of these crops had a negative effect on weediness.
The overall CEI value showed that the ternary crop had the best results or the most effective results. The study showed that assessing the impact of multi-cropping on an agroecosystem at four main levels provides a clearer understanding of the impact of the set of indicators on the overall functioning of the agroecosystem. Such an assessment framework can help decision-makers determine how best to implement multifunctional agriculture to maintain or increase yields and ecosystem service provision when considering alternative strategies for the development of new cropping systems [39]. It should be noted that the studies conducted and calculations made to assess the effect of multi-cropping were carried out under arable farming conditions. In conservation agriculture, under no-till or simplified conditions, CEI values may differ, which requires further field research.

3. Materials and Methods

3.1. Site Description

The field experiment was carried out in 2020–2022 at the Experimental Station of Vytautas Magnus University Agriculture Academy (coordinates: 54°53′7.5″ N 23°50′18.11″ E). The soil of the experimental field was a deeper gleyic saturated loam (45.6% sand, 41.7% silt, 12.7% clay) Planosol (Endohypogleyic-Eutric Planosol-Ple-gln-w) [40]. Soil pHHCl varied from 7.3–7.8; total nitrogen content was 0.08–0.13%; humus content was 1.5–1.7%%; available phosphorus content was 189–280 mg·kg−1; available potassium content was 97–118 mg·kg−1; available sulfur content was 1.2–2.6 mg·kg−1; and available magnesium content was 436–790 mg·kg−1. The microrelief was levelled and the water regime was regulated by closed drainage.
In 2020, the average daily air temperature and precipitation during the vegetative season were close to the long-term average (since 1974). In 2021, the air temperature was high, and the distribution of precipitation was very uneven, as there was too little moisture in the middle of the vegetative season and not enough at the end. In 2022, the end of the vegetative season was unusually dry with high temperatures (Table 1).

3.2. Experimental Design and Agricultural Practice

There were 7 experimental treatments: single crops of maize (1), hemp (2), and faba bean (3); binary crops of maize and hemp (4), maize and faba bean (5), and hemp and faba bean (6); and a ternary crop of maize, hemp, and faba bean (7). The initial size of the plots was 8 m2. A total of 21 plots were investigated in the experiment. Table 2 shows the grouping of crops, the treatments, and their abbreviations.
According to the sowing plan, 50 cm row spacing was maintained when sowing a single row of maize, hemp, or faba bean. Before the experiment was set up, sown oats (Avena sativa) were grown on the site. After oat harvesting, straw was disked with a Väderstad Carrier 300 disk harrow (Väderstad AB, Väderstad, Sweden) and ploughed after 2 weeks with a Gamega PP-3–43 plough with semi-helical ploughshares (Gamega Ltd., Garliava, Lithuania). In the spring of each year of the experiment, when the soil reached the right moisture content, it was cultivated to a depth of 3–4 cm with a Laumetris KLG-3.6 seedbed cultivator (Laumetris Ltd., Keleriškės village, Lithuania)). Subsequently, the plots were formed and fertilized with NPK 15:15:15 (200 kg ha−1) in the first year and NPK 5:15:30 + 5S (200 kg ha−1) in the second and third years of the experiment. Maize (Zea mays L.) (Pioneer hybrid P8105), hemp (Cannabis sativa L.) (variety Austa SK), and faba bean (Vicia faba L.) (variety Vertigo) were sown manually in a continuous manner in the experimental plots as single, binary, and ternary crops according to a predetermined sowing scheme. After the weeds had germinated in abundance, the inter-rows were mowed twice using a hand hoe weeder. Synthetic pesticides were not used during the experiment. The agro-techniques of the experiment are well described by Balandaitė [22].

3.3. Methods and Analysis

3.3.1. Soil Agrochemical Properties

In each experimental year after crop harvesting, 0–25 cm layer soil samples were taken for macronutrient evaluation. Laboratory analyses were conducted to determine the levels of the main macro-elements (N, P, K, and Mg) and the pH of the soil. The analyses were carried out at the Agrochemical Research Laboratory of the Lithuanian Centre for Agriculture and Forestry.
Soil structure and stability. Soil samples were collected with a shovel after sowing the crops before inter-row mowing from 0–25 cm soil layer. A Retsch sieving apparatus (Retsch Lab Equipment, VERDER Group, The Netherlands) and a set of sieves were used to determine the soil structure. The water stability (wet sieving) of soil aggregates was determined by the Retsch wet sieving device from a previously dry sieved soil fraction of 1–2 mm. The results of the tests are expressed as percentages [41].
CO2 concentration and emissions. These parameters were determined by infrared gas analyzer (IFGA). An LI-8100A portable soil respiration system with an 8100–103 camera was used. A 20 cm diameter ring was hammered into each plot in the spring and 3 measurements were taken: at the beginning, in the middle, and at the end of the crop vegetative season.
Photosynthetically active radiation. Tests were carried out during the vegetative season at the beginning of faba bean flowering. Photosynthetically active radiation (PAR) was measured with an HD 9021 RAD/PAR radiometer (FAR E m−2, 400–700 nm). PAR was measured in different arcs of the crop: at the ground surface, at one-half height, and above the crop (background). This indicator is expressed as a percentage of background irradiance [22].
Crop density. At the end of the vegetative season, crop density was evaluated by determining the productivity of multiple crops. Density was evaluated at a minimum of 5 locations in the plot, in a 0.5 m longitudinal row. An average sample was taken. The crop density is given as plants per m2.
Crop development indicators. These were determined in the second half of the vegetative season by assessing the chlorophyll index and leaf assimilative area. The leaf assimilative area (cm2) was determined using a Win Dias leaf area meter (Delta-T Devices Ltd., Cambridge, UK). The chlorophyll index of the leaves was measured with a CCM-200 Plus chlorophyll meter.
Crop biometric and productivity indices. These were measured at harvest time to assess crop height and dried biomass. A total of 36 spots were generated for the study. The biomass samples were dried in a thermostat at 105 °C to constant weight [42].
Weed flora. This parameter was determined by assessing the number of weeds at the end of the crop vegetative season. The number of weeds (m−2) and the dried biomass (g m−2) at the end of the vegetative season were studied. Weeds were uprooted, dried to air-dry biomass, and weighed, and a botanical analysis of species composition was performed [43].
The variations in the indices (variables) described above and the units of measurement are presented in Table 3.

3.3.2. Statistical Analysis

Correlation and regression analyses of the data were carried out using the the statistical software package SYSTAT, version 10 [44]. A comprehensive evaluation of the multi-cropping effect on the agroecosystem was carried out based on the methodologies of Lohmann [45] and Heyland [46]. An example of the CEI calculations is shown in Supplementary Materials, Table S1 from reference [21].

4. Conclusions

A comprehensive assessment of the main indices (variables) in a multi-crop agroecosystem found that in terms of total dried crop biomass, the effects of ternary and binary crops with maize and hemp on the agroecosystem were the highest. The assessment of total weed numbers and dried weed biomass showed that the scores for indices of the binary hemp and faba bean crop were significantly above the assessment threshold, indicating it had an advantage compared to single and multi-crops. The assessment of CO2 emissions showed that the binary crops had the greatest impact on the agroecosystem.
The calculation of CEI showed that the ternary maize–hemp–faba bean crop had the least impact on gas emissions and increased weed abundance (levels 2–4) and the greatest effect on total dried crop biomass capacity (level 1). A comprehensive assessment of the effect of all four system levels on the agroecosystem showed 2–35% higher effectiveness of the ternary crop.

Author Contributions

Conceptualization, K.R. and J.B.; methodology, K.R. and J.B.; software, A.S., J.B. and R.K.; validation, A.S., R.K. and K.R.; formal analysis, J.B., A.S. and R.K.; investigation, K.R., J.B., R.K. and A.S.; resources, J.B.; data curation, A.S., R.K. and J.B.; writing—original draft preparation, J.B., R.K., A.S. and K.R.; writing—review and editing, K.R., R.K., J.B. and A.S.; visualization, J.B. and A.S.; supervision, K.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest. The funder had no role in the design of the study, analyses, or writing of the manuscript.

References

  1. Scheper, J.; Badenhausser, I.; Kentelhardt, J.; Kleijn, D. Biodiversity and pollination benefits trade off against in an intensive farming system. Proc. Natl. Acad. Sci. USA 2023, 120, e2212124120. [Google Scholar] [CrossRef] [PubMed]
  2. Brooker, R.W.; Bennett, A.E.; Cong, W.-F.; Daniell, T.J.; George, T.S.; Hallett, C.H.; Iannetta, P.; Jones, H.; Karley, A.; Li, L.; et al. Improving intercropping: A synthesis of research in agronomy, plant physiology and ecology. New Phytol. 2015, 206, 107–117. [Google Scholar] [CrossRef] [PubMed]
  3. Gliessman, S.R.; Rosemeyer, M. The Conversion to sustainable Agriculture: Principles, Processes and Practices; University of California: Oakland, CA, USA, 2010; p. 352. [Google Scholar]
  4. Maitra, S.; Hossain, A.; Brestic, M.; Skalicky, M.; Ondrisik, P.; Gitari, H.; Brahmachari, K.; Shankar, T.; Bhadra, P.; Palai, J.B.; et al. Intercropping–A low input agricultural strategy for food and environmental security. Agron. J. 2021, 11, 343. [Google Scholar] [CrossRef]
  5. Kumawat, G.; Shahi, J.P.; Kumar, M. Assessment of genetic diversity of maize (Zea mays L.) hybrids under water logging condition. Electron. J. Plant Breed. 2020, 11, 252–258. [Google Scholar]
  6. García-Lara, S.; Serna-Saldivar, S.O. Chapter 1—Corn History and Culture. In Corn: Chemistry and Technology, 3rd ed.; Serna-Saldivar, S.O., Ed.; AACC International Press: St. Paul, MN, USA, 2019; pp. 1–18. [Google Scholar]
  7. Galasso, I.; Russo, R.; Mapalli, S.; Ponzoni, E.; Brambilla, I.M.; Battelli, G.; Reggiani, R. Variability in seed traits in a collection of Cannabis sativa L. genotypes. Front. Plant Sci. 2016, 7, 688. [Google Scholar] [CrossRef] [PubMed]
  8. Andre, C.M.; Hausman, J.F.; Guerriero, G. Cannabis sativa: The Plant of the Thousand and One Molecules. Front. Plant Sci. 2016, 7, 174167. [Google Scholar] [CrossRef]
  9. Côté, D.M.; Achouri, A.; Karboune, S.; L’hocine1, L. Faba Bean: An Untapped Source of Quality Plant Proteins and Bioactives. Nutrients 2022, 14, 1541. [Google Scholar] [CrossRef]
  10. Duc, G.S.; Bao, M.; Baum, B.; Redden, M.; Sadiki, M.J.; Suso, M.; Zong, X. Diversity maintenance and use of Vicia faba L. genetic resources. Field Crops Res. 2010, 115, 270–278. [Google Scholar] [CrossRef]
  11. Wang, J.; Lu, X.; Zhang, J.; Wei, H.; Li, M.; Lan, N.; Luo, H. Intercropping perennial aquatic plants with rice improved paddy field soil microbial biomass, biomass carbon and biomass nitrogen to facilitate soil sustainability. Soil Tillage Res. 2021, 208, 104–108. [Google Scholar] [CrossRef]
  12. Mousavi, S.R.; Eskandari, H. A General Overview on Intercropping and Its Advantages in Sustainable Agriculture. J. Appl. Environ. Biol. Sci. 2011, 1, 482–486. [Google Scholar]
  13. Liu, K.; Harisson, M.T.; Yan, H.; Liu, D.L.; Meinke, H.; Hoogenboom, G.; Wang, B.; Peng, B.; Guan, K.; Jaegermeyr, J.; et al. Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates. Nat. Commun. 2023, 14, 765. [Google Scholar] [CrossRef] [PubMed]
  14. Mu-Chun, Y.; Ting-Ting, X.; Peng-Hui, S.; Jian-Jun, D. Effects of Different Cropping Patterns of Soybean and Maize Seedlings on Soil Enzyme Activities and MBC and MBN. J. Northeast Agric. Univ. 2012, 19, 42–47. [Google Scholar] [CrossRef]
  15. Kumar, R.; Pandey, S.; Pandey, A. Plant roots and carbon sequestration. Curr. Sci. 2006, 91, 885–890. [Google Scholar]
  16. Hauggaard-Nielsen, H.; Jensen, E.S. Facilitative root interactions in intercrops. Plant Soil. 2005, 274, 237–250. [Google Scholar] [CrossRef]
  17. Liu, X.; Rahman, T.; Song, C.; Yang, F.; Su, B.; Cui, L.; Bu, W.; Yang, W. Relationships among light distribution, radiation use efficiency and land equivalent ratio in maize–soybean strip intercropping. Field Crops Res. 2018, 224, 91–101. [Google Scholar] [CrossRef]
  18. Velička, R.; Mockevičienė, R.; Marcinkevičienė, A.; Pupalienė, R.; Butkevičienė, L.M.; Kriaučiūnienė, Z.; Kosteckas, R.; Čekanauskas, S. Necheminių piktžolių kontrolės būdų effective palyginimas vasarinių rapsų pasėlyje ekologinės žemdirbystės sąlygomis. Žemės Ūkio Mokslai 2015, 22, 189–197. (In Lithuanian) [Google Scholar] [CrossRef]
  19. Kassam, A.; Friedrich, T.; Shaxson, F.; Pretty, J. The spread of Conservation Agriculture: Justification, sustainability and uptake. Int. J. Agric. Sustain. 2009, 7, 292–320. [Google Scholar] [CrossRef]
  20. Chimonyo, V.G.P.; Modi, A.T.; Mabhaudhi, T. Perspective on crop modelling in the management of intercropping systems. Arch. Agron. Soil Sci. 2015, 61, 1511–1529. [Google Scholar] [CrossRef]
  21. Kimbirauskienė, R.; Sinkevičienė, A.; Švereikaitė, A.; Romaneckas, K. The Complex Effect of Different Tillage Systems on the Faba Bean Agroecosystem. Plants 2024, 13, 513. [Google Scholar] [CrossRef]
  22. Balandaitė, J. Crop Biodiversity Influence on Multi-Crops Sustainability, Productivity and Energy Efficiency. Doctoral Thesis, Vytautas Magnus University, Akademija, Lithuania, 2023. [Google Scholar]
  23. Tahir, M.; Li, C.; Zeng, T.; Xin, Y.; Chen, C.; Javed, H.; Yang, W.; Yan, Y. Mixture composition influenced the biomass yield and nutritional quality of legume-grass pastures. Agron. 2022, 12, 1449. [Google Scholar] [CrossRef]
  24. Cai, G.; Su, X.; Li, Y.; Wang, X. Comparisons between diversified multicropping systems in terms of crop productivity, economic benefits and carbon footprint in the Pearl River Delta region of South China. Farm. Syst. 2023, 1, 1–8. [Google Scholar] [CrossRef]
  25. Arina, N.; Martini, Y.; Surdiana, S.; Fauzi, M.; Zulkefly, S. Radiation dynamics on crop productivity in different cropping systems. Int. J. Agron. 2021, 2021, 4570616. [Google Scholar]
  26. Litvinova, S.; Boop, L.; Galeev, R.; Smirnov, E.; Petrov, D. Formation of stable agrocenoses of corn hybrids in a sharply continental climate. In IOP Conference Series: Earth and Environmental Science; IOP Publishing: Bristol, UK, 2022; p. 981. [Google Scholar] [CrossRef]
  27. Birthal, P.; Hazrana, J. Crop diversification and resilience of agriculture to climatic shocks: Evidence from India. Agric. Syst. 2019, 173, 345–354. [Google Scholar] [CrossRef]
  28. Kotroczo, Z.; Fekete, I. Significance of soil respiration from biological activity in the degradation processes of different types of organic matter. J. Environ. Agric. Ener. 2020, 1, 171–179. [Google Scholar]
  29. Sun, Y.; Wang, C.; Yang, J.; Liao, J.; Chen, H.; Ruan, H. Elevated CO2 shifts soil microbial communities from K- to r-strategists. Glob. Ecol. Biogeogr. 2021, 30, 961–972. [Google Scholar] [CrossRef]
  30. Hu, F.; Feng, F.; Zhao, C.; Chai, Q.; Yu, A.; Yin, W.; Gan, Y. Integration of weed-maize intercropping with conservation practices reduces CO2 emissions and enhances water use in dry areas. Soil Tillage Res. 2017, 169, 44–53. [Google Scholar] [CrossRef]
  31. Lupwayi, N.; Kennedy, A. Grain legumes in Northern Great Plains: Impact on selected biological soil processes. J. Agron. 2007, 99, 1700–1709. [Google Scholar] [CrossRef]
  32. Rudinskienė, A. Caraway (Carum carvi L.) in Multifunctional Crops Cultivations and Their Impact on the Agroecosystem. Doctoral Thesis, Vytautas Magnus University, Akademija, Lithuania, 2022. [Google Scholar]
  33. Rudinskienė, A.; Marcinkevičienė, A.; Velička, R.; Steponavičienė, V.; Kosteckas, R. The effects of incorporating caraway into a multi-cropping farming system on the crops and the overall agroecosystem. Eur. J. Agron. 2023; preprint. Available online: https://www.researchgate.net/publication/373375445(accessed on 25 January 2024).
  34. Li, G.; Yu, C.; Shen, P.; Hou, Y.; Ren, Z.; Li, N.; Liao, Y.; Li, T.; Wen, X. Crop diversification promotes soil aggregation and carbon accumulation in global agroecosystems: A meta-analysis. J. Environ. Manag. 2023, 350, 119661. [Google Scholar] [CrossRef]
  35. Robačer, M.; Canali, S.; Lakenborg, K.H.; Baver, F.; Grobelnik, M.S.; Jakopa, M.; Bavec, M. Cover crops in organic field vegetable production. Sci. Hortic. 2016, 208, 104–110. [Google Scholar] [CrossRef]
  36. Ogazie, C.H.; Ochekwu, E.B.; Agbagwa, I.O.; Ugiomoh, I. Multi-cropping practice: Means to sustainable agriculture in the high humid rainforest agroecology of Southern Nigeria. Int. J. Sci. Technol. Res. Arch. 2022, 3, 66–90. [Google Scholar] [CrossRef]
  37. Livingstone, H.; Ang, T.N.; Yuan, X.; Swanepoel, W.; Kerckhoffs, H. Analysis of inter-nodal properties of two industrial hemp cultivars (Fasamo and Ferimon 12) and their relationships with plant density and row spacing. Ind. Crops Prod. 2022, 182, 114880. [Google Scholar] [CrossRef]
  38. Schafer, T.; Honermeier, B. Effect of sowing date and plant density on the cell morphology of hemp (Cannabis sativa L.). Ind. Crops Prod. 2006, 23, 88–98. [Google Scholar] [CrossRef]
  39. Vanino, S.; Di-Bene, C.; Piccini, C.; Fila, G.; Pennelli, B.; Zornoza, R.; Navarro, V.; Fuentes, J.; Huppi, R.; Six, J.; et al. A comprehensive assessment of diversified cropping systems on agro-environmental sustainability in three Mediterranean long-term field experiments. Eur. J. Agron. 2022, 140, 126598. [Google Scholar] [CrossRef]
  40. World Reference Base for Soil Resources, 3rd ed.; World Soil Resources Reports No.106; FAO: Rome, Italy, 2014; Available online: http://www.fao.org/3/i3794en/I3794en.pdf (accessed on 9 January 2024).
  41. Romaneckas, K.; Balandaitė, J.; Sinkevičienė, A.; Kimbirauskienė, R.; Jasinskas, A.; Ginelevičius, U.; Romaneckas, A.; Petlickaitė, R. Short-term impact of multi-cropping of some soil physical properties and respiration. Agronomy 2022, 12, 141. [Google Scholar] [CrossRef]
  42. Romaneckas, K.; Švereikaitė, A.; Kimbirauskienė, R.; Sinkevičienė, A.; Balandaitė, J. The energy and environmental evaluation of maize, hemp and faba bean multi-crops. Agronomy 2023, 13, 2316. [Google Scholar] [CrossRef]
  43. Stancevičius, A. Piktžolių Apskaita ir Laukų Piktžolėtumo Kartografavimas/Weed Accounting and Field Weediness Mapping; Mokslas: Vilnius, Lithuania, 1979; 37p. (In Lithuanian) [Google Scholar]
  44. SPSS Instant 10. Statistics I.; IBM: Armonk, NY, USA, 2000; p. 663. [Google Scholar]
  45. Lohmann, G. Entwicklung eines Bewertungsverfahrens für Anbausysteme mit Differenzierten Aufwandmengen Ertragssteigernder und Ertragssichernder Betriebsmittel. Doctoral Thesis, Institut für Pflanzenbau der Rheinischen Friedrich-Wilhelms-Universität Bonn, Bonn, Germany, 1994. (In German). [Google Scholar]
  46. Heyland, K.U. Zur methodik einer integrierten darstellung und bewertung der produktionsverfahren im pflanzenbau. Pflanzenbauwissenschaften 1998, 2, 145–159. (In German) [Google Scholar]
Plants 13 01372 g001
Figure 1. A model for comprehensive assessment of the impact of multi-cropping on agroecosystems (according to [21]).
Figure 1. A model for comprehensive assessment of the impact of multi-cropping on agroecosystems (according to [21]).
Plants 13 01372 g001
Plants 13 01372 g002
Figure 2. Comprehensive assessment of crop diversification in terms of total dried biomass (system level 1), 2020–2022. M: single maize crop; H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index, * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below evaluation threshold.
Figure 2. Comprehensive assessment of crop diversification in terms of total dried biomass (system level 1), 2020–2022. M: single maize crop; H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index, * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below evaluation threshold.
Plants 13 01372 g002
Plants 13 01372 g003
Figure 3. Comprehensive assessment of crop diversification in terms of CO2 respiration from the soil (system level 2), 2020–2022. M: single maize crop; H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index, * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below evaluation threshold.
Figure 3. Comprehensive assessment of crop diversification in terms of CO2 respiration from the soil (system level 2), 2020–2022. M: single maize crop; H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index, * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below evaluation threshold.
Plants 13 01372 g003
Plants 13 01372 g004
Figure 4. Comprehensive assessment of crop diversification in terms of total number of weeds at end of vegetative season (system level 3), 2020–2022. M: single maize crop; H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index, * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below threshold.
Figure 4. Comprehensive assessment of crop diversification in terms of total number of weeds at end of vegetative season (system level 3), 2020–2022. M: single maize crop; H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index, * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below threshold.
Plants 13 01372 g004
Plants 13 01372 g005
Figure 5. Comprehensive assessment of crop diversification in terms of total dried weed biomass at the end of the vegetative season (system level 4), 2020–2022. M: single maize crop, H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index; * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below threshold.
Figure 5. Comprehensive assessment of crop diversification in terms of total dried weed biomass at the end of the vegetative season (system level 4), 2020–2022. M: single maize crop, H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index; * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below threshold.
Plants 13 01372 g005
Plants 13 01372 g006
Figure 6. Comprehensive assessment of the impact of all four system levels on agroecosystem, 2020–2022. M: single maize crop; H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index; * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below threshold.
Figure 6. Comprehensive assessment of the impact of all four system levels on agroecosystem, 2020–2022. M: single maize crop; H: single hemp crop; FB: single faba bean crop; M + H: binary maize and hemp crop; M + FB: binary maize and faba bean crop; H + FB: binary hemp and faba bean crop; M + H + FB: ternary maize, hemp, and faba bean crop. CEI, complex evaluation index; * average of evaluation points (EPs), ** standard deviation of EPs, *** standard deviation of average of evaluation points below threshold.
Plants 13 01372 g006
Table 1. Average air temperature (°C) and precipitation rate (mm) during multi-crop vegetative periods at Kaunas Meteorological Station.
Table 1. Average air temperature (°C) and precipitation rate (mm) during multi-crop vegetative periods at Kaunas Meteorological Station.
Month/Year202020212022Long-Term Average
Air temperature (°C)
March3.31.61.52.1
April6.96.26.26.4
May10.511.411.011.0
June19.019.517.718.7
July17.422.617.919.3
August18.716.520.918.7
September14.811.410.612.3
Precipitation rate (mm)
March21.01.949.324.1
April4.033.738.425.4
May94.4121.684.0100.0
June99.340.377.672.4
July60.548.4100.569.8
August92.8122.238.784.6
September30.048.044.040.7
Table 2. Experimental treatments.
Table 2. Experimental treatments.
Biodiversity LevelCropsAbbreviation and Number of Treatments
Single cropMaize, hemp, faba bean (single crops)M (1), H (2), FB (3)
Binary cropMaize + hempM + H (4)
Maize + faba beanM + FB (5)
Hemp + faba beanH + FB (6)
Ternary cropMaize + hemp + faba beanM + H + FB (7)
Table 3. Tested variables and their variation.
Table 3. Tested variables and their variation.
IndexVariationUnitIndexVariationUnit
Total dried crop biomass (end of vegetative season)88.7–4401.6g m−2CO2 e-flux rate (middle of vegetative season)2.4–4.68µmol m−2 s−1
PAR at soil surface2.3–27.1%Change in total nitrogen−0.033–0.022mg kg−1
Total crop density (end of vegetative season)19–95units m−2Change in mobile phosphorus−29.0–35.0mg kg−1
Average crop height (end of vegetative season) 63.4–239.5cmChange in mobile potassium−27.0–17.5mg kg−1
Average leaf chlorophyll index (second half of crop vegetative season)7.4–75.7-Change in mobile magnesium−32.0–545mg kg−1
Average leaf assimilative area (middle of vegetative season)66.15–427.1cm−2Dried biomass of total weeds (end of vegetative season)7.5–224.4g m−2
Soil megastructure content (beginning of vegetative season)31.9–52.6%Total number of weeds (end of vegetative season)111.1–472.2units m−2
Soil macrostructure content (beginning of vegetative season)46.7–65.3%Average daily air temperature1.5–22.6°C
Soil microstructure content (beginning of vegetative season)0.7–3.1%Precipitation rate1.9–122.2mm
Soil aggregate stability (beginning of vegetative season)30.2–45.4%---
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Balandaitė, J.; Romaneckas, K.; Kimbirauskienė, R.; Sinkevičienė, A. Comprehensive Assessment of the Effect of Multi-Cropping on Agroecosystems. Plants 2024, 13, 1372. https://doi.org/10.3390/plants13101372

AMA Style

Balandaitė J, Romaneckas K, Kimbirauskienė R, Sinkevičienė A. Comprehensive Assessment of the Effect of Multi-Cropping on Agroecosystems. Plants. 2024; 13(10):1372. https://doi.org/10.3390/plants13101372

Chicago/Turabian Style

Balandaitė, Jovita, Kęstutis Romaneckas, Rasa Kimbirauskienė, and Aušra Sinkevičienė. 2024. "Comprehensive Assessment of the Effect of Multi-Cropping on Agroecosystems" Plants 13, no. 10: 1372. https://doi.org/10.3390/plants13101372

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

Article Metrics

Back to TopTop