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Topic Editors

The State Key Laboratory of Grassland Agro-Ecosystems, Lanzhou University, Lanzhou 730020, China
Prof. Dr. Yangzhou Xiang
School of Geography and Resources, Guizhou Education University, Guizhou 550018, China
College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
College of Grassland Science, Qingdao Agricultural University, Qingdao 266109, China

Evaluating the Functional Value of Agroecosystems under Different Management Scenarios

Abstract submission deadline
20 August 2025
Manuscript submission deadline
20 October 2025
Viewed by
16276

Topic Information

Dear Colleagues,

Agroecosystems, communities of plants and animals interacting with their modified physical and chemical environments, play a crucial role in producing food, fiber, fuel, and other products for human use (Maes, 2018). These systems integrate agricultural activities with the surrounding environment, encompassing both biotic (e.g., crops, livestock, insects, microbes) and abiotic (e.g., climate, nutrients, water, light) components. The interactions within these components can be complex, yet sustainable agroecosystems offer significant benefits such as reducing soil and water erosion, enhancing soil fertility and biodiversity, sequestering carbon, and improving overall productivity, sustainability, stability, and resilience.

In light of the growing challenges related to soil health, food security, and environmental sustainability, there is an urgent need to develop strategies that maximize resource use efficiency while minimizing negative impacts on soils and ecosystems. Understanding the mechanisms behind agroecosystem sustainability is vital for guiding future agricultural practices that can mitigate climate change threats, improve soil fertility, and secure global food supplies.

This Topic seeks to gather and exchange knowledge on the mechanisms and future directions for optimizing agricultural management within agroecosystems.

Dr. Yuan Li
Prof. Dr. Yangzhou Xiang
Dr. Jihui Tian
Prof. Dr. Fuhong Miao
Topic Editors

Keywords

  • agroecosystem productivity
  • greenhouse gas emissions
  • resource use efficiency
  • sustainability
  • soil health
  • climate change mitigation
  • agricultural management

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Agriculture
agriculture
3.3 4.9 2011 19.2 Days CHF 2600 Submit
Agronomy
agronomy
3.3 6.2 2011 17.6 Days CHF 2600 Submit
Grasses
grasses
- - 2022 26.3 Days CHF 1000 Submit
Microorganisms
microorganisms
4.1 7.4 2013 11.7 Days CHF 2700 Submit
Plants
plants
4.0 6.5 2012 18.9 Days CHF 2700 Submit
Biology
biology
3.6 5.7 2012 16.4 Days CHF 2700 Submit

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Published Papers (10 papers)

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16 pages, 3290 KiB  
Article
The Impact of Winter Cover Crops on Soil Nematode Communities and Food Web Stability in Corn and Soybean Cultivation
by Jerry Akanwari, Md Rashedul Islam and Tahera Sultana
Microorganisms 2024, 12(10), 2088; https://doi.org/10.3390/microorganisms12102088 - 18 Oct 2024
Cited by 1 | Viewed by 921
Abstract
There is increasing adoption of winter cover crops (WCCs) in corn and soybean production in Canada, primarily to reduce erosion and increase soil organic matter content. WCCs have the potential to influence nematode communities by increasing free-living nematodes and decreasing plant-parasitic nematodes or [...] Read more.
There is increasing adoption of winter cover crops (WCCs) in corn and soybean production in Canada, primarily to reduce erosion and increase soil organic matter content. WCCs have the potential to influence nematode communities by increasing free-living nematodes and decreasing plant-parasitic nematodes or vice versa. However, the mechanism by which WCCs change nematode community assemblages still remains a key question in soil food web ecology. We tested the hypothesis that the long-term use of rye (Secale cereale), barley (Hordeum vulgare) and oat (Avena sativa) as monocultures or mixtures promotes nematode communities and improves overall soil health conditions compared to winter fallow. The results from this study revealed that the use of WCCs generally promoted a higher abundance and diversity of nematode communities, whereas plant parasitic nematodes were the most abundant in winter fallow. Moreover, the mixtures of WCCs had more similar nematode communities compared to rye alone and winter fallow. The structure and enrichment indices were higher with WCCs, indicating higher nutrient cycling and soil suppressiveness, which are signs of healthy soil conditions. Furthermore, WCCs significantly reduced the populations of root lesion nematode Pratylenchus, although their numbers recovered and increased during the main crop stages. Additionally, mixtures of WCCs promoted the highest abundance of the stunt nematode Tylenchorhynchus, whereas winter fallow had a higher abundance of the spiral nematode Helicotylenchus during the fallow period and the main crop stages. The results show that the long-term use of cover crops can have a positive impact on nematode communities and the soil food web, but these changes depend on the type of WCCs and how they are used. Full article
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Figure 1

Figure 1
<p>Effect of winter cover crops on nematode community composition in corn–soybean production based on feeding guilds under different treatments. The y-axis represents the relative abundance (%) and the x-axis represents the different feeding groups. The bars are mean ± standard error (n = 4) for each treatment. Different letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05 (Tukey HSD test); Mixture 1 = rye and barley; Mixture 2 = oats and rye.</p>
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<p>Effect of winter cover crops in corn–soybean rotation on (<b>A</b>) nematode taxonomic richness and (<b>B</b>) Shannon diversity index. Lower and upper box boundaries are the 25th and 75th percentiles; the line inside the box indicates median; and lower and upper error lines represent 10th and 90th percentiles. Different letters above boxes indicate statistical significance at <span class="html-italic">p</span> &lt; 0.05 (Tukey HSD test). Mixture 1 = rye and barley; Mixture 2 = oats and rye.</p>
Full article ">Figure 3
<p>Non−metric multidimensional scaling (NMDS) plot of nematode communities based on Bray–Curtis dissimilarity metric. Circles within the NMDS plot are 90% confidence ellipses. Mixture 1 = rye and barley; Mixture 2 = oats and rye.</p>
Full article ">Figure 4
<p>Distance-based redundancy analysis (dbRDA) of the relationship between cover crop treatment, nematode community structure and environmental variables using Bray−Curtis dissimilarity matrix. Only species and environmental factors that explains at least 40% (|r| ≥ 0.40) of the variation and significantly different (<span class="html-italic">p</span> &lt; 0.05) are shown. Mixture 1 = rye and barley, Mixture 2 = oats and rye.</p>
Full article ">Figure 5
<p>Generalized linear model (GLM) analysis of nematodes community indices ((<b>A</b>) = maturity index; (<b>B</b>) = plant-parasitic index; (<b>C</b>) = enrichment index; (<b>D</b>) = structure index; (<b>E</b>) = channel index; (<b>F</b>) = basal index). The lines are mean and standard errors (n = 4). Different letters represent significant differences among treatments using Tukey HSD at <span class="html-italic">p</span> &lt; 0.05. N.S = not significant.</p>
Full article ">Figure 6
<p>Food web analysis of nematode communities and their positions as soil health indicators. The vertical axis is the enrichment index (nematode reproduction), and the horizontal axis is the structure index (nematode resistance to disturbance). The soil health condition is categorized into four quadrats (A–D). Bars are mean ± standard errors. Mixture 1 = rye and barley; Mixture 2 = oats and rye.</p>
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<p>Nematode metabolic footprints under different treatment groups. The bars are mean and standard errors (n = 4). Different letters represent significant differences among treatments using Tukey HSD at <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">
13 pages, 5297 KiB  
Article
Cultivated Grassland Types Differently Affected Carbon Flux Downstream of the Yellow River
by Yibo Wang, Xudong Qu, Meixuan Li, Juan Sun and Zhenchao Zhang
Agronomy 2024, 14(5), 974; https://doi.org/10.3390/agronomy14050974 - 6 May 2024
Cited by 1 | Viewed by 1091
Abstract
Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale [...] Read more.
Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties. Full article
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Figure 1

Figure 1
<p>Location of the study area.</p>
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<p>Temperature and precipitation in the study area.</p>
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<p>Photographs of sampling plots with different cultivated grasslands: (<b>a</b>) <span class="html-italic">Medicago sativa</span> grassland; (<b>b</b>) <span class="html-italic">Triticum aestivum</span> grassland; (<b>c</b>) <span class="html-italic">Secale cereale</span> grassland; and (<b>d</b>) <span class="html-italic">Vicia villosa</span> grassland.</p>
Full article ">Figure 4
<p>Dynamics of net ecosystem CO<sub>2</sub> exchange (NEE) (<b>a</b>), ecosystem respiration (ER) (<b>b</b>), and gross ecosystem productivity (GEP) (<b>c</b>) during the 2022–2023 growing period. CK: bare land; MS: <span class="html-italic">Medicago sativa</span> grassland; TA: <span class="html-italic">Triticum aestivum</span> grassland; SC: <span class="html-italic">Secale cereale</span> grassland; and VV: <span class="html-italic">Vicia villosa</span> grassland. Values are the mean ± standard error. The unit of CO<sub>2</sub> flux is µmol·m<sup>−2</sup>·s<sup>−1</sup>. The same applies below.</p>
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<p>Mean values of NEE (<b>a</b>), ER (<b>b</b>), and GEP (<b>c</b>) in the growing season of bare land and cultivated grasslands. Error bars show the standard error.</p>
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<p>Correlation between NEE and BD (<b>a</b>), pH (<b>b</b>) and SOC (<b>c</b>) contents. Correlation between ER and SOC (<b>d</b>) and MBC (<b>e</b>). Correlation between GEP and BD (<b>f</b>), SOC (<b>g</b>) and MBC (<b>h</b>).</p>
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14 pages, 960 KiB  
Article
Influence of EMR–Phosphogypsum–Biochar Mixtures on Sudan Grass: Growth Dynamics and Heavy Metal Immobilization
by Yang Luo, Fang Liu, Xuqiang Luo, Jun Ren, Jinmei Guo and Jinxin Zhang
Agronomy 2024, 14(5), 945; https://doi.org/10.3390/agronomy14050945 - 30 Apr 2024
Cited by 1 | Viewed by 1048
Abstract
This study investigates the growth dynamics and heavy metal immobilization in Sudan grass cultivated on substrates composed of electrolytic manganese residue (EMR), phosphogypsum, and chili straw biochar. Pot experiments revealed that a substrate with phosphogypsum constituting 75% of the mix hinders Sudan grass [...] Read more.
This study investigates the growth dynamics and heavy metal immobilization in Sudan grass cultivated on substrates composed of electrolytic manganese residue (EMR), phosphogypsum, and chili straw biochar. Pot experiments revealed that a substrate with phosphogypsum constituting 75% of the mix hinders Sudan grass seed germination. Compared with sole EMR utilization, the composite substrates notably enhanced plant growth, evidenced by increases in plant height and fresh weight. The integration of these substrates led to a significant elevation in total chlorophyll content (up to 54.39%) and a reduction in malondialdehyde (MDA) levels (up to 21.66%), indicating improved photosynthetic activity and lower oxidative stress. The addition of biochar reduced the content of Zn, Cd, and Mn in the roots of Sudan grass by up to 25.92%, 20.00%, and 43.17%, respectively; and reduced the content of Pb, Mn, and Cr in the shoot by up to 33.72%, 17.53%, and 26.32%, respectively. Fuzzy membership function analysis identified the optimal substrate composition as 75% EMR and 25% phosphogypsum, with 5% chili straw biochar, based on overall performance metrics. This study adopts the concept of “to treat waste with waste”. The approach is to fully consider the fertility characteristics of EMR, phosphogypsum, and biochar, underscoring the potential for utilizing waste-derived materials in cultivating Sudan grass and offering a sustainable approach to plant growth and heavy metal management. Full article
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Figure 1

Figure 1
<p>Emergence rate of Sudan grass under different treatments. Different lowercase letters indicate significant differences between the different treatments at the 0.05 level.</p>
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<p>Photos of Sudan grass under different treatments.</p>
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<p>MDA content of Sudan grass under different treatments. Different lowercase letters indicate significant differences between the different treatments at the 0.05 level.</p>
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15 pages, 962 KiB  
Article
Quantifying the Flows of Nitrogen Fertilizer under Different Application Rates in a Soil–Forage Triticale–Dairy Cow System
by Yongliang You, Guibo Liu, Xianlong Yang, Zikui Wang, Yuan Li, Xingfa Lai and Yuying Shen
Agronomy 2023, 13(12), 3073; https://doi.org/10.3390/agronomy13123073 - 16 Dec 2023
Viewed by 1717
Abstract
Nitrogen (N) can enhance the biomass and feeding quality of forage crops and advance the growth of the herbivorous livestock industry. Investigating the N fertilizer dynamics in the soil–crop–livestock system is important for resource-use efficiency and environmental safety. By using the 15N-labeled [...] Read more.
Nitrogen (N) can enhance the biomass and feeding quality of forage crops and advance the growth of the herbivorous livestock industry. Investigating the N fertilizer dynamics in the soil–crop–livestock system is important for resource-use efficiency and environmental safety. By using the 15N-labeled technology and the in vitro incubation technique, an experiment was conducted in the North China Plain (NCP) in 2015–2016 to quantify the migration and distribution of N fertilizer in the soil–forage triticale (X Triticosecale Wittmack)–dairy cow system. The results showed that 34.1–37.3% of the applied N fertilizer was absorbed by forage triticale, in which 35.9–39.6% N accumulated in the stems and 60.4–64.1% accumulated in the leaves. In addition, 36.3–39.1% of the applied N fertilizer remained in the 0–100 cm soil layer, in which 81.8–91.3% was distributed in the 0–40 cm soil layer. The remaining 24.6–26.8% of the applied N fertilizer was lost in various ways and 28.1–31.3% of the N fertilizer could be utilized by dairy cows. When N fertilizer was applied between 0–225 kg N ha−1, the increased application of N fertilizer improved the biomass yield from 14.0 to 17.5 t ha−1 and enhanced the N content of the forage triticale from 1.3% to 1.4%; however, it did not significantly affect the distribution rate of N fertilizer in the soil–forage triticale–dairy cow system. The optimum N fertilizer application rate for forage triticale is less than 225 kg N ha–1 to maintain high-efficient N use in the soil–crop–livestock system and reduce the environmental risks in the NCP. Our results quantified the N fertilizer dynamics in the soil–forage triticale–dairy cow system and provided a significant reference for guiding rational strategies of forage triticale cultivation. Full article
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Figure 1
<p>The F<span class="html-italic"><sub>NDE</sub></span> and F<span class="html-italic"><sub>NDC</sub></span> in dairy cows under different N-fertilizer treatments. F<span class="html-italic"><sub>NDE</sub></span> represents the N-fertilizer digestion efficiency of the dairy cows and F<span class="html-italic"><sub>NDC</sub></span> represents the fertilizer NUE of the dairy cows. N<sub>75</sub>, N<sub>150</sub>, N<sub>225</sub>, and N<sub>300</sub> represent fertilizer applications of N 75, 150, 225, and 300 kg ha<sup>−1</sup>, respectively, and fertilizer applications of P<sub>2</sub>O<sub>5</sub>180, 180, 180, and 180 kg ha<sup>−1</sup>, respectively. Different lowercase letters in the different treatments represent significant differences at the 0.05 level, and the same lowercase letter in the in the different treatments represents no significance at the 0.05 level.</p>
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<p>The distribution rate of N fertilizer in the soil–forage triticale system, including the stem and leaf of forage triticale, 0–40 cm and 40–100 cm soil layers, and loss in various ways. N<sub>75</sub>, N<sub>150</sub>, N<sub>225</sub>, and N<sub>300</sub> represent fertilizer applications of N 75, 150, 225, and 300 kg ha<sup>−1</sup>, respectively, and fertilizer applications of P<sub>2</sub>O<sub>5</sub>180, 180, 180, and 180 kg ha<sup>−1</sup>, respectively. Different lowercase letters in the different treatments represent significant differences at the 0.05 level, and the same lowercase letter in the in the different treatments represents no significance at the 0.05 level.</p>
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<p>The distribution rate of N fertilizer in the forage triticale–dairy cow system. N<sub>75</sub>, N<sub>150</sub>, N<sub>225</sub>, and N<sub>300</sub> represent fertilizer applications of N 75, 150, 225, and 300 kg ha<sup>−1</sup>, respectively, and fertilizer applications of P<sub>2</sub>O<sub>5</sub>180, 180, 180, and 180 kg ha<sup>−1</sup>, respectively. Different lowercase letters in the different treatments represent significant differences at the 0.05 level, and the same lowercase letter in the in the different treatments represents no significance at the 0.05 level. Different lowercase letters in the different treatments represent significant differences at the 0.05 level, and the same lowercase letter in the in the different treatments represents no significance at the 0.05 level.</p>
Full article ">
15 pages, 1549 KiB  
Article
Effect of Intercropping on Fruit Yield and Financial Benefits of Rosa roxburghii Tratt Orchard in Southwest China
by Ying Liu, Yawen Zhang, Tianhao Xiao, Yuguo Wu, Yuan Li, Ji He, Yangzhou Xiang and Bin Yao
Agronomy 2023, 13(12), 2953; https://doi.org/10.3390/agronomy13122953 - 29 Nov 2023
Cited by 3 | Viewed by 1737
Abstract
The practice of intercropping in Rosa roxburghii Tratt orchards holds potential for enhancing fruit yield and financial benefits, yet remains insufficiently explored. To address this, we delved into the effects of intercropping on fruit yield and financial viability of R. roxburghii orchards in [...] Read more.
The practice of intercropping in Rosa roxburghii Tratt orchards holds potential for enhancing fruit yield and financial benefits, yet remains insufficiently explored. To address this, we delved into the effects of intercropping on fruit yield and financial viability of R. roxburghii orchards in Longli County, southern China. Orchards of varying ages (4 years old and 5 years old; 7 years old and 8 years old) were subjected to different treatments: (i) Zea mays and Capsicum annuum intercropping, and clean tillage for younger orchards, and (ii) Lolium perenne, natural grass, and clean tillage for older orchards. Each treatment was assessed for its impact on fruit yield and financial benefits. In younger orchards, intercropping with Z. mays and C. annuum did not significantly elevate fruit yield compared to clean tillage in the 4-year-old orchard; however, C. annuum intercropping significantly improved fruit yield in the 5-year-old orchard. Concurrently, intercropping significantly augmented the total financial benefit by 9234.35–10,486.25 CNY ha−1 (Z. mays) and 14,304.90–16,629.18 CNY ha−1 (C. annuum) compared to clean tillage. In older orchards, L. perenne intercropping significantly elevated fruit yield by 598.84–803.64 kg·ha−1, while natural grass reduced it by 394.61–986.24 kg·ha−1, compared to clean tillage. Additionally, L. perenne intercropping significantly boosted the total financial benefit by 8873.92–9956.56 CNY ha−1, whereas natural grass negatively impacted financial benefits by 78.42–2444.94 CNY ha−1 compared to clean tillage. Collectively, our results illustrate that judicious selection of intercrops, based on orchard age and conditions, can significantly enhance both fruit yield and financial advantages in R. roxburghii orchards. This study furnishes vital insights for orchard management and accentuates the prospective merits of intercropping in fruit production systems. Full article
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Figure 1
<p>Pictures of two study sites. (<b>a</b>) Clean tillage, (<b>b</b>) Intercropping <span class="html-italic">Zea mays</span>, (<b>c</b>) Intercropping <span class="html-italic">Capsicum annuum</span> in Gujiao town; (<b>d</b>) Clean tillage, (<b>e</b>) Intercropping natural grass, (<b>f</b>) Intercropping <span class="html-italic">Lolium perenne</span> in Xima town.</p>
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<p>Fruit yield of <span class="html-italic">R. roxburghii</span> orchard under different intercropping modes and duration. Fruit yield of <span class="html-italic">R. roxburghii</span> between three intercropping modes (<b>a</b>) under 4 and 5-year-old in Gujiao orchard, and (<b>b</b>) under 7 and 8-year-old in Xima orchard, and fruit yield of <span class="html-italic">R. roxburghii</span> (<b>c</b>) between 4 and 5-year-old under three intercropping modes in Gujiao orchard, and (<b>d</b>) between 7 and 8-year-old under three intercropping modes in Xima orchard. n.s., *, **, and *** denote no significant difference, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 0.01, and <span class="html-italic">p</span> &lt; 0.001, respectively. CT, clean tillage; ZM, <span class="html-italic">Z. mays</span>; CA, <span class="html-italic">C. annuum</span>; NG, natural grass; LP, <span class="html-italic">L. perenne</span>.</p>
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<p>Fruit financial benefits of <span class="html-italic">R. roxburghii</span> under different intercropping modes and duration. Fruit financial benefits of <span class="html-italic">R. roxburghii</span> between three intercropping modes (<b>a</b>) under 4 and 5-year-old in Gujiao orchard, and (<b>b</b>) under 7 and 8-year-old in Xima orchard, and fruit financial benefits of <span class="html-italic">R. roxburghii</span> (<b>c</b>) between 4 and 5-year-old under three intercropping modes in Gujiao orchard, and (<b>d</b>) between 7 and 8-year-old under three intercropping modes in Xima orchard. n.s., *, **, and *** denote no significant difference, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 0.01, and <span class="html-italic">p</span> &lt; 0.001, respectively. CT, clean tillage; ZM, <span class="html-italic">Z. mays</span>; CA, <span class="html-italic">C. annuum</span>; NG, natural grass; LP, <span class="html-italic">L. perenne</span>.</p>
Full article ">Figure 4
<p>Intercrops’ financial benefits of different intercropping modes and duration in <span class="html-italic">R. roxburghii</span> orchards. Intercrops’ financial benefits between three intercropping modes (<b>a</b>) under 4 and 5-year-old <span class="html-italic">R. roxburghii</span> orchard in Gujiao town, and (<b>b</b>) under 7 and 8-year-old <span class="html-italic">R. roxburghii</span> orchard in Xima town, and intercrops’ financial benefits (<b>c</b>) between 4 and 5-year-old <span class="html-italic">R. roxburghii</span> orchard under three intercropping modes in Gujiao town, and (<b>d</b>) between 7 and 8-year-old <span class="html-italic">R. roxburghii</span> orchard under three intercropping modes in Xima town. n.s., **, and *** denote no significant difference, <span class="html-italic">p</span> &lt; 0.01, and <span class="html-italic">p</span> &lt; 0.001, respectively. CT, clean tillage; ZM, <span class="html-italic">Z. mays</span>; CA, <span class="html-italic">C. annuum</span>; NG, natural grass; LP, <span class="html-italic">L. perenne</span>.</p>
Full article ">Figure 5
<p>Total financial benefits of <span class="html-italic">R. roxburghii</span> orchards under different intercropping modes and duration. Total financial benefits of <span class="html-italic">R. roxburghii</span> between three intercropping modes (<b>a</b>) under 4 and 5-year-old in Gujiao orchard, and (<b>b</b>) under 7 and 8-year-old in Xima orchard, and total financial benefits of <span class="html-italic">R. roxburghii</span> (<b>c</b>) between 4 and 5-year-old under three intercropping modes in Gujiao orchard, and (<b>d</b>) between 7 and 8-year-old under three intercropping modes in Xima orchard. n.s., *, **, and *** denote no significant difference, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 0.01, and <span class="html-italic">p</span> &lt; 0.001, respectively. CT, clean tillage; ZM, <span class="html-italic">Z. mays</span>; CA, <span class="html-italic">C. annuum</span>; NG, natural grass; LP, <span class="html-italic">L. perenne</span>.</p>
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15 pages, 1925 KiB  
Article
The Responses of Stem and Leaf Functional Traits of Medicago sativa and Bromus inermis to Different Mixed Planting Patterns
by Fuhong Miao, Xiaoxu Yu, Xinkai Tang, Xindi Liu, Wei Tang, Yanhua Zhao, Chao Yang, Yufang Xu, Guofeng Yang and Juan Sun
Agronomy 2023, 13(11), 2733; https://doi.org/10.3390/agronomy13112733 - 30 Oct 2023
Viewed by 1376
Abstract
This study investigated the differences in stem and leaf growth characteristics of Medicago sativa and Bromus inermis in the Jiaozhou region of China during 2019–2020 under three different planting modes of the two forages: monoculture, mixed species sowing in the same rows, and [...] Read more.
This study investigated the differences in stem and leaf growth characteristics of Medicago sativa and Bromus inermis in the Jiaozhou region of China during 2019–2020 under three different planting modes of the two forages: monoculture, mixed species sowing in the same rows, and mixed species sowing in alternating rows. No special management of the experimental plots was carried out in this study to simulate as much as possible the growth of forages in their natural state. The stem and leaf characteristics influencing the dry matter weight were calculated using grey correlation. These characteristics included leaf length, leaf width, leaf thickness, leaf area, leaf fresh weight, stem length, stem diameter, stem fresh weight, stem–leaf ratio, fresh matter yield, dry matter yield, and protein yield of M. sativa and B. inermis under different sowing methods in different years. The results showed that the weight pattern of the characteristics affecting the yield of M. sativa and B. inermis production was leaf area > stem diameter > leaf length > stem length > leaf width > leaf thickness, leaf area > leaf length > stem length > leaf width > leaf thickness > stem diameter. Considering all the growth factors, the production capacity was ranked as mixed sowing in alternating rows > mixed sowing in same rows > monoculture. Thus, the suitable mode for M. sativaB. inermis sowing was mixed sowing in alternating rows. Full article
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Figure 1
<p>Annual average temperature of test field in Jiaozhou area. Data from China Meteorological Data Service Centre (<a href="http://data.cma.cn" target="_blank">http://data.cma.cn</a> 8 February 2020).</p>
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<p>Correlation of <span class="html-italic">Medicago sativa</span> stem and leaf indicators under different sowing methods. LL is leaf length. LW is leaf width. LT is leaf thickness. LA is leaf area. SL is stem length. SD is stem diameter. Peer mix (P), heterocomplex (H), monoculture (M). Significance levels are as follows: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Correlation of <span class="html-italic">Bromus inermis</span> stem and leaf indicators under different sowing methods. LL is leaf length. LW is leaf width. LT is leaf thickness. LA is leaf area. SL is stem length. SD is stem diameter. Peer mix (P), heterocomplex (H), monoculture (M). Significance levels are as follows: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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12 pages, 2498 KiB  
Article
Effects of Different Tillage and Residue Retention Measures on Silage Maize Yield and Quality and Soil Phosphorus in Karst Areas
by Tao Wang, Wei Ren, Feng Yang, Lili Niu, Zhou Li and Mingjun Zhang
Agronomy 2023, 13(9), 2306; https://doi.org/10.3390/agronomy13092306 - 31 Aug 2023
Cited by 4 | Viewed by 1448
Abstract
Soil phosphorus (P) limitation in karst areas has severely constrained soil quality and land productivity. To enhance silage maize yield and quality and alleviate and/or balance the low phosphorus availability in the karst areas of China, the experiment investigated the effects of different [...] Read more.
Soil phosphorus (P) limitation in karst areas has severely constrained soil quality and land productivity. To enhance silage maize yield and quality and alleviate and/or balance the low phosphorus availability in the karst areas of China, the experiment investigated the effects of different tillage and residue retention practices on silage maize yield and quality and soil phosphorus in this region. The treatment set included: conventional tillage (CT), conventional tillage and root stubble retention (CTH), conventional tillage and mulch (CTM), conventional tillage and crushing and incorporation of hairy vetch by tillage (CTR), no tillage (NT), no tillage and root stubble retention (NTH), no tillage and mulch (NTM), and no tillage and living mulch (NTLM). The results showed that CTM, NTM, CTR, and NTLM significantly increased the height and LAI of silage maize compared with the CT, NT, and NTH treatments. CTM, CTR, and NTM significantly enhanced maize yield. Compared with conventional tillage, not tilling had a more pronounced improvement in silage quality, whereas residue retention hardly affected corn quality. In addition, although not tilling does not significantly increase acid phosphatase activity, it appeared to be advantageous in increasing soil microbial phosphorus and available phosphorus content when combined with cover crop measures. Ultimately, we concluded that NTM and NTLM are beneficial for silage maize yield and quality and soil phosphorus content in karst areas and verified the advantages of combining no tillage and residue retention practices for silage maize production and soil phosphorus improvement in the karst areas of China. Full article
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<p>(<b>a</b>) Study location in southeastern China. (<b>b</b>) The precipitation and mean temperature of the maize growing season in the study area in 2021–2022.</p>
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<p>The biomass of maize at different growth stages in the study area. Notes: conventional tillage (CT), conventional tillage and root stubble retention (CTH), conventional tillage and mulch (CTM), conventional tillage and crushing and incorporation of hairy vetch by tillage (CTR), no tillage (NT), no tillage and root stubble retention (NTH), no tillage and mulch (NTM), and no tillage and living mulch (NTLM). Notes: Different letters indicate significant differences between different soil layers in the same treatment at the <span class="html-italic">p</span> &lt; 0.05 level.</p>
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<p>The dry matter of maize at different growth stages in the study area. Notes: conventional tillage (CT), conventional tillage and root stubble retention (CTH), conventional tillage and mulch (CTM), conventional tillage and crushing and incorporation of hairy vetch by tillage (CTR), no tillage (NT), no tillage and root stubble retention (NTH), no tillage and mulch (NTM), and no tillage and living mulch (NTLM). Notes: Different letters indicate significant differences between different soil layers in the same treatment at the <span class="html-italic">p</span> &lt; 0.05 level.</p>
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<p>Correlation matrix between leaf area index (LAI), height, biomass, dry matter, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), crude fiber (CF), crude ash (Ash), total phosphorus (TP), available phosphorus (AP), soil microbial phosphorus (MBP), and acid phosphatase (ACP). The confidence interval is 95%. * and ** indicate the significant effects of farming practices at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01, respectively, determined by Pearson’s correlation.</p>
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11 pages, 408 KiB  
Article
Screening Optimal Oat Varieties for Cultivation in Arid Areas in China: A Comprehensive Evaluation of Agronomic Traits
by Gang Wang, Huixin Xu, Hongyang Zhao, Yuguo Wu, Xi Gao, Zheng Chai, Yuqing Liang, Xiaoke Zhang, Rong Zheng, Qian Yang and Yuan Li
Agronomy 2023, 13(9), 2266; https://doi.org/10.3390/agronomy13092266 - 29 Aug 2023
Cited by 2 | Viewed by 1708
Abstract
This study was undertaken to identify oat (Avena sativa L.) varieties optimal for cultivation in the Jiuquan region, China, in 2021. A selection of 27 domestic and international oat varieties were analyzed, considering ten key agronomic traits, including plant height, stem diameter, [...] Read more.
This study was undertaken to identify oat (Avena sativa L.) varieties optimal for cultivation in the Jiuquan region, China, in 2021. A selection of 27 domestic and international oat varieties were analyzed, considering ten key agronomic traits, including plant height, stem diameter, spike length, leaf width, and yield. Employing methods such as cluster analysis, principal component analysis, and grey correlation degree, a comprehensive evaluation was conducted. The principal component analysis distilled the ten indicators to three core components. The most influential factors in the first principal component were plant height, ear length, and hay yield, while leaf length and leaf area index were the highest contributors to the second component. The stem-to-leaf ratio emerged as the principal indicator in the third component. The cluster analysis resulted in the classification of the 27 oat varieties into 3 categories. Following a comprehensive evaluation through the grey correlation degree and principal component analysis methodologies, we found that the oat varieties Sweety 1, Fuyan 1, Dingyan 2, Baler, Quebec, and Longyan 2 received the highest scores. These varieties, hence, appear to be the most suitable for cultivation and promotion in the Jiuquan region. This study thus provides invaluable insights into oat cultivation practices, offering guidance for farmers, agricultural policymakers, and future research in the field. Full article
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<p>Dendrogram of agronomic characters by cluster analysis for 27 oat varieties.</p>
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12 pages, 3055 KiB  
Article
Root Architecture of Forage Species Varies with Intercropping Combinations
by Xindi Liu, Yu Jiao, Xiaoyu Zhao, Xiaoxu Yu, Qingping Zhang, Shuo Li, Lichao Ma, Wei Tang, Chao Yang, Guofeng Yang, Juan Sun and Fuhong Miao
Agronomy 2023, 13(9), 2223; https://doi.org/10.3390/agronomy13092223 - 25 Aug 2023
Cited by 3 | Viewed by 1984
Abstract
Belowground root systems under pasture intercropping exhibit complex interactions, and the root interactions of different intercropping combinations are still poorly understood. Therefore, in this work, two perennial and annual herbages were intercropped in pairs and evaluated at a ratio of 1:1. The root [...] Read more.
Belowground root systems under pasture intercropping exhibit complex interactions, and the root interactions of different intercropping combinations are still poorly understood. Therefore, in this work, two perennial and annual herbages were intercropped in pairs and evaluated at a ratio of 1:1. The root morphology and topological structure differed significantly with intercropping combinations. (1) Compared with other cropping patterns, the mean root diameter (RD) of intercropped alfalfa (Medicago sativa L.) and common vetch (Vicia sativa L.) increased notably. The root surface area (RSA), root volume (RV), and mean RD increased significantly when oat (Avena sativa L.) was intercropped with alfalfa. Similarly, the RSA and RV increased in intercropped oat, intercropping relative to monocropping. (2) The forage topological index of the intercropping system was close to one, which was close to that of the herringbone branching. Additionally, the intercropping system had a lower intensity of underground root competition. The root system of the different forage intercropping combinations tended to transition to dichotomous branching. (3) The correlations between root parameters differed according to forage species. Therefore, different intercropping combinations had different belowground root levels of competitiveness and interactions, thereby changing the resource competition environment. Full article
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<p>Root topology diagram. A is the number of links of the greater path length, which is the interior link of the root system. M is the number of the tip roots, which is the exterior link.</p>
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<p>CK: monocropping of each herbage; M. <span class="html-italic">Medicago sativa;</span> V. <span class="html-italic">Vicia sativa</span>; B. <span class="html-italic">Bromus inermis</span>; A, <span class="html-italic">Avena sativa</span>; O, <span class="html-italic">Onobrychis viciaefolia</span> Scop. (M/V-B is M-B or V-B, same below.) (<b>A</b>) Significant differences in the root surface area of each pasture under different intercropping patterns. (<b>B</b>) Root total length. (<b>C</b>) Total root volume. (<b>D</b>) Average root diameter. (<b>E</b>) Root crossing. (<b>F</b>) Root tips. Differences in the geometric parameters of plant roots under different intercropping patterns. Different lowercase letters (a, b) indicate that the root system of the grass species was significantly different among planting patterns (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>CK: monocrop for each herbage; M, <span class="html-italic">Medicago sativa;</span> V, <span class="html-italic">Vicia sativa</span>; B, <span class="html-italic">Bromus inermis;</span> A, <span class="html-italic">Avena sativa</span>; O, <span class="html-italic">Onobrychis viciaefolia</span> Scop. (M/V-B is M-B or V-B, same below.) (<b>A</b>) Significant differences in the topological index of each pasture under different intercropping patterns. (<b>B</b>) Corrected topological index (q<sub>a</sub>). (<b>C</b>) Corrected topological index (q<sub>b</sub>). (<b>D</b>) Root fractal dimension. (<b>E</b>) Link number. Different lowercase letters (a, b, and c) indicate that the root system of the grass species was significantly different among planting patterns (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Correlation analysis of the root parameters. Alfalfa (<b>A</b>), common vetch (<b>B</b>), smooth brome (<b>C</b>), and oat (<b>D</b>). TRL: total root length; TRSA: total root surface area; TRV: total root volume; ARD: average root diameter; RT: root tips; RC: root crossing; FD: fractal dimension; TI: topological index; q<sub>a</sub>, q<sub>b</sub>: corrected topological index; Pe: link number.</p>
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14 pages, 1039 KiB  
Article
Soil Carbon, Nitrogen and Phosphorus Fractions and Response to Microorganisms and Mineral Elements in Zanthoxylum planispinum ‘Dintanensis’ Plantations at Different Altitudes
by Yingu Wu and Yanghua Yu
Agronomy 2023, 13(2), 558; https://doi.org/10.3390/agronomy13020558 - 15 Feb 2023
Cited by 4 | Viewed by 2476
Abstract
The Carbon (C), nitrogen (N) and phosphorus (P) fractions, mineral element concentrations, microbial density, and biomass in 0–10 and 10–20 cm soil fractions under Zanthoxylum planispinum ‘dintanensis’ plantations, were measured at altitudes of 531, 640, 780, 871, and 1097 m in the mountainous [...] Read more.
The Carbon (C), nitrogen (N) and phosphorus (P) fractions, mineral element concentrations, microbial density, and biomass in 0–10 and 10–20 cm soil fractions under Zanthoxylum planispinum ‘dintanensis’ plantations, were measured at altitudes of 531, 640, 780, 871, and 1097 m in the mountainous karst areas of Guizhou Province, Southwest China, and the correlations between altitude and the soil variables were analyzed. The results showed that: (1) with the increase in altitude, there was no significant linear change in C fractions, total N, effective N, microorganism density, or mineral element concentration in each soil layer; however, ammonium-N and nitrate-N concentrations gradually decreased, and the P fraction was higher at the highest altitude; (2) soil C, N, and P fractions, concentrations of microorganisms and mineral elements at the same altitude showed a surface aggregation effect; (3) principal component analysis identified the main indicators affecting C, N and P fractions as total calcium, effective calcium, effective iron, total zinc, and bacteria; (4) correlation analysis showed that both total N and C fractions were positively correlated with effective N and P fractions and that mineral element concentrations were more closely correlated with C, N, and (especially) P fractions than with microorganism abundance. Overall, the effect of altitude on C, N, and P fractions showed that the correlation with soluble organic carbon was stronger than particulate organic carbon and easily oxidized carbon, inorganic N was closer correlated than organic N, and organic P was closer correlated than inorganic P. In conclusion, it shows that research focusing on soil N conservation, nutrient stoichiometry balance, and application of mineral-rich element fertilizers is important for Zanthoxylum planispinum ‘dintanensis’ plantation maintenance. Full article
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<p>Effect of altitude on the concentration of total organic carbon (<b>A</b>), dissolved organic carbon (<b>B</b>), particulate organic carbon (<b>C</b>), easily oxidizable carbon (<b>D</b>), total nitrogen (<b>E</b>), available nitrogen (<b>F</b>), ammonium nitrogen (<b>G</b>), nitrate nitrogen (<b>H</b>), total phosphorus (<b>I</b>), available phosphorus (<b>J</b>), closed storage phosphorus (<b>K</b>), calcium phosphorus (<b>L</b>), moderately active phosphorus (<b>M</b>), active phosphorus (<b>N</b>), phosphorus in agglomerates (<b>O</b>), of soils in different soil depths of the <span class="html-italic">Zanthoxylum planispinum</span> ‘dintanensis’ plantation. Different uppercase letters indicate significant differences among different altitudes at the same soil depth (<span class="html-italic">p</span> &lt; 0.05), whereas different lowercase letters indicate significant differences between different soil depths at the same altitude (<span class="html-italic">p</span> &lt; 0.05). Data points represent mean ± standard deviation.</p>
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<p>Effect of altitude on soil bacteria (<b>A</b>), fungi (<b>B</b>), actinomycetes (<b>C</b>), microbial biomass carbon (<b>D</b>), microbial biomass nitrogen (<b>E</b>), microbial biomass phosphorus (<b>F</b>) at different soil depths of the <span class="html-italic">Zanthoxylum planispinum</span> ‘dintanensis’ plantation. Different uppercase letters indicate significant differences among different altitudes in the same soil depth (<span class="html-italic">p</span> &lt; 0.05), whereas different lowercase letters indicate significant differences between different soil depths at the same altitude (<span class="html-italic">p</span> &lt; 0.05). Data points represent mean ± standard deviation.</p>
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<p>Effect of altitude on the total calcium (<b>A</b>), available calcium (<b>B</b>), total magnesium (<b>C</b>), available magnesium (<b>D</b>), total iron (<b>E</b>), available iron (<b>F</b>), total zinc (<b>G</b>), available zinc (<b>H</b>) in soil at different soil depths of the <span class="html-italic">Zanthoxylum planispinum</span> ‘dintanensis’ plantation. Different uppercase letters indicate significant differences among different altitudes at the same soil depth (<span class="html-italic">p</span> &lt; 0.05), whereas different lowercase letters indicate significant differences between different soil depths at the same altitude (<span class="html-italic">p</span> &lt; 0.05). Data points represent mean ± standard deviation.</p>
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