Pub Date : 2024-10-19DOI: 10.1016/j.fcr.2024.109613
<div><h3>Context</h3><div>Soil water and fertility management have been the main challenges of crop production in West Africa, and their impacts are exacerbated by climate variability. While research has been conducted to optimize fertility and water applications for rainfed crops production in this region, little is known about the management of these resources for off-season cereal crops production.</div></div><div><h3>Objective</h3><div>This study assessed the optimal combination of irrigation and fertilizer levels for off-season maize production in Benin, using the DSSAT CERES-Maize crop model.</div></div><div><h3>Methods</h3><div>Two years’ experiments (2018 and 2019) of 4 levels of deficit nutrient (DN) and two years’ experiments (2019 and 2020) of 4 levels of deficit irrigation (DI) were conducted and data were collected on maize growth and yield. DSSAT model was calibrated using crop data from DN experiment in 2018 (DN2018) and DI experiment in 2019 (DI2019), and validated using the DN2019 and the DI2020 experimental data. Then, a long-term scenarios analysis (40-years, 1980–2019) was performed to optimize (i) DI levels, (ii) DN rates; and (iii) combined DI levels and DN rates.</div></div><div><h3>Results</h3><div>The model predicted the grain yield (GY) and total aboveground biomass (TB), with a relative root mean square error and a coefficient of efficiency of 18.3 % and 0.38 for the GY and 11.7 % and 0.50 for the TB during the validation, respectively. However, the model did not account for the effects of DI or DN on the phenological dates, which led to similar predicted values for the anthesis and maturity dates among DI and DN treatments during calibration and validation. Moreover, the model was sensitive to periods with high values of temperature (>45°C) recorded during the DI period, inducing a reduction of the grain filling rate in DI treatments. DI treatments were more sensitive to a change in DUL, SLL, SAT, RGFIL and RUE than the DN treatments; while the DN treatments were more sensitive to the CTCNP2. Reducing maize water requirements by 40 % at the vegetative stage resulted in similar predicted grain yield as in the full irrigation treatment; while reducing the water requirements by 60 % resulted in similar predicted water use efficiency (WUE) as in the full irrigation treatment. Furthermore, the inter-annual variability of grain yield was lower under the optimal DI combined with no fertilizer but higher under high DI combined with higher fertilizer rates. Finally, a combination of 40–60 % of deficit irrigation at the vegetative stage and one-third to half of the recommended fertilizer rates depending on resources availability was the optimum combination of DI and DN rates for off-season maize production.</div></div><div><h3>Conclusions</h3><div>The projected grain yield and WUE under optimal DI and DN levels were likely underestimated due to shortcomings in the model structure to deal with effects of water and nutrient str
背景土壤水分和肥力管理一直是西非作物生产的主要挑战，而气候多变性又加剧了其影响。本研究利用 DSSAT CERES-Maize 作物模型，评估了贝宁反季节玉米生产中灌溉和施肥水平的最佳组合。方法进行了两年（2018 年和 2019 年）4 级赤字养分（DN）试验和两年（2019 年和 2020 年）4 级赤字灌溉（DI）试验，并收集了玉米生长和产量数据。利用 2018 年（DN2018 年）缺养试验和 2019 年（DI2019 年）缺灌试验的作物数据对 DSSAT 模型进行了校准，并利用 DN2019 年和 DI2020 年的试验数据进行了验证。结果该模型预测了谷物产量（GY）和总地上生物量（TB），在验证过程中，GY 的相对均方根误差和效率系数分别为 18.3 % 和 0.38，TB 的相对均方根误差和效率系数分别为 11.7 % 和 0.50。然而，该模型没有考虑 DI 或 DN 对物候期的影响，这导致校准和验证期间 DI 和 DN 处理的开花期和成熟期预测值相似。此外，该模型对 DI 期间记录的高温度值（45°C）很敏感，导致 DI 处理的谷粒灌浆率降低。DI 处理比 DN 处理对 DUL、SLL、SAT、RGFIL 和 RUE 的变化更敏感；而 DN 处理对 CTCNP2 更敏感。将玉米无性期的需水量减少 40%，预测的谷物产量与全灌溉处理相似；将需水量减少 60%，预测的水分利用效率（WUE）与全灌溉处理相似。此外，在最佳 DI 和不施肥的情况下，谷物产量的年际变异性较低，但在高 DI 和高施肥量的情况下，谷物产量的年际变异性较高。结论 由于模型结构在处理水分和养分胁迫对物候期的影响方面存在缺陷，因此在最佳 DI 和 DN 水平下的预计谷物产量和 WUE 很可能被低估。为了可靠地评估水分和养分胁迫对谷物产量和WUE的影响，需要更新DSSAT中CERES作物模型的参数化和代码，以充分考虑水分和养分胁迫对物候期的影响，以及物候期对LAI和产量预测的贡献。
{"title":"Optimizing deficit irrigation and fertilizer application for off-season maize production in Northern Benin","authors":"","doi":"10.1016/j.fcr.2024.109613","DOIUrl":"10.1016/j.fcr.2024.109613","url":null,"abstract":"<div><h3>Context</h3><div>Soil water and fertility management have been the main challenges of crop production in West Africa, and their impacts are exacerbated by climate variability. While research has been conducted to optimize fertility and water applications for rainfed crops production in this region, little is known about the management of these resources for off-season cereal crops production.</div></div><div><h3>Objective</h3><div>This study assessed the optimal combination of irrigation and fertilizer levels for off-season maize production in Benin, using the DSSAT CERES-Maize crop model.</div></div><div><h3>Methods</h3><div>Two years’ experiments (2018 and 2019) of 4 levels of deficit nutrient (DN) and two years’ experiments (2019 and 2020) of 4 levels of deficit irrigation (DI) were conducted and data were collected on maize growth and yield. DSSAT model was calibrated using crop data from DN experiment in 2018 (DN2018) and DI experiment in 2019 (DI2019), and validated using the DN2019 and the DI2020 experimental data. Then, a long-term scenarios analysis (40-years, 1980–2019) was performed to optimize (i) DI levels, (ii) DN rates; and (iii) combined DI levels and DN rates.</div></div><div><h3>Results</h3><div>The model predicted the grain yield (GY) and total aboveground biomass (TB), with a relative root mean square error and a coefficient of efficiency of 18.3 % and 0.38 for the GY and 11.7 % and 0.50 for the TB during the validation, respectively. However, the model did not account for the effects of DI or DN on the phenological dates, which led to similar predicted values for the anthesis and maturity dates among DI and DN treatments during calibration and validation. Moreover, the model was sensitive to periods with high values of temperature (>45°C) recorded during the DI period, inducing a reduction of the grain filling rate in DI treatments. DI treatments were more sensitive to a change in DUL, SLL, SAT, RGFIL and RUE than the DN treatments; while the DN treatments were more sensitive to the CTCNP2. Reducing maize water requirements by 40 % at the vegetative stage resulted in similar predicted grain yield as in the full irrigation treatment; while reducing the water requirements by 60 % resulted in similar predicted water use efficiency (WUE) as in the full irrigation treatment. Furthermore, the inter-annual variability of grain yield was lower under the optimal DI combined with no fertilizer but higher under high DI combined with higher fertilizer rates. Finally, a combination of 40–60 % of deficit irrigation at the vegetative stage and one-third to half of the recommended fertilizer rates depending on resources availability was the optimum combination of DI and DN rates for off-season maize production.</div></div><div><h3>Conclusions</h3><div>The projected grain yield and WUE under optimal DI and DN levels were likely underestimated due to shortcomings in the model structure to deal with effects of water and nutrient str","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1016/j.fcr.2024.109616
<div><h3>Context or problem</h3><div>Soil nutrient deficiency is one of the significant challenges in grain production, particularly nitrogen (N), phosphorus (P), and potassium (K). These deficiencies not only reduce crop yields but also cause associated environmental issues, such as soil structure deterioration and ecosystem services diminution.</div></div><div><h3>Objectives</h3><div>This research aimed to investigate the long-term effects of NPK fertilizers on soil nutrient properties and maize phenology, further on the grain yield, and to evaluate the nutrient use efficiency and soil nutrient balance under different fertilization managements.</div></div><div><h3>Methods</h3><div>A long-term field experiment was initiated in 1990 in a summer maize field in the North China Plain, including five fertilizer treatments: CK (control), NP, NK, PK, and NPK. The soil nutrient properties, maize yields, crop nutrient uptake amount, nutrient recovery efficiency (NRE), nutrient harvest index (NHI), and soil nutrient balance were annually evaluated from 2005 to 2022.</div></div><div><h3>Results</h3><div>Significant improvements in maize yields were found under NPK (9081 kg ha<sup>−1</sup>), NP (6426 kg ha<sup>−1</sup>), and PK (2668 kg ha<sup>−1</sup>) compared with CK (1809 kg ha<sup>−1</sup>) and NK (1656 kg ha<sup>−1</sup>). The yield increase was mainly attributed to: (1) enhancing in soil nutrient properties, such as soil organic carbon, soil total N (TN), available N (AN), total P (TP), available P (AP), and available K (AK), and (2) the shortened vegetative period, leading to greater sunshine hours (SH) and accumulative growing degree days (GDD) during the reproductive period. Furthermore, a random forest analysis quantified their importance to grain yield, showing that the edaphic factors (mainly SOC, TN, AK, AN, TP, AP, C:N, and N:P) explained a much greater proportion of yield variation compared with phenological factors (mainly GDD during tasseling and physiological maturity stages, and SH during tasseling stage). Additionally, the significantly higher response ratio of both N and P to NRE and NHI implied that N and P fertilizers having a more pronounced impact on improving nutrient use efficiency than K fertilizer. In terms of soil nutrient balance, a most relative soil nutrient balance was detected under NPK treatment, avoiding either substantial nutrient depletion or accumulation under any nutrient deficiency conditions.</div></div><div><h3>Conclusions</h3><div>Soil deficiencies in N and P had more severe impacts on maize yields and nutrient use efficiency compared with K deficiency. Additionally, a balanced NPK fertilizer regime effectively managed soil nutrient balance.</div></div><div><h3>Implications or significance</h3><div>These findings elucidate the roles of N, P, and K fertilizers in maize production and soil nutrient conditions from a long-term field experiment, which could provide valuable insights for optimizing fertilization mana
背景或问题土壤养分缺乏是谷物生产面临的重大挑战之一，尤其是氮（N）、磷（P）和钾（K）。本研究旨在探讨氮磷钾肥对土壤养分性质和玉米物候的长期影响，进一步研究氮磷钾肥对谷物产量的影响，并评估不同施肥管理下的养分利用效率和土壤养分平衡。方法1990年在华北平原的一块夏玉米田中开始了一项长期田间试验，包括五个肥料处理：1990年在华北平原夏玉米田进行了一项长期田间试验，包括五个肥料处理：CK（对照）、NP、NK、PK和NPK。结果 与 CK（1809 kg ha-1）和 NK（1656 kg ha-1）相比，NPK（9081 kg ha-1）、NP（6426 kg ha-1）和 PK（2668 kg ha-1）显著提高了玉米产量。增产的主要原因是(1) 提高了土壤养分性质，如土壤有机碳、土壤全氮（TN）、可利用氮（AN）、全磷（TP）、可利用磷（AP）和可利用钾（AK）；(2) 缩短了植株生长期，导致生育期日照时数（SH）和累积生长度日数（GDD）增加。此外，随机森林分析量化了这些因素对谷物产量的重要性，结果表明，与物候因素（主要是抽穗期和生理成熟期的 GDD 以及抽穗期的 SH）相比，土壤因素（主要是 SOC、TN、AK、AN、TP、AP、C:N 和 N:P）解释了更大比例的产量变化。此外，氮肥和磷肥对 NRE 和 NHI 的响应比率明显较高，这意味着氮肥和磷肥对提高养分利用效率的影响比钾肥更明显。在土壤养分平衡方面，氮磷钾肥处理的土壤养分相对最平衡，在任何养分缺乏条件下都避免了养分的大量消耗或积累。这些研究结果通过长期田间试验阐明了氮、磷、钾肥在玉米生产和土壤养分状况中的作用，为优化施肥管理策略提供了有价值的见解。
{"title":"Impacts of nitrogen (N), phosphorus (P), and potassium (K) fertilizers on maize yields, nutrient use efficiency, and soil nutrient balance: Insights from a long-term diverse NPK omission experiment in the North China Plain","authors":"","doi":"10.1016/j.fcr.2024.109616","DOIUrl":"10.1016/j.fcr.2024.109616","url":null,"abstract":"<div><h3>Context or problem</h3><div>Soil nutrient deficiency is one of the significant challenges in grain production, particularly nitrogen (N), phosphorus (P), and potassium (K). These deficiencies not only reduce crop yields but also cause associated environmental issues, such as soil structure deterioration and ecosystem services diminution.</div></div><div><h3>Objectives</h3><div>This research aimed to investigate the long-term effects of NPK fertilizers on soil nutrient properties and maize phenology, further on the grain yield, and to evaluate the nutrient use efficiency and soil nutrient balance under different fertilization managements.</div></div><div><h3>Methods</h3><div>A long-term field experiment was initiated in 1990 in a summer maize field in the North China Plain, including five fertilizer treatments: CK (control), NP, NK, PK, and NPK. The soil nutrient properties, maize yields, crop nutrient uptake amount, nutrient recovery efficiency (NRE), nutrient harvest index (NHI), and soil nutrient balance were annually evaluated from 2005 to 2022.</div></div><div><h3>Results</h3><div>Significant improvements in maize yields were found under NPK (9081 kg ha<sup>−1</sup>), NP (6426 kg ha<sup>−1</sup>), and PK (2668 kg ha<sup>−1</sup>) compared with CK (1809 kg ha<sup>−1</sup>) and NK (1656 kg ha<sup>−1</sup>). The yield increase was mainly attributed to: (1) enhancing in soil nutrient properties, such as soil organic carbon, soil total N (TN), available N (AN), total P (TP), available P (AP), and available K (AK), and (2) the shortened vegetative period, leading to greater sunshine hours (SH) and accumulative growing degree days (GDD) during the reproductive period. Furthermore, a random forest analysis quantified their importance to grain yield, showing that the edaphic factors (mainly SOC, TN, AK, AN, TP, AP, C:N, and N:P) explained a much greater proportion of yield variation compared with phenological factors (mainly GDD during tasseling and physiological maturity stages, and SH during tasseling stage). Additionally, the significantly higher response ratio of both N and P to NRE and NHI implied that N and P fertilizers having a more pronounced impact on improving nutrient use efficiency than K fertilizer. In terms of soil nutrient balance, a most relative soil nutrient balance was detected under NPK treatment, avoiding either substantial nutrient depletion or accumulation under any nutrient deficiency conditions.</div></div><div><h3>Conclusions</h3><div>Soil deficiencies in N and P had more severe impacts on maize yields and nutrient use efficiency compared with K deficiency. Additionally, a balanced NPK fertilizer regime effectively managed soil nutrient balance.</div></div><div><h3>Implications or significance</h3><div>These findings elucidate the roles of N, P, and K fertilizers in maize production and soil nutrient conditions from a long-term field experiment, which could provide valuable insights for optimizing fertilization mana","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1016/j.fcr.2024.109609
<div><h3>Context</h3><div>Ratoon rice (RR) has witnessed a rapid expansion in China primarily driven by its superior profitability, cost-effectiveness and lower labor requirements compared to double-season rice (DR). Identifying proper management of irrigation and stubble height cutting is essential for balancing crop production, greenhouse gases (GHG) emissions of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O, and economic benefits in RR cropping systems. Although the grain yield of RR is significantly affected by agronomic management, little is known about how agronomic practices influence the crop production, carbon footprint (CF), and net ecosystem economic benefits (NEEB) in RR cropping systems.</div></div><div><h3>Methods</h3><div>Field experiments were conducted to investigate the impacts of stubble height and water management on grain yield, GHG emissions, CF and of NEEB of RR during the cropping seasons of 2019–2021. The treatments included DR under farmers’ conventional fertilization and irrigation management, high-stubble ratoon rice under farmers’ conventional field water management (FWP), low-stubble ratoon rice under FWP, high-stubble ratoon rice under safe alternative wetting and drying irrigation management (AWD), and low-stubble ratoon rice under AWD.</div></div><div><h3>Results</h3><div>The major CF contributor was the direct GHG emissions (<em>GHG</em><sub><em>direct</em></sub>) from crop fields in different treatments. Relative to DR, the annual CF and yield-scaled CF (<em>CF</em><sub><em>y</em></sub>) of RR were reduced by 30.2–37.0 % and 6.21–23.7 %, respectively. The decrease in CF and <em>CF</em><sub><em>y</em></sub> of RR mainly resulted from the lower cumulative emissions of CO<sub>2</sub> and CH<sub>4</sub> as well as its shorter growth duration and lower crop biomass relative to DR. Low-stubble treatment led to a significant increase in <em>GHG</em><sub><em>direct</em></sub> compared to high-stubble treatment. However, the CF of low-stubble RR did not differ significantly from that of high-stubble RR due to a substantial enhancement in the net primary production. Low-stubble management reduced the <em>CF</em><sub><em>y</em></sub> of RR by 9.4–12.1 %, due to the higher grain yield. Relative to FWP, AWD had negligible impact on crop biomass and grain yield of RR, while significantly decreased the CF and <em>CF</em><sub><em>y</em></sub> by 17.6–33.2 % and 6.21–23.7 %, respectively. Relative to FWP, the adoption of AWD resulted in a notable increase in the NEEB of RR by 6.8–20.5 %, due to the substantial mitigation in CH<sub>4</sub> emissions and lower agricultural inputs of electricity and labor. Relative to high-stubble management, low-stubble management enhanced crop N recovery and reduced potential N loss to the environment.</div></div><div><h3>Conclusion</h3><div>In RR cropping system, low-stubble management coupled with safe AWD irrigation could be a promising strategy in reducing CF while maintaining higher yiel
{"title":"Stubble height and irrigation significantly influenced the carbon footprint of ratoon rice cropping system in South China","authors":"","doi":"10.1016/j.fcr.2024.109609","DOIUrl":"10.1016/j.fcr.2024.109609","url":null,"abstract":"<div><h3>Context</h3><div>Ratoon rice (RR) has witnessed a rapid expansion in China primarily driven by its superior profitability, cost-effectiveness and lower labor requirements compared to double-season rice (DR). Identifying proper management of irrigation and stubble height cutting is essential for balancing crop production, greenhouse gases (GHG) emissions of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O, and economic benefits in RR cropping systems. Although the grain yield of RR is significantly affected by agronomic management, little is known about how agronomic practices influence the crop production, carbon footprint (CF), and net ecosystem economic benefits (NEEB) in RR cropping systems.</div></div><div><h3>Methods</h3><div>Field experiments were conducted to investigate the impacts of stubble height and water management on grain yield, GHG emissions, CF and of NEEB of RR during the cropping seasons of 2019–2021. The treatments included DR under farmers’ conventional fertilization and irrigation management, high-stubble ratoon rice under farmers’ conventional field water management (FWP), low-stubble ratoon rice under FWP, high-stubble ratoon rice under safe alternative wetting and drying irrigation management (AWD), and low-stubble ratoon rice under AWD.</div></div><div><h3>Results</h3><div>The major CF contributor was the direct GHG emissions (<em>GHG</em><sub><em>direct</em></sub>) from crop fields in different treatments. Relative to DR, the annual CF and yield-scaled CF (<em>CF</em><sub><em>y</em></sub>) of RR were reduced by 30.2–37.0 % and 6.21–23.7 %, respectively. The decrease in CF and <em>CF</em><sub><em>y</em></sub> of RR mainly resulted from the lower cumulative emissions of CO<sub>2</sub> and CH<sub>4</sub> as well as its shorter growth duration and lower crop biomass relative to DR. Low-stubble treatment led to a significant increase in <em>GHG</em><sub><em>direct</em></sub> compared to high-stubble treatment. However, the CF of low-stubble RR did not differ significantly from that of high-stubble RR due to a substantial enhancement in the net primary production. Low-stubble management reduced the <em>CF</em><sub><em>y</em></sub> of RR by 9.4–12.1 %, due to the higher grain yield. Relative to FWP, AWD had negligible impact on crop biomass and grain yield of RR, while significantly decreased the CF and <em>CF</em><sub><em>y</em></sub> by 17.6–33.2 % and 6.21–23.7 %, respectively. Relative to FWP, the adoption of AWD resulted in a notable increase in the NEEB of RR by 6.8–20.5 %, due to the substantial mitigation in CH<sub>4</sub> emissions and lower agricultural inputs of electricity and labor. Relative to high-stubble management, low-stubble management enhanced crop N recovery and reduced potential N loss to the environment.</div></div><div><h3>Conclusion</h3><div>In RR cropping system, low-stubble management coupled with safe AWD irrigation could be a promising strategy in reducing CF while maintaining higher yiel","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1016/j.fcr.2024.109612
Context
Intercropping has gained attention as a strategy to diversify cereal-based systems and enhance sustainability. However, its performance in Mediterranean conditions, especially in non-organic farming, remains less explored.
Objective
Assess the performance of intercropping under contrasting nitrogen (N) fertilisation levels to enhance productivity in the Mediterranean region.
Methods
Three intercropping (IC) systems were compared with their respective sole crops under on-farm irrigated conditions in the Ebro Valley (NE Spain). The mixtures included rapeseed/pea (IC-RP) and durum wheat/pea (IC-WP) over three seasons from 2021 to 2023, and durum wheat/faba bean (IC-WF) in 2022 and 2023. A row intercropping design was set at a 50/50 replacement ratio, with two N fertilisation treatments: 0 N (no mineral N) and +N (75 kg mineral N ha−1, with additional pre-sowing fertilisation with pig slurry applied at 165 kg N ha−1 in 2023 only). Key variables included grain yield, land equivalent ratio (LER), overyielding index, biomass and N concentration.
Results
The IC-WP and IC-WF showed reduced legumes yields due to competition, with no overyielding or increased land use efficiency (LER=0.94 and 0.86, respectively). In contrast, IC-RP exhibited increased land use efficiency (LER=1.43), though with high variability, and achieved overyielding (+9 %) in only one out of the three years.
Conclusions
Intercropping productivity in Mediterranean areas depends heavily on species selection. Pairing species with different physiology, like rapeseed and pea, promotes temporal niche differentiation and compensation mechanisms. Conversely, closer-matched species like wheat and legumes tend to intensify competition, reducing benefits.
Implications or significance
Several indicators are necessary to assess intercropping performance. Rapeseed-pea intercropping warrants deeper exploration in Mediterranean conditions.
{"title":"Rapeseed-pea intercrop outperforms wheat-legume ones in land-use efficiency in Mediterranean conditions","authors":"","doi":"10.1016/j.fcr.2024.109612","DOIUrl":"10.1016/j.fcr.2024.109612","url":null,"abstract":"<div><h3>Context</h3><div>Intercropping has gained attention as a strategy to diversify cereal-based systems and enhance sustainability. However, its performance in Mediterranean conditions, especially in non-organic farming, remains less explored.</div></div><div><h3>Objective</h3><div>Assess the performance of intercropping under contrasting nitrogen (N) fertilisation levels to enhance productivity in the Mediterranean region.</div></div><div><h3>Methods</h3><div>Three intercropping (IC) systems were compared with their respective sole crops under on-farm irrigated conditions in the Ebro Valley (NE Spain). The mixtures included rapeseed/pea (IC-RP) and durum wheat/pea (IC-WP) over three seasons from 2021 to 2023, and durum wheat/faba bean (IC-WF) in 2022 and 2023. A row intercropping design was set at a 50/50 replacement ratio, with two N fertilisation treatments: 0 N (no mineral N) and +N (75 kg mineral N ha<sup>−1</sup>, with additional pre-sowing fertilisation with pig slurry applied at 165 kg N ha<sup>−1</sup> in 2023 only). Key variables included grain yield, land equivalent ratio (LER), overyielding index, biomass and N concentration.</div></div><div><h3>Results</h3><div>The IC-WP and IC-WF showed reduced legumes yields due to competition, with no overyielding or increased land use efficiency (LER=0.94 and 0.86, respectively). In contrast, IC-RP exhibited increased land use efficiency (LER=1.43), though with high variability, and achieved overyielding (+9 %) in only one out of the three years.</div></div><div><h3>Conclusions</h3><div>Intercropping productivity in Mediterranean areas depends heavily on species selection. Pairing species with different physiology, like rapeseed and pea, promotes temporal niche differentiation and compensation mechanisms. Conversely, closer-matched species like wheat and legumes tend to intensify competition, reducing benefits.</div></div><div><h3>Implications or significance</h3><div>Several indicators are necessary to assess intercropping performance. Rapeseed-pea intercropping warrants deeper exploration in Mediterranean conditions.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-12DOI: 10.1016/j.fcr.2024.109607
Context
Several meta-analyses have demonstrated that intercropping increases land use efficiency and fertilizer use efficiency of grain-producing crop species, but no overarching synthesis has been made on the effects of fertilizer management on fertilizer use efficiency.
Research questions
Here we assess the relative N use efficiency of species mixtures compared to sole crops under different N input strategies using global data.
Methods
We built a global database of yield and fertilizer N input with 600 data records representing the results of 136 independent experiments from 80 publications with four main types of species functional combinations (SFCs), based on key traits that were found relevant in previous intercropping studies: C3-cereal/legume, maize/legume, C4-non-maize/legume and maize/C3-cereal.
Results
We found that the literature reports results for four main N input strategies in the intercrop and sole crops: (1) zero fertilizer N input (Nic=N1=N2=0), (2) equal fertilizer N input (Nic=N1=N2>0), (3) intermediate fertilizer N input (N1≥Nic≥N2 and N1>N2), and (4) transgressive fertilizer N input (Nic>N1≥N2), where N1, N2 and Nic represent the N input in sole crop 1, sole crop 2 and the intercrop. With zero N input, high land equivalent ratio was found in cereal/legume intercrops but not in maize/C3-cereal intercrops. Intermediate N input (strategy 3) resulted in high LER (land equivalent ratio) and FNER (fertilizer N equivalent ratio) because of the high intercropping advantage of cereals in C3-cereal/legume, maize/legume, and C4-non-maize/legume intercrops and maize in maize/C3-cereal intercrops. Equal N input in the sole crops and the intercrops resulted in LER and FNER being equal and N saving was entirely due to land saving, regardless of SFCs. Transgressive N input resulted in high LER but low FNER.
Conclusions
The study confirms that cereal/legume intercropping increases LER at zero N input. Strategies that tailor N input in intercropping to species demand (strategy 3) pair high productivity and LER to high fertilizer N use efficiency. The transgressive N input strategy maximizes LER at the expense of FNER, thus potentially generating high N losses.
{"title":"Nitrogen input strategies impact fertilizer nitrogen saving by intercropping: A global meta-analysis","authors":"","doi":"10.1016/j.fcr.2024.109607","DOIUrl":"10.1016/j.fcr.2024.109607","url":null,"abstract":"<div><h3>Context</h3><div>Several meta-analyses have demonstrated that intercropping increases land use efficiency and fertilizer use efficiency of grain-producing crop species, but no overarching synthesis has been made on the effects of fertilizer management on fertilizer use efficiency.</div></div><div><h3>Research questions</h3><div>Here we assess the relative N use efficiency of species mixtures compared to sole crops under different N input strategies using global data.</div></div><div><h3>Methods</h3><div>We built a global database of yield and fertilizer N input with 600 data records representing the results of 136 independent experiments from 80 publications with four main types of species functional combinations (SFCs), based on key traits that were found relevant in previous intercropping studies: C3-cereal/legume, maize/legume, C4-non-maize/legume and maize/C3-cereal.</div></div><div><h3>Results</h3><div>We found that the literature reports results for four main N input strategies in the intercrop and sole crops: (1) zero fertilizer N input (N<sub>ic</sub>=N<sub>1</sub>=N<sub>2</sub>=0), (2) equal fertilizer N input (N<sub>ic</sub>=N<sub>1</sub>=N<sub>2</sub>>0), (3) intermediate fertilizer N input (N<sub>1</sub>≥N<sub>ic</sub>≥N<sub>2</sub> and N<sub>1</sub>>N<sub>2</sub>), and (4) transgressive fertilizer N input (N<sub>ic</sub>>N<sub>1</sub>≥N<sub>2</sub>), where N<sub>1</sub>, N<sub>2</sub> and N<sub>ic</sub> represent the N input in sole crop 1, sole crop 2 and the intercrop. With zero N input, high land equivalent ratio was found in cereal/legume intercrops but not in maize/C3-cereal intercrops. Intermediate N input (strategy 3) resulted in high LER (land equivalent ratio) and FNER (fertilizer N equivalent ratio) because of the high intercropping advantage of cereals in C3-cereal/legume, maize/legume, and C4-non-maize/legume intercrops and maize in maize/C3-cereal intercrops. Equal N input in the sole crops and the intercrops resulted in LER and FNER being equal and N saving was entirely due to land saving, regardless of SFCs. Transgressive N input resulted in high LER but low FNER.</div></div><div><h3>Conclusions</h3><div>The study confirms that cereal/legume intercropping increases LER at zero N input. Strategies that tailor N input in intercropping to species demand (strategy 3) pair high productivity and LER to high fertilizer N use efficiency. The transgressive N input strategy maximizes LER at the expense of FNER, thus potentially generating high N losses.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-11DOI: 10.1016/j.fcr.2024.109606
Poor fertilizer management and intensive tillage have increased production costs, lowered productivity, and significantly depleted soil nutrients. Although nutrient management options (NMOs) within crop establishment options (CEOs) based maize production system (MPS) is seldom explored, CEOs is increasingly advocated to tackle problems with soil health, food security, and climate change. Developing and implementing effective NMOs is needed for improving system sustainability, profitability, and productivity. We evaluated the effects of CEOs and NMOs on nutrient acquisition, profitability, and maize productivity in the Northwestern Indo-Gangetic Plains (IGPs) of India during 2018–2019. In this study, four CEOs treatment [(i) conventional tillage without residue {CT–R}, (ii) conventional tillage with residue {CT+R}, (iii) permanent raised bed without residue {PRB–R}, and (iv) permanent raised bed with residue {PRB+R}], were kept in the main plot and three NMOs [(i) soil test-based recommendation {STBR}, (ii) nutrient expert-based recommendation {NE}, and (iii) NE with GreenSeeker {NE+GS} were tested in subplots. The results showed that the crop growth metrics, including plant height, dry matter accumulation, leaf area index, and crop growth rate, were significantly greater at PRB+R comparing to treatments. Additionally, PRB+R resulted in the shortest time to 50 % and 75 % silking, indicating enhanced crop development. NMOs significantly improved crop growth parameters. The NE+GS treatment recorded higher plant height (145.8–149.2 cm and 222.3–224.8 cm), dry matter accumulation (195.5–198.4 g/m² and 408.4–412.0 g/m²), leaf area index (2.45–2.48 and 3.24–3.30), and crop growth rate (6.50 and 7.10 g/m²/day). PRB+R showed the shortest silking times (60.5 and 62.2 days). PRB+R also attained the maximum maize yield (6.23 and 6.26 t/ha), by a 17.82 % and 17.57 % increase over CT–R in 2018 and 2019. The NE+GS treatment resulted in the highest maize productivity, with additional yield gains over NE alone and STBR. The lowest cultivation cost ($513.87/ha and $513.97 /ha), highest net return ($1028.91/ha and $1083.60/ha), and best benefit-cost ratio (2.00 and 2.11) were observed with PRB–R, while gross returns ($1573.78/ha and $1630.42/ha) had highest in PRB+R. The NE+GS option achieved higher gross returns ($1544.73/ha and $1599.37/ha), net returns ($918.29/ha and $977.30/ha), and benefit-cost ratios (1.47 and 1.57) with lower cultivation costs ($626.43/ha and $622.06/ha) compared to NE and STBR. The PRB+R and NE+GS combination had found highest nutrient uptake (N, P, K) in grain and straw, highlighting their effectiveness in nutrient management. Overall, our findings recommend adopting PRB+R and NE+GS to optimize maize production system productivity and profitability, ensuring agricultural sustainability and resilience to adverse climatic conditions in Northwest India.
{"title":"Crop establishment and nutrient management options: Optimizing productivity, maximize profitability and mitigating adverse climatic conditions in the maize-based production system of Northwest India","authors":"","doi":"10.1016/j.fcr.2024.109606","DOIUrl":"10.1016/j.fcr.2024.109606","url":null,"abstract":"<div><div>Poor fertilizer management and intensive tillage have increased production costs, lowered productivity, and significantly depleted soil nutrients. Although nutrient management options (NMOs) within crop establishment options (CEOs) based maize production system (MPS) is seldom explored, CEOs is increasingly advocated to tackle problems with soil health, food security, and climate change. Developing and implementing effective NMOs is needed for improving system sustainability, profitability, and productivity. We evaluated the effects of CEOs and NMOs on nutrient acquisition, profitability, and maize productivity in the Northwestern Indo-Gangetic Plains (IGPs) of India during 2018–2019. In this study, four CEOs treatment [(i) conventional tillage without residue {CT–R}, (ii) conventional tillage with residue {CT+R}, (iii) permanent raised bed without residue {PRB–R}, and (iv) permanent raised bed with residue {PRB+R}], were kept in the main plot and three NMOs [(i) soil test-based recommendation {STBR}, (ii) nutrient expert-based recommendation {NE}, and (iii) NE with GreenSeeker {NE+GS} were tested in subplots. The results showed that the crop growth metrics, including plant height, dry matter accumulation, leaf area index, and crop growth rate, were significantly greater at PRB+R comparing to treatments. Additionally, PRB+R resulted in the shortest time to 50 % and 75 % silking, indicating enhanced crop development. NMOs significantly improved crop growth parameters. The NE+GS treatment recorded higher plant height (145.8–149.2 cm and 222.3–224.8 cm), dry matter accumulation (195.5–198.4 g/m² and 408.4–412.0 g/m²), leaf area index (2.45–2.48 and 3.24–3.30), and crop growth rate (6.50 and 7.10 g/m²/day). PRB+R showed the shortest silking times (60.5 and 62.2 days). PRB+R also attained the maximum maize yield (6.23 and 6.26 t/ha), by a 17.82 % and 17.57 % increase over CT–R in 2018 and 2019. The NE+GS treatment resulted in the highest maize productivity, with additional yield gains over NE alone and STBR. The lowest cultivation cost ($513.87/ha and $513.97 /ha), highest net return ($1028.91/ha and $1083.60/ha), and best benefit-cost ratio (2.00 and 2.11) were observed with PRB–R, while gross returns ($1573.78/ha and $1630.42/ha) had highest in PRB+R. The NE+GS option achieved higher gross returns ($1544.73/ha and $1599.37/ha), net returns ($918.29/ha and $977.30/ha), and benefit-cost ratios (1.47 and 1.57) with lower cultivation costs ($626.43/ha and $622.06/ha) compared to NE and STBR. The PRB+R and NE+GS combination had found highest nutrient uptake (N, P, K) in grain and straw, highlighting their effectiveness in nutrient management. Overall, our findings recommend adopting PRB+R and NE+GS to optimize maize production system productivity and profitability, ensuring agricultural sustainability and resilience to adverse climatic conditions in Northwest India.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-11DOI: 10.1016/j.fcr.2024.109610
Context
In high-latitude regions, variable weather conditions during the growing season and in winter cause considerable variation in forage grass productivity. Tools for predicting grassland status and yield, such as field measurements, satellite image analysis and process-based simulation models, can be combined in decision support for grassland management. Here, we calibrated and validated the BASic GRAssland (BASGRA) model against dry matter and Leaf area index data from temporary grasslands in northern Norway.
Objective
The objective of this study was to compare the performance of model versions calibrated against i) only region-specific ground data, ii) both region-specific ground and Sentinel-2 satellite data and, iii) field trial data from other regions.
Methods
Ground and satellite sensed data including biomass dry matter, leaf area index, and autumn and spring ground cover from 2020 to 2022 were acquired from 13 non-permanent grassland fields at four locations. These data were input to BASGRA calibrations together with soil and daily weather data, and information about cutting and nitrogen fertilizer application regimes. The effect of the winter season was taken into account in simulations by initiating the simulations either in autumn or in early spring.
Results
Within datasets, initiating the model in spring resulted in higher dry matter prediction accuracy (normalised RMSE 22.3–54.0 %) than initiating the model in autumn (normalised RMSE 41.1–93.4 %). Regional specific calibrations resulted in more accurate biomass predictions than calibrations from other regions while using satellite sensing data in addition to ground data resulted in only minor changes in biomass prediction accuracy.
Conclusion
All regional calibrations against data from northern Norway changed model parameter values and improved dry matter prediction accuracy compared with the reference calibration parameter values. Including satellite-sensed data in addition to ground data in calibrations did not further increase prediction accuracy compared with using only ground data.
Implications
Our findings show that regional data from farmers’ fields can substantially improve the performance of the BASGRA model compared to using controlled field trial data from other regions. This emphasises the need to account for regional diversity in non-permanent grassland when estimating grassland production potential and stress impact across geographic regions. Further use of satellite data in grassland model calibrations would probably benefit from more detailed assessments of the effect of grass growth characteristics and light and cloud conditions on estimates of grassland leaf area index and biomass from remote sensing.
{"title":"Combining satellite-sensed and ground data and the BASGRA model to predict grass yield in high-latitude regions","authors":"","doi":"10.1016/j.fcr.2024.109610","DOIUrl":"10.1016/j.fcr.2024.109610","url":null,"abstract":"<div><h3>Context</h3><div>In high-latitude regions, variable weather conditions during the growing season and in winter cause considerable variation in forage grass productivity. Tools for predicting grassland status and yield, such as field measurements, satellite image analysis and process-based simulation models, can be combined in decision support for grassland management. Here, we calibrated and validated the BASic GRAssland (BASGRA) model against dry matter and Leaf area index data from temporary grasslands in northern Norway.</div></div><div><h3>Objective</h3><div>The objective of this study was to compare the performance of model versions calibrated against i) only region-specific ground data, ii) both region-specific ground and Sentinel-2 satellite data and, iii) field trial data from other regions.</div></div><div><h3>Methods</h3><div>Ground and satellite sensed data including biomass dry matter, leaf area index, and autumn and spring ground cover from 2020 to 2022 were acquired from 13 non-permanent grassland fields at four locations. These data were input to BASGRA calibrations together with soil and daily weather data, and information about cutting and nitrogen fertilizer application regimes. The effect of the winter season was taken into account in simulations by initiating the simulations either in autumn or in early spring.</div></div><div><h3>Results</h3><div>Within datasets, initiating the model in spring resulted in higher dry matter prediction accuracy (normalised RMSE 22.3–54.0 %) than initiating the model in autumn (normalised RMSE 41.1–93.4 %). Regional specific calibrations resulted in more accurate biomass predictions than calibrations from other regions while using satellite sensing data in addition to ground data resulted in only minor changes in biomass prediction accuracy.</div></div><div><h3>Conclusion</h3><div>All regional calibrations against data from northern Norway changed model parameter values and improved dry matter prediction accuracy compared with the reference calibration parameter values. Including satellite-sensed data in addition to ground data in calibrations did not further increase prediction accuracy compared with using only ground data.</div></div><div><h3>Implications</h3><div>Our findings show that regional data from farmers’ fields can substantially improve the performance of the BASGRA model compared to using controlled field trial data from other regions. This emphasises the need to account for regional diversity in non-permanent grassland when estimating grassland production potential and stress impact across geographic regions. Further use of satellite data in grassland model calibrations would probably benefit from more detailed assessments of the effect of grass growth characteristics and light and cloud conditions on estimates of grassland leaf area index and biomass from remote sensing.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-10DOI: 10.1016/j.fcr.2024.109605
Context
Global dimming reduces incident radiation, and thus affects rice yield. Canopy structure is closely related to light interception, internal light distribution, photosynthesis and radiation use efficiency (RUE). However, less attention is paid to the effects of global dimming on rice canopy structure. Whether weak light leads to poor canopy structure and thus affects light distribution and RUE, thereby reducing dry matter accumulation and grain yield remains unknown.
Objective and methods
The objectives of this study were to explore the effects of global dimming on canopy structure, and its relationships with canopy light distribution and RUE under artificially simulated weak light in hybrid rice. Field experiments with two rice hybrids (Y-liangyou900, YLY900; Chuanyou6203, CY6203) were conducted under no shading (CK), 40 % shading at booting stage (S) and 40 % shading at grain-filling stage (SS) in 2021 and 2022.
Results
The effects of shading on the growth characteristics and yield of rice varied with different varieties. Shading at booting stage resulted in larger basal, opening and drooping angles of the top three leaves of both varieties. This rise in leaf angles increased the light extinction coefficient (KL) of YLY900, but it had no significant effect on CY6203. Shading significantly reduced RUE during the total growth period, with reductions of 24.3 % and 16.8 % under S, and 11.1 % and 8.9 % under SS for YLY900 and CY6203 in two years, respectively. The total dry weight of YLY900 under S and SS was 34.6 % and 22.8 % lower than that under CK in both years, accordingly, the total dry weight of CY6203 was 27.0 % and 21.6 % lower, respectively. Ultimately, shading resulted in a significant decrease in grain yield compared with CK, and the effect of S on yield was greater than that of SS because of the significantly lower spikelet differentiation under S. In terms of varieties, shading had a greater effect on canopy structure, light distribution and RUE of YLY900 than that of CY6203, which explained yield advantage of CY6203 over YLY900 under shading.
Conclusions
Shading increased leaf angles of the top three leaves and caused a draped canopy structure. This change affected the canopy light distribution and RUE. Therefore, the varieties with slightly draped upper leaves might be better able to adapt to the global dimming and reduce yield loss.
Implications or significance
Understanding the changes of canopy structure, light distribution and RUE under shading were highly significant for the breeding and cultivation of climate-dependent varieties.
背景全球气候变暗会减少入射辐射，从而影响水稻产量。冠层结构与光拦截、内光分布、光合作用和辐射利用效率（RUE）密切相关。然而，人们较少关注全球光照变暗对水稻冠层结构的影响。本研究的目的是探讨全球调光对杂交水稻冠层结构的影响，以及在人工模拟弱光条件下冠层光分布和辐射利用效率的关系。结果遮光对水稻生长特性和产量的影响因品种而异。在抽穗期遮光会导致两个品种前三片叶片的基角、开角和下垂角增大。叶片角度的增加提高了 YLY900 的光消光系数（KL），但对 CY6203 没有显著影响。遮光明显降低了整个生长期的RUE，YLY900和CY6203在S条件下分别降低了24.3%和16.8%，在SS条件下分别降低了11.1%和8.9%。在 S 和 SS 条件下，YLY900 两年的总干重分别比 CK 条件下低 34.6 % 和 22.8 %，相应地，CY6203 的总干重分别低 27.0 % 和 21.6 %。在品种方面，遮光对 YLY900 的冠层结构、光分布和 RUE 的影响均大于 CY6203，这说明在遮光条件下 CY6203 比 YLY900 具有产量优势。这一变化影响了冠层光照分布和产量。影响或意义了解遮光条件下冠层结构、光分布和RUE的变化对培育和种植气候依赖型品种意义重大。
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Pub Date : 2024-10-09DOI: 10.1016/j.fcr.2024.109602
<div><h3>Context</h3><div>The use of alfalfa in rotation with intensive crops is common practice to mitigate the physical and chemical issues arising from intensive farming practices. However, there is a dearth of studies on this practice. Given the current concern regarding climate change and the significant impact agriculture has on greenhouse gas (GHG) emissions, understanding the emissions associated with this practice, as well as the most suitable soil and crop management techniques for their mitigation, is of paramount importance.</div></div><div><h3>Objective</h3><div>The present study aimed to (i) quantify emissions of N<sub>2</sub>O, CO<sub>2</sub> and CH<sub>4</sub> in an alfalfa crop following a maize cropping scenario; (ii) to determine which tillage system generates the lowest GHG emissions, and; (iii) to determine how N fertilisation from a preceding intensive maize crop affects GHG emissions during alfalfa cropping period.</div></div><div><h3>Methods</h3><div>A three-year field experiment (2019, 2020 and 2021) was conducted to assess the emissions of N<sub>2</sub>O, CO<sub>2</sub> and CH<sub>4</sub> from alfalfa cultivation following a three-year period of irrigated maize. Two soil management practices (no-tillage and conventional tillage) were implemented during both the maize cropping period and the alfalfa establishment. Additionally, the nitrogen (N) fertilisation rates applied to the preceding maize crop were included as a treatment (0, 200, and 400 kg N ha⁻¹, corresponding to zero, medium, and high fertilisation levels, respectively) in a randomized block design with two factors.</div></div><div><h3>Results</h3><div>Emissions of N<sub>2</sub>O in alfalfa ranged from 0.05 to 0.32 mg N<sub>2</sub>O-N m⁻² day⁻¹, being significantly higher only during first month of sampling in the treatments that had received fertilisation. CO<sub>2</sub> emissions ranged from 1158 to 4258 mg CO<sub>2</sub>-C m⁻² day⁻¹. Year-average CH<sub>4</sub> fluxes were −0.27 g C ha⁻¹ day⁻¹. The average total dry matter produced by alfalfa was 17700 kg ha⁻¹ year⁻¹, being higher for the no-tillage treatment, though significantly so only during first month of sampling.</div></div><div><h3>Conclusions</h3><div>Under Mediterranean conditions, the tillage system and mineral N fertilizer rates have a relative effect on greenhouse gas emissions during the alfalfa cropping period. Plots without N fertilization initially produced lower N<sub>2</sub>O emissions and higher total dry matter, resulting in the lowest scaled emissions. For the tillage treatment, no significant differences were found in emission dynamics, which may be due to the fact that alfalfa does not involve soil disturbance, leading to a homogenization of the treatments. However, the NT treatment showed lower scaled emissions due to higher yields in the first year. Therefore, alfalfa cultivation is characterized by low GHG emissions, high yields, and a notable capacity to mitigate the negative effec
背景使用紫花苜蓿与集约化作物轮作是缓解集约化耕作带来的物理和化学问题的常见做法。然而，有关这种做法的研究却很少。鉴于当前人们对气候变化的关注以及农业对温室气体排放的重大影响，了解与这种做法相关的排放以及最适合的土壤和作物管理技术对缓解这些问题至关重要。本研究旨在：(i) 量化玉米种植方案后紫花苜蓿作物的一氧化二氮、二氧化碳和甲烷排放量；(ii) 确定哪种耕作制度产生的温室气体排放量最低；(iii) 确定之前密集型玉米作物的氮肥如何影响紫花苜蓿种植期间的温室气体排放量。方法 进行了一项为期三年（2019 年、2020 年和 2021 年）的田间试验，以评估灌溉玉米三年后紫花苜蓿种植的一氧化二氮、二氧化碳和甲烷排放量。在玉米种植期和紫花苜蓿生长期采用了两种土壤管理方法（免耕和常规耕作）。结果紫花苜蓿中的一氧化二氮排放量从 0.05 到 0.32 毫克一氧化二氮-氮平方米天¹不等，只有在第一个月采样时，施过肥的处理中的一氧化二氮排放量明显较高。二氧化碳排放量为 1158 至 4258 毫克 CO2-C m² 天-¹。全年平均甲烷通量为-0.27 g C ha-¹ day-¹。结论在地中海条件下，耕作制度和矿物氮肥施用量对紫花苜蓿种植期间的温室气体排放有相对影响。未施用氮肥的地块最初产生的一氧化二氮排放量较低，干物质总量较高，因此按比例计算的排放量最低。在耕作处理中，排放动态没有发现显著差异，这可能是由于紫花苜蓿不涉及土壤扰动，导致处理的同质性。不过，由于第一年产量较高，NT 处理的按比例排放较低。因此，紫花苜蓿种植的特点是温室气体排放量低、产量高，并能显著减轻以往密集型作物的负面影响。 意义 本研究提供了地中海灌溉系统下典型的玉米-紫花苜蓿轮作中紫花苜蓿种植期间的温室气体排放数据，这对旨在减少农业污染的新农业政策很有帮助。此外，它还证明了这种作物有能力缓解之前的集约化耕作方式造成的不利农艺和环境条件。
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Pub Date : 2024-10-07DOI: 10.1016/j.fcr.2024.109599
Context or problem
There is an urgent need to address the contradiction between maize production and soil nutrient shortages to achieve efficient maize production with minimum fertilizer, labor and environmental costs. Determination of rational Nitrogen (N) application patterns is the key to solving this problem.
Objective or research question
N application is an effective strategy to improve maize N uptake (NU), yield and water use efficiency (WUE). However, the effects of different N application patterns on maize NU, yield and WUE vary greatly, and it is difficult to determine the great-yield and high-efficiency N application pattern for maize in the Loess Plateau region according to a single experimental study.
Methods
We synthesized 102 studies (102 sites) in the Loess Plateau region of China to evaluate the effects of different N application patterns (BU: basal urea; TU: basal and topdressing urea; S/C: slow/controlled release urea; S/CU: slow/controlled release urea mixed with normal urea) on maize NU, yield, WUE, and N use efficiency (NUE), and explored their responses to different climates, soil physicochemical properties, and field management practices.
Results
N application significantly increased the maize NU, yield and WUE. S/CU pattern significantly improved maize NU, yield and WUE the most with 110.74 %, 83.13 % and 86.21 %, respectively, compared to non-N application. S/C pattern showed the greatest increase in NUE of maize (3.47 %). Random forest analysis showed that growing season precipitation (GSP) was the most important determinant of the impact of N fertilizer application on maize NU, yield and WUE, while soil total nitrogen (TN) content was the most important determinant of maize NUE. The greatest increase in S/CU pattern yield and WUE enhanced when GSP and MAT were 200–400 mm and ≤ 10 °C, respectively. N application was more effective in increasing maize yield and WUE when the soil texture was clay loam and SOM < 10 g kg−1. Film mulching also further increased maize NU, yield, and WUE. In addition, variety of “Xianyu 335” had higher effect sizes for NU, yield and WUE than “Zhengdan 958”.
Conclusions
S/CU pattern obtained greater maize yield and WUE with lower fertilizer and labor costs, the suitable rate of nitrogen application was determined to be 165.20 kg ha−1 and the urea mix ratio was 65 %.
Implications or significance
The results would provide theoretical support and technical guidance for great-yield and high-efficiency green production of maize in the Loess Plateau of China.
背景或问题迫切需要解决玉米生产与土壤养分短缺之间的矛盾，从而以最低的肥料、劳动力和环境成本实现高效玉米生产。确定合理的施氮（N）模式是解决这一问题的关键。目标或研究问题施氮是提高玉米氮吸收量（NU）、产量和水分利用效率（WUE）的有效策略。然而，不同施氮模式对玉米氮吸收量、产量和水分利用效率的影响差异很大，很难根据单一的试验研究确定黄土高原地区玉米的高产高效施氮模式。方法 我们综合了中国黄土高原地区的102项研究（102个点），评估了不同施氮模式（BU：基施尿素；TU：基施和表施尿素；S/C：缓控释尿素；S/CU：缓控释尿素与普通尿素混合施用）对玉米氮素单位面积、产量、水分利用率和氮素利用效率（NUE）的影响，并探讨了它们对不同气候、土壤理化性质和田间管理措施的响应。结果 施用氮能明显提高玉米氮素单位、产量和水分利用效率。与不施用氮肥相比，S/CU 模式对玉米营养单位、产量和水分利用效率的提高最大，分别为 110.74 %、83.13 % 和 86.21 %。S/C 模式对玉米氮利用效率的提高最大（3.47%）。随机森林分析表明，生长季降水量（GSP）是决定施用氮肥对玉米NU、产量和WUE影响的最重要因素，而土壤全氮（TN）含量是决定玉米NUE的最重要因素。当 GSP 和 MAT 分别为 200-400 mm 和 ≤ 10 °C 时，S/CU 模式产量和 WUE 的增幅最大。当土壤质地为粘壤土、SOM < 10 g kg-1 时，施氮能更有效地提高玉米产量和水分利用效率。地膜覆盖也进一步提高了玉米的氮素单位、产量和WUE。结论S/CU 模式以较低的肥料成本和劳动力成本获得了较高的玉米产量和WUE，确定适宜的施氮量为 165.20 kg ha-1，尿素混合比例为 65%。
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