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  Subjects -> AGRICULTURE (Total: 847 journals)
    - AGRICULTURAL ECONOMICS (75 journals)
    - AGRICULTURE (594 journals)
    - CROP PRODUCTION AND SOIL (97 journals)
    - DAIRYING AND DAIRY PRODUCTS (29 journals)
    - POULTRY AND LIVESTOCK (52 journals)

AGRICULTURE (594 journals)

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Journal Cover European Journal of Agronomy
  [SJR: 1.488]   [H-I: 75]   [9 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1161-0301
   Published by Elsevier Homepage  [3175 journals]
  • Trait identification of faba bean ideotypes for Northern European
           environments
    • Authors: G. Bodner; A. Kronberga; L. Lepse; M. Olle; I.M. Vågen; L. Rabante; J.A. Fernández; G. Ntatsi; A. Balliu; B. Rewald
      Pages: 1 - 12
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): G. Bodner, A. Kronberga, L. Lepse, M. Olle, I.M. Vågen, L. Rabante, J.A. Fernández, G. Ntatsi, A. Balliu, B. Rewald
      European pulse production faces a continued loss of cultivated area along with decreasing or stagnant yields. Vicia faba is a traditional legume with high genetic diversity cultivated in a wide range of European climates. Therefore V. faba is promising to identify stable and high yielding genotypes for specific target environments. The Nordic-Baltic region is challenging for legume growing due to short vegetation period and heat/drought stress in continental climates. Within the pan-European Eurolegume project a set of 18 V. faba accessions containing var. minor and major local landraces and modern cultivars of different geographical origin was evaluated in multi-environmental trials. The aim of this study was to identify ideotypes for Northern Europe and reveal key phenotypic traits conferring high yield potential and stability. Four target environmental clusters represented the range of Nordic growing conditions with yield levels from 128 g m−2 to 380 g m−2. Multivariate classification differentiated distinctive groups of var. minor and var. major accessions with few overlapping genotypes, the former having higher average yield, taller structure, more pods per node and longer flowering duration. Late sowing under long-day conditions above 55°N latitudes resulted in early flowering due to short vegetative development (650 °Cd). Extended flowering duration and tall stature were the most important traits conferring high yields. A negative trade-off between yield potential and yield stability was detected, with yield advantages of stress resistant genotypes only in a limited range of low yielding target environments (<180 g m−2). The highest yielding accessions (Latvian var. minor landrace Bauska and var. major landrace Cēres) represented a favourable combination of yield potential and stability. High temperatures at flowering, within a range of average maximum July temperatures between 20.5–24.5 °C, were identified as most critical environmental variable depressing yield levels between 38.5 (var. major) and 56.2 (var. minor) g m−2 °C−1. It was concluded that Baltic landraces are promising ideotypes, with adapted flowering phenology and morphological structure, for increased V. faba yields in Nordic target environments.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.02.008
      Issue No: Vol. 96 (2018)
       
  • Predicting genotypic differences in irrigated sugarcane yield using the
           Canegro model and independent trait parameter estimates
    • Authors: Natalie Hoffman; Abraham Singels; Alana Patton; Sanesh Ramburan
      Pages: 13 - 21
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): Natalie Hoffman, Abraham Singels, Alana Patton, Sanesh Ramburan
      Crop models have the potential to support plant breeding by predicting genotype response to environmental factors, and identifying desirable genetic traits for improved crop performance. The study tested whether the Canegro sugarcane model can predict genotypic differences in stalk dry mass (SDM) yields observed in field trials using independently derived genetic trait information. Other objectives included the estimation of three trait parameters (TP) for selected genotypes, and assessing their role in determining genotypic differences in SDM yields. Phenotyping was conducted in a well-watered pot trial at Mount Edgecombe, South Africa comprising 14 genotypes. Gross photosynthate produced per unit of intercepted photosynthetically active radiation under ideal conditions (PARCEo) was estimated from leaf level photosynthetic efficiency (A) and stomatal conductance (gs ). Thermal time from shoot emergence to the start of stalk elongation (CHUPIBASE) was estimated from measurements of leaf number. Maximum fraction of aerial dry biomass growth partitioned to stalks (STKPFMAX) was estimated from the measured stalk fraction of aerial biomass at harvest. Values of PARCEo (A) and PARCEo (gs ) differed significantly between genotypes with a range of 47% and 67% of the mean, respectively. CHUPIBASE values also differed significantly between genotypes and showed a range of 23% of the mean. STKPFMAX values did not differ significantly between genotypes and showed the least variation with a range of 17% of the mean. The Canegro model predicted SDM yields and rankings well (r = 0.90**) for nine genotypes grown in well-watered field trials at Pongola, South Africa, using these independent estimates of PARCEo (A), CHUPIBASE and STKPFMAX values. The overestimation of the observed genotypic range in SDM yields were corrected by dynamically scaling leaf level photosynthetic efficiency using fractional sunlit leaf area. The reliable prediction of genotype performance was mostly ascribed to the impact of PARCEo. The extent of genetic variation in PARCEo found in the relatively small number of genotypes for well-watered crops, suggest that sugarcane improvement could be enhanced by screening breeding populations for high values of this trait. The study provided proof of concept that realistic sugarcane models could be used for identifying key traits (in this case PARCEo) and their ideal values (in this case as high as possible), and therefore could be used to assist in defining sugarcane breeding targets.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.01.005
      Issue No: Vol. 96 (2018)
       
  • Crucifer glucosinolate production in legume-crucifer cover crop mixtures
    • Authors: Antoine Couëdel; Lionel Alletto; John Kirkegaard; Éric Justes
      Pages: 22 - 33
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): Antoine Couëdel, Lionel Alletto, John Kirkegaard, Éric Justes
      Cover crops grown in rotation with cash crops provide ecosystem services by reducing water pollution and anthropogenic inputs. Bispecific crucifer–legume cover crop mixtures are seen as a solution to increase biodiversity and to combine ecosystem services of both species. Legumes fix nitrogen while crucifers have the capacity to suppress pathogens due to the biocidal hydrolysis products of the endogenous secondary metabolites called glucosinolates (GSL). However there is a lack of information on the impact of plant–plant interactions in the crucifer-legume mixtures on crucifer GSL production compared to sole crop. The aim of our study was to assess GSL production of a wide range of bispecific crucifer-legume mixtures in comparison to sole crops. Experiments were conducted at two sites (near Toulouse and Orléans, France) over two years. Various cultivars from eight crucifer (Brassicaceae) species (rape, white mustard, Indian mustard, Ethiopian mustard, turnip, turnip rape, radish and rocket) and nine legume (Fabaceae) species (Egyptian clover, crimson clover, common vetch, purple vetch, hairy vetch, pea, soya bean, faba bean, and white lupin) were tested in sole crop and bispecific mixtures (substitutive design of 50%–50% sole crops). We show that for a wide range of species, crucifers in cover crop mixtures had the same GSL types, concentrations and proportions (aliphatic, aromatic and indole) as in sole crops. Crucifers in mixtures tended to have more biomass per plant, both for shoots and roots, than in sole crops so that the total GSL production per plant generally increased in the mixture compared to the sole crop. Thus despite halving the crucifer density in the mixtures the GSL production on an area basis declined by only 20%. These results have been validated for a wide range of crucifer species and provide support for crucifer-legume mixtures to produce nutrient-related services while potentially maintaining high GSL production. Specific experiments are needed to evaluate whether this double effect of unchanged GSL concentration and small reduction in GSL production has an impact on the biofumigation potential of cover crop mixtures compared to sole crucifers.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.02.007
      Issue No: Vol. 96 (2018)
       
  • Impact of nutrient supply on the expression of genetic improvements of
           cereals and row crops – A case study using data from a long-term
           fertilization experiment in Germany
    • Authors: Victor Rueda-Ayala; Hella Ellen Ahrends; Stefan Siebert; Thomas Gaiser; Hubert Hüging; Frank Ewert
      Pages: 34 - 46
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): Victor Rueda-Ayala, Hella Ellen Ahrends, Stefan Siebert, Thomas Gaiser, Hubert Hüging, Frank Ewert
      Impacts of nutrient supply and different cultivars (genotypes) on actual yield levels have been studied before, but the long-term response of yield trends is hardly known. We present the effects of 24 different fertilizer treatments on long-term yield trends (1953–2009) of winter wheat, winter rye, sugar beet and potato, with improved cultivars changing gradually over time. Data was obtained from the crop rotation within the long-term fertilization experiment at Dikopshof, Germany. Yield trends were derived as the slope regression estimates between adjusted yield means and polynomials of the first year of cultivation of each tested cultivar, when tested for more than two years. A linear trend fitted best all data and crops. Yields in highly fertilized treatments increased linearly, exceeding 0.08 t ha−1 a−1 for both, winter wheat and winter rye, and ≥0.30 and ≥0.20 t ha−1 a−1 for sugar beet and potato fresh matter yields. Yield trends of winter cereals and sugar beet increased over time at N rates ≥40 kg ha−1 a−1, being 0.04–0.10 t ha−1 a−1 for cereals and 0.26–0.34 t ha−1 a−1 for sugar beet, although N rates >80 kg ha−1 a−1 produced a stronger effect. Nitrogen was the most influential nutrient for realisation of the genetic yield potential. Additional supply of P and K had an effect on yield trends for rye and sugar beet, when N fertilization was also sufficient; high K rates benefited potato yield trends. We highlight the importance of adequate nutrient supply for maintaining yield progress to actually achieve the crop genetic yield potentials. The explicit consideration of the interaction between crop fertilization and genetic progress on a long-term basis is critical for understanding past and projecting future yield trends. Long-term fertilization experiments provide a suitable data source for such studies.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.03.002
      Issue No: Vol. 96 (2018)
       
  • Effects of foliar fertilization of a biostimulant obtained from chicken
           feathers on maize yield
    • Authors: Manuel Tejada; Bruno Rodríguez-Morgado; Patricia Paneque; Juan Parrado
      Pages: 54 - 59
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): Manuel Tejada, Bruno Rodríguez-Morgado, Patricia Paneque, Juan Parrado
      Due to the important contribution that it makes to human nutrition, maize is one of the most widely-consumed cereals in the world. There is, therefore, high demand for fertilizers that will maintain maize production at both high yield and quality levels. The objective of this work was to study the effect of foliar fertilization using a biostimulant, obtained by enzymatic hydrolysis from chicken feathers, on the productivity and quality of maize crops (Zea mays, L. cv PR32W86 Pioneer), located in Trujillanos (Extremadura, Spain), over two consecutive seasons. Foliar biostimulant/biofertilizer was applied three times each season and at two rates (3.6 and 7.2 l ha−1). At the higher rate and for both seasons, foliar fertilization significantly increased the leaf concentrations of macro- and micronutrients, while grain protein content and yield increased by 26% and 14%. These results suggest that the foliar use of this biostimulant could be of great interest to the farmer for improving both maize crop yield and quality.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.03.003
      Issue No: Vol. 96 (2018)
       
  • Responses of yield, CH4 and N2O emissions to elevated atmospheric
           temperature and CO2 concentration in a double rice cropping system
    • Authors: Bin Wang; Jianling Li; Yunfan Wan; Yu’e Li; Xiaobo Qin; Qinzhu Gao; Muhammad Ahmed Waqas; Andreas Wilkes; Weiwei Cai; Songcai You; Shouhua Zhou
      Pages: 60 - 69
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): Bin Wang, Jianling Li, Yunfan Wan, Yu’e Li, Xiaobo Qin, Qinzhu Gao, Muhammad Ahmed Waqas, Andreas Wilkes, Weiwei Cai, Songcai You, Shouhua Zhou
      Elevated atmospheric temperature and CO2 concentration ([CO2]) can strongly affect yield, CH4 and N2O emissions in rice paddies. However, understanding of their response to combined temperature and [CO2] increases under field conditions is still limited. To study this issue further, an open-top chamber (OTC) platform was set up to simulate two levels of atmospheric temperature (ambient and 2 °C elevated) and two levels of [CO2] (ambient and 60 ppm elevated) during two rotations of double rice, including twelve independent OTCs and three un-chambered open field sites as trial plots. The experimental site is located in Hubei Province, Central China, which has a subtropical monsoon climate. In all four rice seasons, elevated CO2 induced an increment in grain yield by 11.4–19.7%, while also enhancing CH4 and N2O emissions by 19.8–52.6% and 102.4–140.0%, respectively, compared with ambient temperature and [CO2]. Elevated temperature enhanced CH4 emissions by 4.4–36.0%, and decreased N2O emissions by 1.5–10.5% in three rice seasons. Elevated temperature had different effects on grain yield, with a reduction of 1.0–3.2% in early rice and an increase of 6.3–9.2% in late rice. When elevated temperature and [CO2] were combined, there was a positive interaction that further enhanced CH4 emissions and yield of late rice, and an offsetting effect on N2O emissions and yield of early rice. Over the 2-year experiment, warming and CO2 enrichment caused an increase of 9.3–44.2% in greenhouse gas intensity, suggesting that more greenhouse gas emissions will be emitted to produce a unit mass of rice under projected global warming. These findings provide initial data for the estimation of CH4 and N2O emissions under elevated temperature and [CO2] in double rice cropping system, and stress the need for effective management practices that promote rice yield while reducing greenhouse gas emissions.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.01.014
      Issue No: Vol. 96 (2018)
       
  • Source-sink manipulations indicate seed yield in canola is limited by
           source availability
    • Authors: Heping Zhang; Sam Flottmann
      Pages: 70 - 76
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): Heping Zhang, Sam Flottmann
      In canola, strong competition for assimilates from the overlapping of structural and reproductive growth can lead canola yield to be limited by source availability during seed filling. In this study, we tested this hypothesis by manipulating source-sink relationships in a series of experiments (i) shading during flowering and during seed filling, (ii) partial removal of flowers and pods of individual plants, (iii) defoliation at the vegetative stage and after full flowering, and (iv) supplemental irrigation during seed filling. Shading (60% of incoming radiation reduction) during flowering reduced the number of pods and seeds (sink) but increased mean seed weight (MSW), resulting in 24% yield loss. Shading during seed-filling reduced MSW as well as the number of pods and seeds per area and, causing 26% yield reduction compared to the control. Partial pod removal and full defoliation at full flowering decreased pods per plant and reduced yield by10–40%. Defoliation during the vegetative stage reduced yield by 11%. Supplemental irrigation increased yield by 10% without any impact on MSW. However, these manipulations simultaneously either reduced or increased the sink size (seeds m−2) while altering the source availability. If the manipulated plants were assumed to have a similar sink size to the control, shading would have decreased MSW by 16–22%. Similarly, the full defoliation after full flowering decreased MSW by 27% and the defoliation at the vegetative stage by 11%. On the contrary, supplemental irrigation would have increased MSW by 8–21%. The decrease in MSW in the downward-manipulation of source availability and the increase in MSW in the upward-manipulation of source availability indicate that canola yield was driven by source availability during seed filling period. However, yield reduction from shading at flowering indicates that yield could be limited by sink size established during flowering. Therefore, agronomic management and future breeding should be directed to increase assimilates available to the crop from flowering onwards.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.03.005
      Issue No: Vol. 96 (2018)
       
  • Future climate change projects positive impacts on sugarcane productivity
           in southern China
    • Authors: Hongyan Ruan; Puyu Feng; Bin Wang; Hongtao Xing; Garry J. O’Leary; Zhigang Huang; Hao Guo; De Li Liu
      Pages: 108 - 119
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): Hongyan Ruan, Puyu Feng, Bin Wang, Hongtao Xing, Garry J. O’Leary, Zhigang Huang, Hao Guo, De Li Liu
      Climate change is recognised to alter the distribution of rainfall and increase temperature and atmospheric CO2 concentration [CO2] and pose a formidable challenge to the sustainability of various cropping industries around the world. Additionally, in specific regions, like China, and for particular crops, like sugarcane, the likely effects of climate change are not straightforward. This is because of non-linearity of the interacting climatic factors on crop growth and yield. In our study, the APSIM-Sugarcane model was used to examine the likely response of sugarcane in future climate scenarios. Statistically downscaled climate data based on 28 global climate models (GCMs) under RCP4.5 and RCP8.5 scenarios were used to generate the change in climate in southern China. The results show that the model well reproduced observations for biomass dry matter (DM), biomass fresh matter (FM), sugar yields (S) and leaf area index (LAI), with values for the index of agreement of 0.65, 0.71, 0.84 and 0.70, respectively. The values of RMSE were relatively low with 7.10 t ha−1 for DM, 18.87 t ha−1 for FM, 0.84 t ha−1 for S and 1.03 m2 m−2 for LAI. On average, the ensemble of downscaled GCM projections showed a small increase in radiation and rainfall in the future at the four locations considered, with significantly increased temperature. Sugarcane yields in southern China appeared to be positively affected under future climate and [CO2] changes. Overall, DM was projected to increase by 5.6 and 6.4 and 6.6 t ha−1 for RCP4.5 in 2030s, 2060s and 2090s relative to 1961–2010, respectively. However, RCP8.5 had less promotion compared to RCP4.5 on DM. Similar increased trends for three future time periods could be found in FM and S. Our results showed that the largest percentage change in S occurred at high latitude locations (e.g., Hezhou), with mean values 28.1% and 39.4% for RCP4.5 and RCP8.5 in 2030s, 44.2% and 23.5% in 2060s, and 41.1% and 45.5% for in 2090s, respectively. In addition, our multiple linear regression analyses showed that the changes in radiation, rainfall and temperature together with elevated [CO2] could explain more than 70% of sugarcane yields change across four locations. Across all locations, increases in sugarcane yields were strongly correlated (P = .001) with each degree (Celsius) increase in future temperature and per mm increase in future rainfall. For example, the DM, FM and S increased 7.8–14.2, 16.6–36.1 and 2.7–6.1 kg ha−1 mm−1 responding to rainfall, respectively. Although uncertainties in our study on the impact of climate change on sugarcane might arise from the choice of crop model and GCMs, the results would be pivotal for developing high-yield adaptive strategies as well as informing policy makers to improve sugarcane productivity in China.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.03.007
      Issue No: Vol. 96 (2018)
       
  • Comparison of dry seeded and puddled transplanted rainy season rice on the
           High Ganges River Floodplain of Bangladesh
    • Authors: M. Jahangir Alam; E. Humphreys; M.A.R. Sarkar; Sudhir-Yadav
      Pages: 120 - 130
      Abstract: Publication date: May 2018
      Source:European Journal of Agronomy, Volume 96
      Author(s): M. Jahangir Alam, E. Humphreys, M.A.R. Sarkar, Sudhir-Yadav
      In the High Ganges River Floodplain of Bangladesh, rice is normally established by puddling and transplanting. This is a costly practice in terms of tillage, labour and irrigation requirement. Dry seeding of rice has the potential to reduce these costs and facilitate timely crop establishment. However, the performance of dry seeded rice (DSR) in other parts of South Asia has been variable in comparison with that of puddled transplanted rice (PTR). Therefore, a four-year replicated experiment was conducted to compare the performance of PTR and DSR, grown during the rainy season, in the High Ganges River Floodplain. There were two tillage treatments for DSR − full tillage and strip tillage. Two levels of rice residue retention (removed; partial retention) were compared in sub-plots. Grain yield of DSR was significantly (by 5% or 0.2 t ha−1) lower than the yield of PTR, while DSR reduced irrigation input by 240–880 mm over the four years. The variation in the reduction in irrigation input was due to variation in the incidence and amount of rainfall across the four years. There were no significant differences between the use of full and strip tillage for DSR for any of the measured parameters, and any effects of rice residue retention were small. The cost of production of DSR was reduced by 9% (USD 87 ha−1) in comparison with PTR, which led to a small increase in the gross margin and BCR of DSR. The results suggest that replacement of puddled transplanted aman with dry seeded aman in the High Ganges River Floodplain can be done with only a small yield loss, but with significantly reduced irrigation input, lower costs of production, and similar profitability.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.03.006
      Issue No: Vol. 96 (2018)
       
  • Estimation of plant height using a high throughput phenotyping platform
           based on unmanned aerial vehicle and self-calibration: Example for sorghum
           breeding
    • Authors: Pengcheng Hu; Scott C. Chapman; Xuemin Wang; Andries Potgieter; Tao Duan; David Jordan; Yan Guo; Bangyou Zheng
      Pages: 24 - 32
      Abstract: Publication date: April 2018
      Source:European Journal of Agronomy, Volume 95
      Author(s): Pengcheng Hu, Scott C. Chapman, Xuemin Wang, Andries Potgieter, Tao Duan, David Jordan, Yan Guo, Bangyou Zheng
      Plant height is an essential trait to evaluate in grain sorghum, being positively associated with potential grain yield. Standard manual measures of plant height for large breeding trials are labour-intensive and time-consuming. Due to potential field access issue and the remote nature of breeding trials, Unmanned Aerial vehicles (UAVs) are well-suited to measure plant height if the ground surface can be referenced. In this study, we compared existing algorithms with a new method for estimating plant height for a sorghum breeding trial. Images were captured by a RGB camera mounted on an UAV before emergence and near maturity to generate digital surface models (DSMs). Two existing methods (‘point cloud’ and ‘reference ground’) and a new method (‘self-calibration’) were used to estimate ground level and plant height at the plot level. The self-calibration method required manual measurements of the actual plant height in a sample of plots (fewer than 30), which could be completed during the 30-min flight time. UAV-derived plant heights from each method were compared to manual measurements. The self-calibration method had the best performance (R 2 = 0.63; RMSE = 0.07 m; repeatability = 0.74), with similar repeatability to manual measurement (0.78). The point cloud and reference ground methods had lower repeatabilities (0.34 and 0.38, respectively). For the self-calibration method, we tested different sampling strategies to balance accuracy and the workload of manual measurements, finding that a sample of 30–40 plots from the1440 total could obtain precision similar to manual measurement of the entire trial. The self-calibration method offers a pragmatic, robust and universal approach to high throughput phenotyping of plot plant height with UAV surveys.

      PubDate: 2018-02-26T12:46:17Z
      DOI: 10.1016/j.eja.2018.02.004
      Issue No: Vol. 95 (2018)
       
  • Data requirements for crop modelling—Applying the learning curve
           approach to the simulation of winter wheat flowering time under climate
           change
    • Authors: M. Montesino-San Martin; D Wallach; J.E. Olesen; A.J. Challinor; M.P Hoffman; A.K. Koehler; R.P Rötter; J.R. Porter
      Pages: 33 - 44
      Abstract: Publication date: April 2018
      Source:European Journal of Agronomy, Volume 95
      Author(s): M. Montesino-San Martin, D Wallach, J.E. Olesen, A.J. Challinor, M.P Hoffman, A.K. Koehler, R.P Rötter, J.R. Porter
      A prerequisite for application of crop models is a careful parameterization based on observational data. However, there are limited studies investigating the link between quality and quantity of observed data and its suitability for model parameterization. Here, we explore the interactions between number of measurements, noise and model predictive skills to simulate the impact of 2050′s climate change (RCP8.5) on winter wheat flowering time. The learning curve of two winter wheat phenology models is analysed under different assumptions about the size of the calibration dataset, the measurement error and the accuracy of the model structure. Our assessment confirms that prediction skills improve asymptotically with the size of the calibration dataset, as with statistical models. Results suggest that less precise but larger training datasets can improve the predictive abilities of models. However, the non-linear relationship between number of measurements, measurement error, and prediction skills limit the compensation between data quality and quantity. We find that the model performance does not improve significantly with a theoretical minimum size of 7–9 observations when the model structure is approximate. While simulation of crop phenology is critical to crop model simulation, more studies are needed to explore data needs for assessing entire crop models.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.02.003
      Issue No: Vol. 95 (2018)
       
  • Simulated adaptation strategies for spring wheat to climate change in a
           northern high latitude environment by DAYCENT model
    • Authors: Xiaobo Qin; Hong Wang; Yong He; Yu’e Li; Zhiguo Li; Qingzhu Gao; Yunfan Wan; Budong Qian; Brian McConkey; Ron DePauw; Reynald Lemke; William J. Parton
      Pages: 45 - 56
      Abstract: Publication date: April 2018
      Source:European Journal of Agronomy, Volume 95
      Author(s): Xiaobo Qin, Hong Wang, Yong He, Yu’e Li, Zhiguo Li, Qingzhu Gao, Yunfan Wan, Budong Qian, Brian McConkey, Ron DePauw, Reynald Lemke, William J. Parton
      In order to identify strategies to support global food security while protecting the environment under future climate in northern high latitude environments such as the Canadian Prairies, the DAYCENT model was calibrated, validated, and subsequently used to project effects of climate change (increased carbon dioxide concentration, precipitation, and temperature), nitrogen (N) application rate, and yield potential (radiation use efficiency of biomass, RUEB) of spring wheat (Triticum aestivum L.) on yield production and environmental outputs. Results indicated that projected grain yield and environmental impacts, i.e. soil organic carbon (SOC), N leached below root zone and nitrous oxide (N2O) emission, are affected by different climate change scenarios, N fertilizer rate and RUEB. From these results, we can assess impacts of fertilizer rates on projected grain yield and environmental impacts (SOC, N leaching and N2O emission) in the near future (2017–2046) and distant future (2047–2076). In the near future, if wheat RUEB is improved from current 38–43 mg C kJ−1, the projected yield over seven climate change scenarios will increase 35% with a fertilizer rate of 100 kg N ha−1 compared to the current rate (50 kg N ha−1). Corresponding increases of N leaching, N2O emission and final SOC in 2046 are 29, 35 and 12%, respectively. Additional increases of yield and SOC will be small if more N is added, while N leaching and N2O emission will be further increased. Assuming the cultivar grown in the distant future is improved to 53 mg C kJ−1 RUEB and the fertilizer rate is raised to 125 kg N ha−1, projected yield, N leaching, N2O emission and final SOC in 2076 will be increased by 69, 26, 56 and 80%, respectively. If the N input is increased to 150 kg N ha−1, corresponding increases will be 83, 30, 103 and 151%. It seems that appropriate N input could be 100–125 kg N ha−1 for the near future and distant future, respectively in order to balance production and environmental impacts. Results of our study indicated that after modification and calibration, DAYCENT model can be used to identify adaptation strategies for food security and environmental protection in high latitude environments under future climate change.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2017.12.005
      Issue No: Vol. 95 (2018)
       
  • Agroforestry enables high efficiency of light capture, photosynthesis and
           dry matter production in a semi-arid climate
    • Authors: Dongsheng Zhang; Guijuan Du; Zhanxiang Sun; Wei Bai; Qi Wang; Liangshan Feng; Jiaming Zheng; Zhe Zhang; Yang Liu; Shu Yang; Ning Yang; Chen Feng; Qian Cai; Jochem B. Evers; Wopke van der Werf; Lizhen Zhang
      Pages: 1 - 11
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): Dongsheng Zhang, Guijuan Du, Zhanxiang Sun, Wei Bai, Qi Wang, Liangshan Feng, Jiaming Zheng, Zhe Zhang, Yang Liu, Shu Yang, Ning Yang, Chen Feng, Qian Cai, Jochem B. Evers, Wopke van der Werf, Lizhen Zhang
      Agroforestry systems, which combine annual crops with trees, are used widely in semi-arid regions to reduce wind erosion and improve resource (e.g. water) use efficiency. Limited knowledge is available on optimizing such systems by the choice of crop species with specific physiological traits (i.e. C3 vs C4, N-fixing vs non-N-fixing). In this study we quantified the light interception and utilization efficiency of trees and crops in agroforestry systems comprising apricot trees and a C3 species (sweet potato), a C4 species (millet) or an N-fixing legume species (peanut), and used measurements in the sole stands as a reference. A significant delay in leaf growth was found in millet. Maximum LAI of millet was 17% higher in agroforestry then expected from sole crop LAI, taking into account the relative density of 2/3, while a 25% decrease in maximum LAI compared to expected was observed in peanut and sweet potato. The total light interception in agroforestry was 54% higher than in sole tree stands and 23% higher than in sole crops. The millet intercepted more light and produced more biomass in agroforestry than peanut and sweet potato. The LUE values of the crops in the mixed systems were higher than those of the sole crops, as was the photosynthetic efficiency of individual leaves, especially in plants in the border rows of the crop strips. High light capture in agroforestry made a greater contribution to productivity of understory crops than the increases in light use efficiency. We conclude that agroforestry systems with apricot trees and annual crops, especially millet, can improve light utilization in semi-arid climates and contribute to regional sustainability and adaptation to climate change.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2018.01.001
      Issue No: Vol. 94 (2018)
       
  • After-effects of long-term tillage and residue management on topsoil state
           in Boreal conditions
    • Authors: Dalia Feiziene; Virginijus Feiza; Aldis Karklins; Agne Versuliene; Daiva Janusauskaite; Sarunas Antanaitis
      Pages: 12 - 24
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): Dalia Feiziene, Virginijus Feiza, Aldis Karklins, Agne Versuliene, Daiva Janusauskaite, Sarunas Antanaitis
      It is known that all processes in soil act in close interdependence and are site- and soil-specific, and climate and human activity dependent. Numerous studies have been done worldwide on soil structural composition, soil organic carbon (SOC) sequestration and soil CO2 efflux investigation, although most of published results were obtained in conditions different from the soil type, texture and climate conditions in the Nemoral-2 environmental/Boreal climatic zone. The effects of long-term tillage treatments on soil properties are seldom reported in Boreal conditions. The objective of this study was to assess the subsequent long-term cumulative effects of 17 years of conventional (CT) and no-tillage (NT) in combination with straw removal or return, on SOC accumulation, soil pore-size distribution (PSD), water release characteristics (WRC) and CO2 efflux on loam and sandy loam within a 0–10 cm layer of Cambisol during the main development stages of winter wheat. A more pronounced superiority of NT over CT for SOC sequestration rate within the topsoil layer emerged on loam than on sandy loam. The total volume of transition and storage pores, which is responsible for better soil water movement, was higher in sandy loam then in loam and under NT than under CT. However, a higher retention of topsoil moisture during the main growing stages of winter wheat was on loam than on sandy loam. Straw on loam acted as a material for soil loosening by increasing the total volume of fissures, transition and storage pores. Meanwhile, on sandy loam, the straw acted as a pore clogging material by decreasing the total volume of the same pores. Consequently, on loam, in spite of a high capability of NT with residue return to storage plant available water (PAW), the topsoil moisture during dry weather conditions at the main growing stages of winter wheat was lower than under other soil management practices. On sandy loam, NT with residue returning governed the highest PAW content and maintained the highest topsoil moisture. Nevertheless, the highest potential to reduce CO2 efflux on both loam and sandy loam has been demonstrated by CT with residue return.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2018.01.003
      Issue No: Vol. 94 (2018)
       
  • Towards improved calibration of crop models – Where are we now and
           where should we go'
    • Authors: S.J. Seidel; T. Palosuo; P. Thorburn; D. Wallach
      Pages: 25 - 35
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): S.J. Seidel, T. Palosuo, P. Thorburn, D. Wallach
      Crop simulation models are increasingly used in agricultural decision making. Calibration is a demanding and critical step in developing and applying a model. Despite its importance little attention has been paid to documenting and analysing current calibration practices. This study reports the results from 211 responses to a web-based survey of calibration practices. The survey questions covered multiple choices that are required when doing a calibration exercise. Concerning data, most respondents used field data, but regional data and a combination of field and regional data were also used. Almost all respondents used multiple data types, the most common being phenology and yield data. The median number of estimated parameters was 6, and often this number was only slightly smaller than the number of environments that provided the data. Most respondents fit the data in multiple stages, starting in most cases with phenology data. Many respondents searched for parameter values that minimized a sum of squared errors, but substantial groups used an ad hoc measure of goodness-of-fit, the GLUE method, a weighted least squares method or a Bayesian approach. Nearly half the respondents simply used trial-and-error to search for the best-fit parameters. The other respondents were split more or less equally between those who used existing software and those who wrote new software. Slightly less than half the respondents obtained information on parameter uncertainty. Model evaluation was based on goodness-of-fit or data splitting or cross validation. The median time devoted to crop model calibration was 25 days. Based on these results, a list of topics that should be covered in guidelines for calibration is suggested.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2018.01.006
      Issue No: Vol. 94 (2018)
       
  • Wheat performance with subclover living mulch in different
           agro-environmental conditions depends on crop management
    • Authors: E. Radicetti; J.P. Baresel; E.J. El-Haddoury; M.R. Finckh; R. Mancinelli; J.H. Schmidt; I. Thami Alami; S.M. Udupa; M.G.A. van der Heijden; R. Wittwer; E. Campiglia
      Pages: 36 - 45
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): E. Radicetti, J.P. Baresel, E.J. El-Haddoury, M.R. Finckh, R. Mancinelli, J.H. Schmidt, I. Thami Alami, S.M. Udupa, M.G.A. van der Heijden, R. Wittwer, E. Campiglia
      Intercropping has been proposed as a useful strategy for reducing external inputs in cereal-based cropping systems, while maintaining adequate crop yield. Intercropping of wheat and subclover, implemented as living mulch, is recommended, but there is limited experimental proof for its suitability in different environments. The main objective of this study was to provide an overview and evaluation of wheat-subclover intercropping under different agro-environmental conditions. Coordinated field experiments were conducted over a two-year period in six sites located in four agro-environmental zones [Atlantic North (Neu-Eichenberg, Germany), Continental (Freising, Germany – Tänikon, Switzerland), Mediterranean North (Viterbo, Italy), Mediterranean South (Sidi Alla Tazi and Sidi El Aidi, Morocco)]. Wheat–subclover intercropping was compared with a pure wheat. Additionally, other treatments adopted in specific sites were: soil tillage (conventional and minimum tillage); fertilization input (high and low level); cropping system (conventional and organic). The measurements recorded were: soil coverage, wheat and subclover phenological stages, wheat grain yield and yield components, subclover and weed biomass. The data of each site were analyzed separately and were also used for a meta-analysis to obtain an overview of how pedo-climatic conditions affect the interactions of subclover living mulch with wheat and weeds. Subclover biomass was the highest at Viterbo (228 g m−2 of DM) proving its adaptability to the climatic conditions of Mediterranean North characterized by mild temperature and abundant rainfall. Wheat-subclover intercropping reduced weed infestation (from 22 to 75% in Mediterranean South and North, respectively). Intercropping also resulted in grain yield losses compared to pure wheat in Mediterranean North and Continental (on average −16 and −14%, respectively), probably because of the competition between the intercropped species. In the agro-environmental zones where subclover growth was limited by cold temperatures (Atlantic North) or dry conditions (Mediterranean South), hardly any grain yield reduction of intercropped wheat was observed. Subclover biomass and wheat grain yield were also negatively correlated and yield reductions were generally due to a reduced number of fertile spikes. The yield gap between intercropped and pure wheat was reduced when: (i) there was a proper spatial arrangement of subclover and wheat; (ii) the amount of added mineral nitrogen fertilizer was reduced, while compost application did not influence the cropping systems. The use of subclover living mulch in wheat appears to be most suitable for low input systems. Future research should focus on the development of appropriate crop management practices for intercropping in order to avoid wheat yield loss.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2018.01.011
      Issue No: Vol. 94 (2018)
       
  • Uncertainty in wheat phenology simulation induced by cultivar
           parameterization under climate warming
    • Authors: Leilei Liu; Daniel Wallach; Jun Li; Bing Liu; Linxiang Zhang; Liang Tang; Yu Zhang; Xiaolei Qiu; Weixing Cao; Yan Zhu
      Pages: 46 - 53
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): Leilei Liu, Daniel Wallach, Jun Li, Bing Liu, Linxiang Zhang, Liang Tang, Yu Zhang, Xiaolei Qiu, Weixing Cao, Yan Zhu
      Rigorous calibration of crop phenology models, providing both best-estimate parameters and estimates of parameter uncertainty, is essential for evaluating how crops will respond to future environmental and management changes. Least squares parameter estimation is a widely used approach to calibration of nonlinear models, and there are many software packages available for implementing this approach. However, these packages are rarely if ever used for complex phenology models because of technical difficulties. The purpose of this research is to overcome these difficulties, in particular the issue of a model which is a discontinuous function of the parameters. The calculations were conducted with the WheatGrow phenology model, but the approach is applicable to other complex phenology models. The approach was used to calibrate WheatGrow phenology for 4 widely used cultivars in the main winter wheat production region of China. The resulting fit to the data was quite good (root mean squared error (RMSE) of 3–4 days for flowering and maturity). The coefficients of variation (CV) of the parameters ranged from 6% to 40%. Furthermore, the model was used to predict the effect of warming on phenology, and the uncertainty in those predictions. The results showed that each degree of warming reduced the time from sowing to flowering by 7–8 days for the spring cultivars and 3–4 days for the winter cultivars. The time form flowering to maturity is hardly affected. In addition, the higher the temperature, the larger the uncertainty in the predictions. Comparison with variability in multi-model ensembles suggests that parameter uncertainty is less than the model uncertainty.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2017.12.001
      Issue No: Vol. 94 (2018)
       
  • A review of tef physiology for developing a tef crop model
    • Authors: Kirsten Paff; Senthold Asseng
      Pages: 54 - 66
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): Kirsten Paff, Senthold Asseng
      Tef (Eragrostis tef (Zucc.) Trotter) is important for Ethiopian food security and a significant source of income for smallholder farmers in Ethiopia. In industrialized nations, tef is becoming a popular health food due to its lack of gluten and high nutritional value. Though tef is an important crop within Ethiopia, research on the crop has been limited. Crop models are an important tool for assessing food security, the effectiveness of management practices, and the impacts of climate change on crop production. The only existing crop models for tef are the FAO-AEZ crop growth simulation model, and the FAO AquaCrop model, which focuses on water limited crop production. The FAO AEZ model only produces final yields, which limits its applicability. The AquaCrop model has been validated using data from northern Ethiopia under current climate conditions without nitrogen limitations. As tef production spreads across the world, and Ethiopia suffers from soil fertility depletion and climate change, there is a need for a more comprehensive tef model. Tef, a short-day C4 crop, shows a high level of genetic diversity, resulting in large variation in water use, water use efficiency, growing season length, and even photosynthetic rate across cultivars. Tef quickly reaches a closed canopy, resulting in a higher early-season water use efficiency than wheat (C3 crop) or sorghum (C4 crop). Lodging is a significant yield limitation in tef, and is often exacerbated by fertilizer applications. There are several areas of tef research that have limited, or no, published data, especially on a field level, which will hinder future tef model development. These areas include the effects of temperature on photosynthesis and phenology, the effects of heat stress on senescence, the effects of elevated atmospheric CO2 on photosynthesis and transpiration, and a field level lodging model. By combining relevant information from other crops with the available tef literature, however, it should be possible to create a tef crop model prototype.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2018.01.008
      Issue No: Vol. 94 (2018)
       
  • Reduced herbicide use does not increase crop yield loss if it is
           compensated by alternative preventive and curative measures
    • Authors: Nathalie Colbach; Stéphane Cordeau
      Pages: 67 - 78
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): Nathalie Colbach, Stéphane Cordeau
      Herbicide use must be reduced because of environmental and health issues. This raises the question of whether weeds and the resulting crop yield loss will increase. Previous studies analysing relationships between herbicide use intensity, weeds and yield loss suffer from methodological shortcomings in terms of weed flora and farm diversity as well as temporal scales. Here, we collected data on 272 arable cropping systems from one Spanish and six French regions, from farm surveys, the Biovigilance-Flore network, expert opinion, cropping system trials, crop advisors and scientists. Each system was simulated over 27 years and with 10 weather repetitions consisting of 28 randomly chosen weather years, using the virtual-field model FlorSys. This process-based model simulates multi-species weed floras and crop canopies as a function of cropping systems and pedoclimate at a daily time-step over the years. Four series of simulations were run, 1) starting with a typical regional weed flora, 2) eliminating all herbicides without any other change in management practices. The two series were run again, but without an initial weed seed bank. Comparing series 1 and 2 to respectively 3 and 4 led to calculating a crop yield loss due to weeds in series 1 and 2. Comparing series 1 and 2 quantified the herbicide impact on weeds, crop production and yield loss. The simulations showed that (1) crop yield loss increased with increasing weed biomass, and that the weed/crop biomass ratio at crop flowering was the best indicator of the year’s yield loss, (2) herbicide use intensity was not correlated to either weed variables or yield loss, because herbicide use intensity greatly depended on other management practices; e.g., it decreased with increasing frequency and interannual variation of mechanical weeding and superficial tillage, (3) weed biomass and yield loss increased when herbicides were eliminated without any other change in management practices, (4) effects were more visible at the multi-annual than the annual scales. The systems the most sensitive to herbicide suppression were characterized by monotonous rotations with short crop cover, high herbicide use, no plough or winter ploughing and frequent rolling operations. Finally, a decision tree predicting yield loss as a function of management practices was proposed to support farmers and crop advisors when designing innovative cropping systems reconciling low herbicide use and low yield loss.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2017.12.008
      Issue No: Vol. 94 (2018)
       
  • Soil carbon varies between different organic and conventional management
           schemes in arable agriculture
    • Authors: Teng Hu; Peter Sørensen; Jørgen Eivind Olesen
      Pages: 79 - 88
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): Teng Hu, Peter Sørensen, Jørgen Eivind Olesen
      The effects of organic versus conventional farming systems on changes in soil organic carbon (SOC) has long been debated. The effects of such comparisons may depend considerably on the design of the respective systems and climate and soil conditions under which they are performed. Here, we compare a range of arable organic and conventional crop systems at three sites (Jyndevad, Foulum and Flakkebjerg) in Denmark through long-term experiments initiated in 1997. The experimental treatments in the organic farming systems included use of whole-year green manure crops, catch crops and animal manure (as cattle, pig or digested slurry). Data on plant residues and animal manure were used to estimate C inputs to the soil. This was compared with measured changes in topsoil (0–25 cm) SOC content over 4–8 years. During 1997–2004, green manure, catch crops and animal manure enhanced estimated C input by 0.9, 1.0 and 0.7 Mg C ha−1 yr−1 respectively, across all locations. Based on measured SOC changes, green manure enhanced SOC by 0.4 Mg C ha−1 yr−1 and catch crops by 0.2 Mg C ha−1 yr−1, while animal manure by insignificantly 0.1 Mg C ha−1 yr−1. After 2005, advantages of using green manure (grass-clover) on SOC change disappeared, because cuttings of the grass-clover was removed whereas before 2005 they were mulched in the field, albeit there was still a small extra estimated C input of 0.2 Mg C ha−1 yr−1. An estimated higher C input of 0.7 Mg C ha−1 yr−1 with catch crops did not result in significant increase in measured topsoil SOC. From 2005–2008, the first 4 years of comparison between organic and conventional farming at all three sites, organic farming with animal manure had 0.3 Mg C ha−1 yr−1 higher estimated C input, but SOC measurements showed that conventional farming accumulated 0.4 Mg C ha−1 yr−1 more SOC than organic farming. At Foulum from 2005 to 2012, organic farming with animal manure had 0.7 Mg C ha−1 yr−1 more input, and topsoil SOC measurements showed a higher accumulation of 0.4 Mg C ha−1 yr−1 in organic compared with conventional farming. Regressions of changes in topsoil SOC against estimated C inputs showed that 10–20% of C inputs were retained in topsoil SOC over the experimental period. There was no clear indication that belowground C input contributed more to SOC than aboveground C inputs. Despite consistently higher estimated C inputs in organic versus conventional systems, we were not able to detect consistent differences in measured SOC between the systems.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2018.01.010
      Issue No: Vol. 94 (2018)
       
  • Vulnerability to climatic and economic variability is mainly driven by
           farmers’ practices on French organic dairy farms
    • Authors: Maëlys Bouttes; Magali San Cristobal; Guillaume Martin
      Pages: 89 - 97
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): Maëlys Bouttes, Magali San Cristobal, Guillaume Martin
      The climatic and economic context of agricultural production is increasingly unpredictable and volatile. These issues raise questions about the vulnerability of agricultural systems, i.e. their ability to cope with, adapt to, or recover from the effects of a range of hazards. Applied to organic dairy farming, vulnerability relates to farm productivity and economic efficiency that remain controversial. Our objective was to show whether and how organic dairy farm vulnerability can be reduced by adapting agricultural diversity as well as land-use and herd-management intensities of farm configurations over time, along with contextual changes (both climatic and economic). We analyzed data from 51 organic dairy farms surveyed for 5–14 years in the northwest lowland plains and central mountains of France. Our method considered farm vulnerability as a function of the mean level of, trend in, and variability in productivity and economic efficiency and related these vulnerability variables to explanatory variables that illustrate farm exposure to climatic and economic variability and farm configurations over time using partial least square (PLS) regressions. The animal stocking rate in both regions was positively related to mean farm productivity, whereas concentrate (nutrient-rich feedstuffs e.g. soybean meal) distribution was negatively related to mean and trend of economic efficiency. On average, farm productivity responded positively to land-use intensification, but increasing farm economic efficiency required thrifty management and self-sufficiency with regard to animal feeding. Overall, it appeared that tradeoffs among vulnerability variables were driven by farmers’ practices rather than by interannual variability in rainfall amounts and energy or milk prices. This reveals that the extent to which farms must adapt to changes in the production context remains large and partly unexplored by most organic dairy farmers.

      PubDate: 2018-02-26T12:46:17Z
      DOI: 10.1016/j.eja.2018.01.013
      Issue No: Vol. 94 (2018)
       
  • Analyzing ecosystem services in apple orchards using the STICS model
    • Authors: Constance Demestihas; Daniel Plénet; Michel Génard; Iñaki Garcia de Cortazar-Atauri; Marie Launay; Dominique Ripoche; Nicolas Beaudoin; Sylvaine Simon; Marie Charreyron; Christiane Raynal; Françoise Lescourret
      Pages: 108 - 119
      Abstract: Publication date: March 2018
      Source:European Journal of Agronomy, Volume 94
      Author(s): Constance Demestihas, Daniel Plénet, Michel Génard, Iñaki Garcia de Cortazar-Atauri, Marie Launay, Dominique Ripoche, Nicolas Beaudoin, Sylvaine Simon, Marie Charreyron, Christiane Raynal, Françoise Lescourret
      Fruit tree production faces the major challenge of ensuring maximal productivity with due consideration for the environment and human health. The increasingly recognized concept of ecosystem service could help to address this duality. In this paper, we propose an analytical framework based on a soil crop model to investigate how agricultural management and pedoclimatic conditions affect the joint production of marketed and non-marketed ecosystem services through underlying ecosystem functions in apple orchards. The ecosystem services considered on an annual scale were soil nitrogen availability, climate regulation, water regulation and fruit production. Ecosystem functions and services were described by specific indicators that were quantified using the STICS soil crop model. This model was parameterized using data collected on two experimental apple orchard sites under conventional and low-input or organic management in southeastern France. The interdependencies between environmental components, cultural operations and ecosystem functions were dynamically integrated by the model and highlighted significant interactions between the indicators of ecosystem services. Thus, the service indicators soil organic nitrogen variation and the prevention of nitrogen denitrification and of leaching were positively correlated and in conflict with soil mean nitrate concentration and mean soil humidity. They were also linked negatively to nitrogen mineralization enhanced by irrigation and positively to soil carbon sequestration impacted by fertilization; these two functions were impacted by soil conditions. Yield and carbon sequestration presented a strong synergy and were positively correlated to nitrogen absorption increased by mineral fertilization. Globally, nitrogen fertilization management and planting density were particularly important for the delivery of multiple ecosystem services, but soil and climate effects were far from negligible, especially for nitrogen and water-related services. The ecosystem service profiles of the studied cropping systems were diversified, with contrasted profiles showing high yield and carbon sequestration but low prevention of nitrogen denitrification and of nitrogen leaching, and more balanced profiles. The STICS crop model made it possible to quantify and analyze profiles of ecosystem services and should be helpful in instrumenting the dialogue between fruit growers and other stakeholders by simulating scenarios to optimize multiple services. However, it has to be improved to address the impact of grass cover on soil functions and the long-term functioning of apple orchards.

      PubDate: 2018-02-26T12:46:17Z
      DOI: 10.1016/j.eja.2018.01.009
      Issue No: Vol. 94 (2018)
       
  • Component crop physiology and water use efficiency in response to
           intercropping
    • Authors: Jose G. Franco; Stephen R. King; Astrid Volder
      Pages: 27 - 39
      Abstract: Publication date: February 2018
      Source:European Journal of Agronomy, Volume 93
      Author(s): Jose G. Franco, Stephen R. King, Astrid Volder
      Interspecies specific interactions are generally regarded as drivers of plant productivity in multispecies agroecosystems. Complementary use of resource in diverse communities can enhance community productivity through optimal use of plant-available resources and positive interactions such as facilitation can ameliorate high abiotic stress conditions. We studied the effects on physiological response, leaf traits and water use efficiency of a multifunctional species intercropping system consisting of peanut (Arachis hypogaea L.), watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai], okra [Abelmoschus esculentus (L.) Moench], cowpea [Vigna unguiculata (L.) Walp.], and pepper (Capsicum annuum L.) planted alone or in various intercropping combinations in a low fertilizer input system in the peak of summer heat in Texas. Differences in gas exchange measurements were detected only in watermelon in year 2 of the study when okra was the dominant crop. This same year watermelon specific leaf area (SLA) was significantly higher when okra was present in a treatment and particularly in the three and four species combinations, W pwo and W pwoc, 27.5 and 31.0m2 kg−1, respectively, as compared to watermelon grown in monoculture, strip intercropped with peanut (S pw) and within row intercropped with peanut (W pw), 20.4, 20.1, and 19.8m2 kg−1, respectively. This corresponds with an increase watermelon leaf N concentration and a decrease in leaf C:N ratio in W pwo and W pwoc treatments. No differences in d13C composition, a measure of water use efficiency over the leaf lifespan, were detected across cropping system for each species. Water use efficiency based on per plant production (WUEyield) indicated an increase in water use efficiency in dominant crops such as watermelon in 2011 and okra in 2012, but a reduction in WUEyield subordinate crops such as cowpea and pepper both years of the study. Peanut grown in monoculture and strip intercropped with watermelon had significantly lower leaf water potential values in 2012, −2.2 and −2.1MPa, respectively, as compared to intercropping systems increasing in level of integration (W pw =−1.1, W pwo =−0.6, W pwoc =−1.3, W all =−1.1MPa), indicating peanut benefited from alterations to microclimate and facilitative interactions with companion crops in some intercropping systems through a reduction in plant water stress. The results from this study suggest there may be a benefit to a multifunctional intercropping system in the form of increased food production per unit of water input in dominant crops and reduced water stress for some component species. This is important to producers; showing a method to increase overall crop production without increasing water inputs.

      PubDate: 2018-02-26T12:46:17Z
      DOI: 10.1016/j.eja.2017.11.005
      Issue No: Vol. 93 (2018)
       
  • Azotobacter-enriched organic manures to increase nitrogen fixation and
           crop productivity
    • Authors: M. Ângelo Rodrigues; Laurindo Chambula Ladeira; Margarida Arrobas
      Pages: 88 - 94
      Abstract: Publication date: February 2018
      Source:European Journal of Agronomy, Volume 93
      Author(s): M. Ângelo Rodrigues, Laurindo Chambula Ladeira, Margarida Arrobas
      The use of fertilizers with beneficial microorganisms has increased in recent years. In this study, the performance was assessed of two manures enriched with Azotobacter (BioF1 and BioF2), a non-enriched organic manure (Organ), an inorganic N fertilizer applied at a rate equivalent to the organic manures (MinR1) and applied at twice the rate (MinR2), and a control treatment. A field trial and a pot experiment were carried out both consisting of a sequence of three crops per year [lettuce (Lactuca sativa)-lettuce-turnip (Brassica rapa)] grown for two years. Above ground dry matter (DM) yield and N recovery were higher in the inorganic fertilized plots in comparison to the organic manured plots. Anion exchange membranes inserted into the soil in short periods during the growing seasons revealed higher soil nitrate levels in the inorganic fertilized treatments. Organic amendments improved performance over time, proving that their fertilizing effect, though modest in the short-term, lasts longer. The biofertilizers containing Azotobacter (BioF1, BioF2) increased the bioavailability of N over Organ, by an additional N-fixing value of 11.4 kg ha−1 estimated from the six crops of the field experiment (∼5.7 kg N per year). If compared on the basis of the same amount of N recovered, organic amendments produced an average increase of 720 kg DM ha−1 over the inorganic fertilizer (∼120 kg per crop) due to a general manuring effect. From the results of these experiments, no beneficial effects on crop growth could be attributed to biofertilizers other than the slight increase in N fixation.

      PubDate: 2018-02-05T10:06:11Z
      DOI: 10.1016/j.eja.2018.01.002
      Issue No: Vol. 93 (2018)
       
  • Concepts, approaches, and avenues for modelling crop health and crop
           losses
    • Authors: Serge Savary; Andrew D. Nelson; Annika Djurle; Paul D. Esker; Adam Sparks; Lilian Amorim; Armando Bergamin Filho; Tito Caffi; Nancy Castilla; Karen Garrett; Neil McRoberts; Vittorio Rossi; Jonathan Yuen; Laetitia Willocquet
      Abstract: Publication date: Available online 18 April 2018
      Source:European Journal of Agronomy
      Author(s): Serge Savary, Andrew D. Nelson, Annika Djurle, Paul D. Esker, Adam Sparks, Lilian Amorim, Armando Bergamin Filho, Tito Caffi, Nancy Castilla, Karen Garrett, Neil McRoberts, Vittorio Rossi, Jonathan Yuen, Laetitia Willocquet
      This article addresses the modelling of crop health and its impact on crop losses, with a special emphasis on plant diseases. Plant disease epidemiological models have many different shapes. We propose a summary of modelling structures for plant disease epidemics, which stem from the concepts of infection rate, of site, of basic infection rate corrected for removals (Rc), and of basic reproductive number (R0). Crop losses, the quantitative and qualitative impacts of diseases and pests on crop performances, can be expressed along many different dimensions. We focus on yield loss, defined as the difference between the attainable yield and the actual yield, in a production situation. The modelling of yield loss stems from the concept of damage mechanism, which can be applied to the wide range of organisms (including pathogens, weeds, arthropods, or nematodes) that may negatively affect crop growth and performances. Damage mechanisms are incorporated in crop growth models to simulate yield losses. In both fields, epidemiology and crop loss, we discuss the process of model development, including model simplification. We emphasize model simplification as a main avenue towards model genericity. This is especially relevant to enable addressing the diversity of crop pathogens and pests. We also discuss the usefulness of considering differing evaluation criteria depending on the stage of model development, and thus, depending on modelling objectives. We illustrate progress made on two global key crops where model simplification has been critical; rice and wheat. Modelling pests and diseases, and of the yield losses they cause on these two crops, lead us to propose the concept of crop health syndrome as a set of injury functions, each representing the dynamics of an injury (such as, for example, the time-course of an epidemic). Crop health in a given context can be represented by the set of such injury functions, which in turn can be used as drivers for crop loss models.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.04.003
       
  • Modelling varietal differences in response to phosphorus in West African
           sorghum
    • Authors: M. Adam; K.A. Dzotsi; G. Hoogenboom; P.C.S. Traoré; C.H. Porter; H.F.W. Rattunde; B. Nebie; W.L. Leiser; E. Weltzien; J.W. Jones
      Abstract: Publication date: Available online 11 April 2018
      Source:European Journal of Agronomy
      Author(s): M. Adam, K.A. Dzotsi, G. Hoogenboom, P.C.S. Traoré, C.H. Porter, H.F.W. Rattunde, B. Nebie, W.L. Leiser, E. Weltzien, J.W. Jones
      In West Africa’s highly weathered soils, plant-available soil-P levels determine sorghum performance and yield to a far greater extent than projected variability in climate. Despite local landrace varieties having excellent adaptation to the environment and a relatively stable yield, sorghum grain yield remains quite low, averaging less than 1 t ha−1. Low P availability in West African soils has significant effects on crop development and growth with potential grain yield losses of more than 50%. Use of mechanistic models, which integrate physiological processes, could assist with understanding the differences in P-uptake among varieties and guide effective P management. Yet only few crop models include a soil-plant P model for simulating crop yield response to P management. A generic soil-plant P module was developed for crop models in the Cropping System Model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT) but the module was adapted and tested only on two crops, groundnut and maize. The aim of the study was to adapt the soil-plant P module for sorghum and perform initial testing on highly weathered soils in West Africa. Data used in adapting and testing the soil-plant P model for sorghum consisted of in-season P concentrations and dry weights of stems, leaves and grain from four sorghum varieties covering a range of maturities and photoperiod sensitivities and grown in high-P and P-deficient soils at ICRISAT-Mali. Results showed that the coupled CERES-Sorghum − P module reasonably reproduced the vegetative and grain yield reductions experienced in the field experiments with an average RMSE of 1561 and 909 kg ha−1 under high P conditions and 1168 and 466 kg ha−1 under low P conditions, respectively. The simulations are in most cases within the observation error. We also confirmed that contrasting variety types differ in their P-uptake dynamics relative to above-ground growth change over time, and hence respond differently to available P.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.04.001
       
  • Modeling salinity effect on rice growth and grain yield with ORYZA v3 and
           APSIM-Oryza
    • Authors: A.M. Radanielson; D.S. Gaydon; T. Li; O. Angeles; C.H. Roth
      Abstract: Publication date: Available online 21 March 2018
      Source:European Journal of Agronomy
      Author(s): A.M. Radanielson, D.S. Gaydon, T. Li, O. Angeles, C.H. Roth
      Development and testing of reliable tools for simulating rice production in salt-affected areas are presented in this paper. New functions were implemented in existing crop models ORYZA v3 and the cropping systems modelling framework APSIM. Field experiments covering two years, two different sites, and three varieties were used to validate both improved models. We used the salt balance module in the systems model APSIM to simulate the observed daily soil salinity with acceptable accuracy (RMSEn <35%), whereas ORYZA v3 used measured soil salinity at a given interval of days as a model input. Both models presented similarly good accuracy in simulating aboveground biomass, leaf area index, and grain yield for IR64 over a gradient of salinity conditions. The model index of agreement ranged from 0.86 to 0.99. Variability of yield under stressed and non-stressed conditions was simulated with a RMSE, of 191 kg ha−1 and 222 kg ha−1 , respectively, for ORYZA v3 and APSIM-Oryza, corresponding to an RMSEn of 14.8% and 17.3%. These values are within the bounds of experimental error, therefore indicating acceptable model performance. The model test simulating genotypic variability of rice crop responses resulted in similar levels of acceptable model performance with RMSEn ranging from 11.3 to 39.9% for observed total above ground biomass for IR64 and panicle biomass for IR29, respectively. With the improved models, more reliable tools are now available for use in risk assessment and evaluation of suitable management options for rice production in salt-affected areas. The approach presented may also be applied in improving other non-rice crop models to integrate a response to soil salinity − particularly in process-based models which capture stage-related stress tolerance variability and resource use efficiency.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.01.015
       
  • Bringing genetics and biochemistry to crop modelling, and vice versa
    • Authors: Xinyou Yin; C. Gerard van der Linden; Paul C. Struik
      Abstract: Publication date: Available online 3 March 2018
      Source:European Journal of Agronomy
      Author(s): Xinyou Yin, C. Gerard van der Linden, Paul C. Struik
      Genetics, biochemistry, and crop modelling are independently evolving disciplines; however, they complement each other in addressing some of the important challenges that crop science faces. One of these challenges is to improve our understanding of crop genotype-to-phenotype relationships in order to assist the development of high-yielding and resource-use efficient genotypes that can adapt to particular (future) target environments. Crop models are successful in predicting the impact of environmental changes on crop productivity. However, when critically tested against real experimental data, crop models have been shown to be less successful in predicting the impact of genotypic variation and genotype-by-environment interactions exhibited in genetic populations. In order to better model gene-trait-crop performance relationships in support of breeding and genetic engineering programmes, crop models need to be improved in terms of both model parameters and model structure. We argue that integration of quantitative genetics and photosynthesis biochemistry with modelling is a first step towards a new generation of improved crop models. With genetic information and biochemical understanding incorporated, crop modelling also generates new insights and concepts that can in turn be used to improve genetic analysis and biochemical modelling of complex traits. This modelling-genetics-biochemistry framework (the MGB triangle framework) stresses the synergy among the three disciplines, and may best serve as a step to achieve the ultimate goal of the more broadly framed “Crop Systems Biology” approach to improve efficiency of both classical breeding and genetic engineering programmes.

      PubDate: 2018-04-24T14:50:50Z
      DOI: 10.1016/j.eja.2018.02.005
       
  • Crop model improvement in APSIM: Using wheat as a case study
    • Authors: Hamish Brown; Neil Huth; Dean Holzworth
      Abstract: Publication date: Available online 24 February 2018
      Source:European Journal of Agronomy
      Author(s): Hamish Brown, Neil Huth, Dean Holzworth
      The process of building and improving a broadly useful set of crop models is a major undertaking and the APSIM (Agricultural Production system SIMulator) development community conduct this work separately from projects that have specific uses of the models. This paper presents a set of standards that a modern crop model should meet, and describes the approaches and software the APSIM development community are using to build and maintain models that meet these standards. The latest version of APSIM combines a range of tools in a single user interface (UI) to assist model developers. It uses a modern version control system to ensure model reliability and a modern distribution system to ensure users can easily access models and receive updates. The wheat model is used as an example to describe the development process using the APSIM platform. Firstly, a test set for the model was developed: • Forty-eight experiments, giving 655 treatments, were collated into a database. • Each of these treatments was configured as a test simulation using the Experiment component in the UI to hasten the process and reduce human error. • The model was implemented in the UI using the plant modelling framework for a visual and flexible approach to model construction. • Graphs and statistics for assessing model performance were constructed in the UI. • From the UI, changes were made to the model, and its performance was reviewed each time until developers were happy with it. • Memo fields were added into the UI to describe experiments and capture the rationale and citations for model structure and parameterisation. This system facilitated a number of science improvements to the wheat model, including new canopy and phenology models and the compilation and more thorough analysis of a large test dataset. The test set was submitted to APSIM governance for review and approval for general release. Once approved, the model was included in the APSIM distribution as a read-only file so users cannot change it. The test set was put into version control to provide a baseline for assessing model performance. Documentation was automatically generated from the test set, providing a full and up-to-date technical description of the model and its evaluation. This demonstrates a robust yet flexible and efficient approach for improving and distributing crop models, facilitated by purpose-designed software.

      PubDate: 2018-02-26T12:46:17Z
      DOI: 10.1016/j.eja.2018.02.002
       
  • Refining the Canegro model for improved simulation of climate change
           impacts on sugarcane
    • Authors: Matthew R. Jones; Abraham Singels
      Abstract: Publication date: Available online 14 February 2018
      Source:European Journal of Agronomy
      Author(s): Matthew R. Jones, Abraham Singels
      Crop models can be used for predicting climate change impacts and exploring adaptation strategies, but their suitability for such tasks needs to be assessed. Although the DSSAT-Canegro model has been used widely for climate impact studies, some shortcomings have been revealed. The objectives were to improve and evaluate the capability of DSSAT-Canegro to predict crop responses to climate change. Model changes included improved simulation of elevated temperature and atmospheric CO2 concentration ([CO2]) impacts, and revised algorithms for tillering, respiration and crop water relations. After calibration, the refined model was tested against an independent set of experimental data, demonstrating acceptable simulation accuracy for aerial dry mass, stalk dry mass and stalk sucrose mass (RMSE = 8.4, 5.2 and 3.3 t/ha respectively). A multiple-site sensitivity analysis revealed that simulated responses by the refined model, of canopy formation, crop water use, crop water status and stalk dry mass to changes in rainfall, temperature and [CO2], were more realistic than those of the old model. Highest average simulated stalk mass was achieved at a temperature regime that was 3 °C warmer than current climate, with yield increases ranging from 0.7% (irrigated Ligne Paradis, Reunion Island) to 7% (rainfed Piracicaba, Brazil). Elevated [CO2] increased yields for rainfed production only (7% for La Mercy, South Africa and 6% for Piracicaba, [CO2] = 750 ppm), through reduced transpiration and improved crop water status. The study highlighted the need for improvements in simulating reduced growth of older crops, and [CO2] effects on transpiration. This study has delivered an improved Canegro model that represents plant processes and their interactions with climatic drivers more realistically, and can predict crop growth, water use and yields, for a wide range of climates, reasonably accurately. We propose that this revised Canegro model is included in a forthcoming release of the DSSAT Cropping System Model, for use in climate change impact studies.

      PubDate: 2018-02-26T12:46:17Z
      DOI: 10.1016/j.eja.2017.12.009
       
  • Indices of forage nutritional yield and water use efficiency amongst
           spring-sown annual forage crops in north-west China
    • Authors: Qingping Zhang; Lindsay W. Bell; Yuying Shen; Jeremy P.M. Whish
      Pages: 1 - 10
      Abstract: Publication date: February 2018
      Source:European Journal of Agronomy, Volume 93
      Author(s): Qingping Zhang, Lindsay W. Bell, Yuying Shen, Jeremy P.M. Whish
      Livestock production in China is increasing to meet demands for animal products, but is limited by feed resources. To explore additional forage options in north-west China, the biomass production and nutritive value of nine spring-sown annual crops (maize (Zea mays), sudan grass (Sorghum sudanense), small millet (Setaria italica), millet (Panicum milliaceum), soybean (Glycine max), common vetch (Vicia sativa), pea (Pisum sativum), oat (Avena sativa) and spring wheat (Triticum aestivum)) were compared under rainfed conditions over two years. Water use efficiencies for biomass (WUEDM) and nutritional yield indices, CP yield (WUECP) and relative feed value yield (WUERFV), were calculated. Maize produced the highest biomass yields of >10t DMha−1 and had the highest WUEDM. Biomass production was next highest in the other warm-season grasses such as sudan grass and millet species (6–9t DMha−1) and soybean (3–7t DMha−1), while spring wheat produced the most early biomass in spring (P< 0.05). The legumes had higher crude protein concentration and produced equivalent or higher CP yields and WUECP to the grasses (1.2–1.7kg CP ha−1 mm−1). Maize and soybean had the highest WUERFV of 26.4kgha−1 mm−1 and 19.4kgha−1 mm−1, respectively. These integrated nutritional yield indices enabled comparisons of water productivity and optimal harvest timing across a range of forage types with differing nutritional characteristics and biomass production potential.

      PubDate: 2017-12-12T13:33:38Z
      DOI: 10.1016/j.eja.2017.11.003
      Issue No: Vol. 93 (2017)
       
  • Random effects models, BLUPs and redundancy analyses for grain legume
           crops in semi-arid environments
    • Authors: Giovanni Avola; Ezio Riggi; Fabio Gresta; Orazio Sortino; Andrea Onofri
      Pages: 18 - 26
      Abstract: Publication date: February 2018
      Source:European Journal of Agronomy, Volume 93
      Author(s): Giovanni Avola, Ezio Riggi, Fabio Gresta, Orazio Sortino, Andrea Onofri
      Grain legume crops play a strategic role in cropping systems around the world, but their acceptance in European agriculture is rather low, because of low yield stability. We used a dataset comprising five to eleven genotypes for each of four legume crops (field pea, lentil, faba bean and chickpea) in four dry environments (two locations by two years). We focused on ‘genotype by environment’ interactions, by using several statistical techniques, such as random models, BLUPs and redundancy analysis. The main aim was to show how these techniques and the concomitant use of yield and other phenological/morphological traits as well as environmental data can help understand which species/genotypes are most adapted to dry environments and address the possible reasons for yield instability. Our results confirmed large environmental effects on the expression of phenology and productive traits, even though a shorter duration of the vegetative phase was associated to higher yields in most species and genotypes. The use of BLUPs gave information on the most suitable genotypes for each of the studied species, targeting the traits and environmental variables which are mostly related to yield level and stability. Baccara in field pea, Pantelleria in lentil, Gemini in faba bean and PA34 in chickpea showed high correlation between yield and precocity of the flowering stage. BLUPs for genotype means across environments emphasize that the reported genotypes where characterized by a low value of stability variance that implies the ability to keep an additive relationship between genotypic and environmental effects. This could represent a strategic issue for genotype selection.

      PubDate: 2017-12-12T13:33:38Z
      DOI: 10.1016/j.eja.2017.11.004
      Issue No: Vol. 93 (2017)
       
  • Agronomic and environmental causes of yield and nitrogen use efficiency
           gaps in Chinese rice farming systems
    • Authors: Ning An; Wenliang Wei; Lei Qiao; Fusuo Zhang; Peter Christie; Rongfeng Jiang; Achim Dobermann; Keith W.T. Goulding; Jinglong Fan; Mingsheng Fan
      Pages: 40 - 49
      Abstract: Publication date: February 2018
      Source:European Journal of Agronomy, Volume 93
      Author(s): Ning An, Wenliang Wei, Lei Qiao, Fusuo Zhang, Peter Christie, Rongfeng Jiang, Achim Dobermann, Keith W.T. Goulding, Jinglong Fan, Mingsheng Fan
      Yield (YG) and nitrogen use efficiency (NUE) gap analysis is a key tool in addressing the sustainable intensification of agricultural systems. Distinguishing and quantifying the underlying agronomic and environmental causes of these gaps is as important as estimating their magnitude. We applied a field experimental framework that allowed us to partition YGs and NUE gaps due to crop management, climatic factors and/or inherent soil productivity. YG and NUE gaps were determined as the differences between yields and NUE under standard farm practices and the attainable yield and NUE using optimum management practices. In farmer’s fields in China, the rice YG and NUE gap (expressed as the partial factor productivity of applied N, namely kg rice grain per kg fertilizer N applied, PFPN) averaged 1900kgha−1 and 18kgkg−1 , respectively. However, both were subject to large variability within and across different rice farming systems in response to key agronomic and environmental variables, with larger gaps in moderate- and low-yielding fields and in single rice systems. Management practices such as optimizing N and water management and increasing rice transplanting density simultaneously narrowed the YG by 38% and the NUE gap by 39% on average. Climatic- (YG-C) and inherent soil productivity-based YGs (YG-S), which represented fractions of YG derived from climate and soil variability, accounted for on average 16% and 38% of the total YG across low- and moderate-yielding fields in single rice systems, and by 14% and 27% in early and 11% and 20% in late rice farming systems, respectively. Growing-degree days (GDD) for early rice and daily minimum temperature (TMIN) for late rice were the best predictors of YG-C. For single rice in the Yangtze Delta, YG-C included multiple factors such as lower daily mean temperature and GDD, and higher daily maximum temperatures and precipitation during rice growing periods. Soil nutrient supplying capacity was partially responsible for YG-S in those under-performing fields. Significant and exploitable potential exists for increasing rice productivity with higher NUE, especially in moderate- and low-yielding fields. However, national and regional agricultural policies should place more emphasis on supporting good agronomy and soil management, thus moving towards a soil-climate smart management approach in rice farming systems.
      Graphical abstract image

      PubDate: 2017-12-12T13:33:38Z
      DOI: 10.1016/j.eja.2017.11.001
      Issue No: Vol. 93 (2017)
       
  • Identification of light availability in different sweet cherry orchards
           under cover by using non-destructive measurements with a Dualex™
    • Authors: Verena Overbeck; Michaela Schmitz; Iryna Tartachnyk; Michael Blanke
      Pages: 50 - 56
      Abstract: Publication date: February 2018
      Source:European Journal of Agronomy, Volume 93
      Author(s): Verena Overbeck, Michaela Schmitz, Iryna Tartachnyk, Michael Blanke
      Changing climatic conditions makes the development of cultivation strategies for protected cherry cultivation necessary. The objective of the present study was to investigate physiological processes in connection with light availability in different planting systems under cover using a Dualex™ for non-destructive measurements. Hence, cherry trees were either trained as hedgerows, i.e. the most dense planting ([2.35m*2]*1.5m), or trained as spindles (2.70m*2.0m; 1.75m*2.9m) and grown under cover or in the open field at Klein-Altendorf near Bonn, Germany. There was no difference in leaf area between the plantings. Non-invasive measurements with the Dualex™ (Force A, France) showed that a larger relative leaf chlorophyll content (Chl=30–33) in the hedgerow trees under crop cover as a result of less light than in the open field-grown leaves with less chlorophyll (ChI=26–28). Similarly, the flavonoid index (Flav), as a relative measure of the epidermal flavonoids and light condition, was generally lower under crop cover and lowest in the hedgerow trees on the adaxial leaf side with Flav=1.4–1.5 relative to 1.6–1.8 in the open field, but always maintained these high values above the critical light level of 1–1.2. Non-invasive SunScan measurements showed light reductions of up to 80% inside the canopy of the dense hedgerow trees under cover in line with the lowest values for Flav and ChI. Although the largest yield per tree was obtained in the planting system with the best light conditions (1.75m*2.9m), the largest yield per acreage was found in the most dense planting (2.7m*2.0m) with hedgerows under cover as an ideal combination of a high yield and fruit quality with good light availability. Overall, our results showed that light availability depends on crown structure, planting system and tree density. The indices Flav and ChI offer the possibility to evaluate the light conditions in an orchard easily and to give a recommendation for an optimized growing system.

      PubDate: 2017-12-12T13:33:38Z
      DOI: 10.1016/j.eja.2017.11.006
      Issue No: Vol. 93 (2017)
       
  • Uncertainty-based auto-calibration for crop yield – the EPIC+ procedure
           for a case study in Sub-Saharan Africa
    • Authors: Bahareh Kamali; Karim C. Abbaspour; Anthony Lehmann; Bernhard Wehrli; Hong Yang
      Pages: 57 - 72
      Abstract: Publication date: February 2018
      Source:European Journal of Agronomy, Volume 93
      Author(s): Bahareh Kamali, Karim C. Abbaspour, Anthony Lehmann, Bernhard Wehrli, Hong Yang
      Process-based crop models are increasingly used to assess the effects of different agricultural management practices on crop yield. However, calibration of historic crop yield is a challenging and time-consuming task due to data limitation and lack of adaptive auto-calibration tools compatible with the model to be calibrated on different spatial and temporal scales. In this study we linked the general auto-calibration procedure SUFI-2 (Sequential Uncertainty Fitting Procedure) to the crop model EPIC (Environmental Policy Integrated Climate) to calibrate maize yield in Sub-Saharan African (SSA) countries. This resulted in the creation of a user-friendly software, EPIC+, for crop model calibration at spatial levels of grid to continent. EPIC+ greatly speeds up the calibration process with quantification of parameter ranges and prediction uncertainty. In the SSA application, we calibrated three sets of parameters referred to as Planting Date (PD), Operation (e.g., fertilizer application, planting density), and Model parameters (e.g., Harvest index, biomass-energy ratio, water stress harvest index, SCS curve number) in three steps to avoid parameter interaction and identifiability problems. In the first step, by adjusting PD parameters, the simulated yield results improved in Western and Central African countries. In the next step, Operation parameters were calibrated for individual countries resulting in a better model performance by more than 40% in many countries. In the third step, Model parameters were calibrated with significant improvements in all countries by an average of 50%. We also found that countries with less socio-political volatility benefited most from the calibration. For countries where agricultural production had trends, we suggest improving the calibration results by applying linear de-trending transformations, which we will explore in more detail in a subsequent study.

      PubDate: 2017-12-12T13:33:38Z
      DOI: 10.1016/j.eja.2017.10.012
      Issue No: Vol. 93 (2017)
       
  • Analysis and modeling of cover crop emergence: Accuracy of a static model
           and the dynamic STICS soil-crop model
    • Authors: Hélène Tribouillois; Julie Constantin; Eric Justes
      Pages: 73 - 81
      Abstract: Publication date: February 2018
      Source:European Journal of Agronomy, Volume 93
      Author(s): Hélène Tribouillois, Julie Constantin, Eric Justes
      Cover crops are increasingly used in agriculture to provide a variety of ecosystem services (e.g. reducing nitrogen leaching, storing carbon in soils) during fallow periods, but it can be challenging to successfully establish them in summer, when water availability may be low. Thus, it is crucial to better quantify, understand and predict the emergence date of a variety of cover crops from multiple contexts in impact assessment studies. The objectives of this study were to 1) analyze variability in emergence dynamics among cover crops grown in fields, 2) identify variables that influence emergence the most and use them to develop a simple model to predict emergence date and 3) calibrate the STICS model to improve its predictions of cover crop emergence. STICS was chosen because it is a dynamic soil-plant model widely validated in the literature for simulating the production of cover crop services. We analyzed emergence dynamics of ten cover crop species sown under a variety of soil, climate and sowing conditions from 18 experimental sites across France. We developed and independently evaluated a static model based on these data to predict the number of days until emergence. We then calibrated STICS using the same data. Results revealed a mean emergence duration of 12 days for all species, but with high variability among experimental sites and years. The simple static model contained only three variables, with the number of consecutive days without significant water input after sowing the most significant. Overall, both the model and STICS predicted emergence date well in the calibration and validation datasets. Accurate prediction of soil moisture in the seedbed and soil water balance is a key factor to accurately predict cover crop emergence. Accurately predicting emergence of cover crops in crop models will help to assess the former’s ability to provide ecosystem services in cropping systems in current and future climates.

      PubDate: 2017-12-27T07:10:13Z
      DOI: 10.1016/j.eja.2017.12.004
      Issue No: Vol. 93 (2017)
       
 
 
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