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  Subjects -> AGRICULTURE (Total: 792 journals)
    - AGRICULTURAL ECONOMICS (69 journals)
    - AGRICULTURE (559 journals)
    - CROP PRODUCTION AND SOIL (92 journals)
    - DAIRYING AND DAIRY PRODUCTS (27 journals)
    - POULTRY AND LIVESTOCK (45 journals)

AGRICULTURE (559 journals)

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Journal Cover European Journal of Agronomy
  [SJR: 1.488]   [H-I: 75]   [11 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1161-0301
   Published by Elsevier Homepage  [3089 journals]
  • Indices of forage nutritional yield and water use efficiency amongst
           spring-sown annual forage crops in north-west China
    • 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
       
  • Random effects models, BLUPs and redundancy analyses for grain legume
           crops in semi-arid environments
    • 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
       
  • Agronomic and environmental causes of yield and nitrogen use efficiency
           gaps in Chinese rice farming systems
    • 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
       
  • Identification of light availability in different sweet cherry orchards
           under cover by using non-destructive measurements with a Dualex™
    • 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
       
  • Uncertainty-based auto-calibration for crop yield – the EPIC+ procedure
           for a case study in Sub-Saharan Africa
    • 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
       
  • Inside Front Cover - Editorial Board Page
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92


      PubDate: 2017-12-12T13:33:38Z
       
  • Climate change impact on global potato production
    • Abstract: Publication date: Available online 1 December 2017
      Source:European Journal of Agronomy
      Author(s): Rubí Raymundo, Senthold Asseng, Richard Robertson, Athanasios Petsakos, Gerrit Hoogenboom, Roberto Quiroz, Guy Hareau, Joost Wolf
      Potato is the most important non-grain crop in the world. Therefore, understanding the potential impacts of climate change on potato production is critical for future global food security. The SUBSTOR-Potato model was recently evaluated across a wide range of growing conditions, and improvements were made to better simulate atmospheric CO2 and high temperature responses. Comparisons of the improved model with field experiments, including elevated atmospheric CO2 concentrations and high temperature environments, showed a RRMSE of 26% for tuber dry matter. When using the improved model across 0.5×0.5° grid cells over all potato-growing regions in the world, the simulated aggregated country tuber dry yields reproduced nationally-reported potato yields with a RRMSE of 56%. Applying future climate change scenarios to current potato cropping systems indicated small global tuber yield reductions by 2055 (−2% to −6%), but larger declines by 2085 (−2% to −26%), depending on the Representative Concentration Pathway (RCP). The largest negative impacts on global tuber yields were projected for RCP 8.5 toward the end of the century. The simulated impacts varied depending on the region, with high tuber reductions in the high latitudes (e.g., Eastern Europe and northern America) and the lowlands of Africa, but less so in the mid-latitudes and tropical highland. Uncertainty due to different climate models was similar to seasonal variability by mid-century, but became larger than year-to-year variability by the end of the century for RCP 8.5.

      PubDate: 2017-12-12T13:33:38Z
       
  • How can forage production in Nordic and Mediterranean Europe adapt to the
           challenges and opportunities arising from climate change'
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Å. Ergon, G. Seddaiu, P. Korhonen, P. Virkajärvi, G. Bellocchi, M. Jørgensen, L. Østrem, D. Reheul, F. Volaire
      Climate change and its effects on grassland productivity vary across Europe. The Mediterranean and Nordic regions represent the opposite ends of a gradient of changes in temperature and precipitation patterns, with increasingly warmer and wetter winters in the north and increasingly warmer and drier summers in the south. Warming and elevated concentration of atmospheric CO2 may boost forage production in the Nordic region. Production in many Mediterranean areas is likely to become even more challenged by drought in the future, but elevated CO2 can to some extent alleviate drought limitation on photosynthesis and growth. In both regions, climate change will affect forage quality and lead to modifications of the annual productivity cycles, with an extended growing season in the Nordic region and a shift towards winter in the Mediterranean region. This will require adaptations in defoliation and fertilization strategies. The identity of species and mixtures with optimal performance is likely to shift somewhat in response to altered climate and management systems. It is argued that breeding of grassland species should aim to (i) improve plant strategies to cope with relevant abiotic stresses and (ii) optimize growth and phenology to new seasonal variation, and that plant diversity at all levels is a good adaptation strategy.

      PubDate: 2017-11-09T15:07:58Z
       
  • A review of data assimilation of remote sensing and crop models
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Xiuliang Jin, Lalit Kumar, Zhenhai Li, Haikuan Feng, Xingang Xu, Guijun Yang, Jihua Wang
      Timely and accurate estimation of crop yield before harvest to allow crop yields management decision-making at a regional scale is crucial for national food policy and security assessments. Modeling dynamic change of crop growth is of great help because it allows researchers to determine crop management strategies for maximizing crop yield. Remote sensing is often used to provide information about important canopy state variables for crop models of large regions. Crop models and remote sensing techniques have been combined and applied in crop yield estimation on a regional scale or worldwide based on the simultaneous development of crop models and remote sensing. Many studies have proposed models for estimating canopy state variables and soil properties based on remote sensing data and assimilating these estimated canopy state variables into crop models. This paper, firstly, summarizes recent developments of crop models, remote sensing technology, and data assimilation methods. Secondly, it compares the advantages and disadvantages of different data assimilation methods (calibration method, forcing method, and updating method) for assimilating remote sensing data into crop models and analyzes the impacts of different error sources on the different parts of the data assimilation chain in detail. Finally, it provides some methods that can be used to reduce the different errors of data assimilation and presents further opportunities and development direction of data assimilation for future studies. This paper presents a detailed overview of the comparative introduction, latest developments and applications of crop models, remote sensing techniques, and data assimilation methods in the growth status monitoring and yield estimation of crops. In particular, it discusses the impacts of different error sources on the different portions of the data assimilation chain in detail and analyzes how to reduce the different errors of data assimilation chain. The literature shows that many new satellite sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. Additionally, new proposed or modified crop models have been reported for improving the simulated canopy state variables and soil properties of crop models. In short, the data assimilation of remote sensing and crop models have the potential to improve the estimation accuracy of canopy state variables, soil properties and yield based on these new technologies and methods in the future.

      PubDate: 2017-11-09T15:07:58Z
       
  • Radiation use efficiency and biomass partitioning to storage roots in
           fodder beet crops
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): E. Chakwizira, E. Teixeira, E. Meenken, A.J. Michel, S. Maley
      Intercepted photosynthetic active radiation (IPAR), radiation use efficiency (RUE) and partitioning of dry matter (DM) to storage roots (proot, %) were quantified for fodder beet crops subjected to contrasting water (irrigated or rain-fed) and nitrogen (N; 0, 25, 50, 100 and 200kg/ha) supply conditions in Canterbury, New Zealand. The objectives were to enhance the understanding of physiological processes controlling fodder beet response to abiotic stresses and also to estimate parameters for biophysical models that simulate crop growth. Data from three field experiments showed a wide range of fodder beet yield (14–29t DM/ha) in response to water and N stress. These yield differences were mostly explained by the treatments effect on IPAR (650–1050MJ PAR/ha), with relatively smaller responses in RUE and proot. For unconstrained (fully irrigated; ≥100kgN/ha) growth conditions, maximum values were 3.6g DM/MJ PAR for RUE and 78% for proot for total biomass at final harvest. The RUE for the rain-fed, 0kgN/ha crops was reduced by up to 25%, while proot was only marginally reduced (∼3% in rain-fed crops) compared with crops under unconstrained growth conditions. While the RUE responded linearly to additional N supply in irrigated crops, rain-fed crops showed a more consistent decline in RUE across N fertiliser rates with 65–70% of unstressed values. High RUE values were observed across a wide range of crop N status (Nitrogen Nutrition Index [NNI] from 0.8 to 1.6) in irrigated crops. In contrast, RUE in rain-fed was low at high NNI estimates because of high N concentration in a smaller canopy area. The lower RUE in rain-fed crops was aligned with reduced leaf photosynthetic rates (Pnleaf) although there was a high variability in Pnleaf measurements. These results give a first quantification of IPAR, RUE, proot and Pnleaf in fodder beet. They provide insights on the relative sensitivity of fodder beet to water and N stresses. These results are valuable for the interpretation of crop responses and for setting parameters for biophysical models to simulate fodder beet growth.

      PubDate: 2017-11-09T15:07:58Z
       
  • Modelling forage yield and water productivity of continuous crop sequences
           in the Argentinian Pampas
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): J.J. Ojeda, K.G. Pembleton, O.P. Caviglia, M.R. Islam, M.G. Agnusdei, S.C. Garcia
      In recent years, the use of forage crop sequences (FCS) has been increased as a main component into the animal rations of the Argentinian pasture-based livestock systems. However, it is unclear how year-by-year rainfall variability and interactions with soil properties affect FCS dry matter (DM) yield in these environments. Biophysical crop models, such as Agricultural Production Systems Simulator (APSIM), are tools that enable the evaluation of crop yield variability across a wide of environments. The objective of this study was to evaluate the APSIM ability to predict forage DM yield and water productivity (WP) of multiple continuous FCS. Thirteen continuous FCS, including winter and summer crops, were simulated by APSIM during two/three growing seasons in five locations across the Argentinian Pampas. Our modelling approach was based on the simulation of multiple continuous FCS, in which crop DM yields depend on the performance of the previous crop in the same sequence and the final soil variables of the previous crop are the initial conditions for the next crop. Overall, APSIM was able to accurately simulate FCS DM yield (0.93 and 3.2Mgha−1 for concordance correlation coefficient [CCC] and root mean square error [RMSE] respectively). On the other hand, the model predictions were better for annual (CCC=0.94; RMSE=0.4gm−2 mm−1) than for seasonal WP (CCC=0.71; RMSE=1.9gm−2 mm−1), i.e. at the crop level. The model performance to predict WP was associated with better estimations of the soil water dynamics over the long-term, i.e. at the FCS level, rather than the short-term, i.e. at the crop level. The ability of APSIM to predict WP decreased as seasonal WP values increased, i.e. for low water inputs. For seasonal water inputs, <200mm, the model tended to under-predict WP, which was directly associated with crop DM yield under-predictions for frequently harvested crops. Even though APSIM showed some weaknesses in predicting seasonal DM yield and WP, i.e. at the crop level, it appears as a potential tool for further research on complementary forage crops based on multiple continuous FCS in the Argentinian livestock systems.

      PubDate: 2017-11-09T15:07:58Z
       
  • Analysis of coffee (Coffea arabica L.) performance in relation to
           radiation level and rate of nitrogen supply II. Uptake and distribution of
           nitrogen, leaf photosynthesis and first bean yields
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Adugna Debela Bote, Zewdneh Zana, Fikre L. Ocho, Jan Vos
      Natural supply of nitrogen is often limiting coffee production. From the viewpoints of growth and biomass production, adequate nitrogen supply is important. Growing coffee under full sunlight not only enhances potential yields but also increases demands for nitrogen fertilizer, the extent of which is ill quantified. This paper provides a comprehensive analysis of N uptake and distribution, biomass production, photosynthetic characteristics of 2.5 years old trees and first bean yields of 3.5 years old coffee trees in response to four radiation treatments (30%–100% of full sun), factorially combined with four rates of nitrogen supply (0–88g tree−1 y−1). The experiment was arranged in a randomized split-split plot design and was conducted at Jimma University horticultural farm, Ethiopia, using three coffee varieties. With larger N application and higher level of radiation, more N was utilized and more biomass and yield were produced. The fertilizer-N recovery ranged from 7 to 17% and declined with larger N supply and increased with radiation level. Coffee trees provided with larger amount of N had higher amounts of N per unit leaf area, light-saturated rate of leaf photosynthesis and first bean yield compared to trees grown in low N supply and limited radiation. The relation between biomass and plant N content was conservative across coffee varieties and can be used to estimate N content from biomass or calculate required uptake to produce a given amount of biomass. Though testing of the relation for other climatic conditions is advisable, this relation can also be used in the development of process-based quantitative coffee tree growth models,. Achieving synchronies between N supply and coffee trees demand without excess or deficiency requires further investigation of options to improve the low nitrogen recovery.

      PubDate: 2017-11-09T15:07:58Z
       
  • Analysis of coffee (Coffea arabica L.) performance in relation to
           radiation levels and rates of nitrogen supply I. Vegetative growth,
           production and distribution of biomass and radiation use efficiency
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Adugna Debela Bote, Biruk Ayalew, Fikre L. Ocho, Niels P.R. Anten, Jan Vos
      Intensively managed full-sun coffee (Coffea arabica L.), is potentially highly productive, but has shown disappointingly low yield performance, as adequate resource supplies (especially plant nutrition) are needed to sustain the productivity. In order to underpin rational radiation and nutrient management, the current study focussed on growth and development of 2.5 years old trees in relation to nitrogen supply in combination with several degrees of radiation. Three coffee varieties were grown under four levels of radiation (30–100% full sun) and four rates of nitrogen supply (0–88gtree−1 y−1), arranged in a randomized split-split plot design at Jimma University horticultural farm, Ethiopia, and their biomass increment (growth) and allocation, and crown characteristics were measured. Growth responded positively to both radiation and nitrogen supply, with positive interactions for several plant attributes (including number and length of branches, numbers of pairs of leaves per branch, radiation use efficiency). Plant height and area per leaflet declined with higher radiation level, while the positive effect of larger N supply on these attributes declined with increase in radiation. Branch length and leaf dry weight showed the most positive plasticity in response to higher radiation. Specific leaf area declined from 187 in shade (reducing sunlight to 30%) to 109cm2 g−1 in full sun without effect of N. Positive effects of nitrogen on growth and biomass production were mediated through higher radiation-use efficiency, RUE, ranging from 0.23 to 0.46gMJ−1 (PAR). Variables associated with dry matter partitioning were modestly responsive to either N or radiation. All these responses were consistent across the three varieties. The study enhanced the understanding of vegetative growth and biomass production of coffee trees and explored traits that underlie these patterns. The study also yielded essential information for managing shade and nitrogen supply in both open sun and agroforestry systems and yielded basic information for developing coffee growth models,

      PubDate: 2017-11-09T15:07:58Z
       
  • Energy and economic efficiency in grazing dairy systems under alternative
           intensification strategies
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Eduardo Llanos, Laura Astigarraga, Valentín Picasso
      The intensification of dairy systems, or the process of increasing milk productivity per unit of land area, can be achieved through various strategies. However, it is debated whether intensification is associated with increased economic and/or environmental efficiency. The aim of this study was to identify alternative intensification strategies for grazing dairy systems and evaluate their economic and energy efficiency. A model for calculating energy inputs and outputs was applied to 30 dairy farms with reliable production and economic records in Uruguay, spanning a wide range of farm features. Milk productivity averaged 3819l.ha−1 year−1 (ranging from 1512 to 6942), intake of concentrate averaged 0.25kgl−1 of milk (ranging from 0.03 to 0.38), fossil energy use averaged 3.96MJkg−1 (ranging from 1.9 to 9.1) and farm net income averaged 317 U$D ha−1 year−1 (ranging from 136 to 748). Using a numerical classification procedure, four farm clusters that represent different technological, production, and efficiency situations for grazing dairy farms were identified, associated with the differential use of pastures and concentrates. Although increasing used of concentrates in diets was associated with higher milk productivity, and sometimes higher economic performance, it was consistently negatively associated with energy efficiency. Dairy farms with a higher proportion of pasture consumption achieved higher efficiency of utilization of feed concentrates (higherkg milk/kg concentrate) and thus used less fossil energy per liter of milk. These results suggest that sustainable intensification of grazing dairy systems should rely on efficient utilization of pastures rather than just increasing concentrate intake.
      Graphical abstract image

      PubDate: 2017-11-09T15:07:58Z
       
  • Modeling sensitivity of grain yield to elevated temperature in the DSSAT
           crop models for peanut, soybean, dry bean, chickpea, sorghum, and millet
    • Abstract: Publication date: Available online 2 November 2017
      Source:European Journal of Agronomy
      Author(s): K.J. Boote, Vara Prasad, L.H. Allen, P. Singh, J.W. Jones
      Crop models are increasingly being used as tools to simulate climate change effects or effects of virtual heat-tolerant cultivars; therefore it is important that upper temperature thresholds for seed-set, seed growth, phenology, and other processes affecting yield be developed and parameterized from elevated temperature experiments whether field or controlled-environment chambers. In this paper, we describe the status of crop models for dry bean (Phaseolus vulgaris L.), peanut (Arachis hypogaea L.), soybean (Glycine max L.), chickpea (Cicer arietinum L.), sorghum (Sorghum bicolor (L.) Moench), and millet (Pennisetum glaucum L. (R.) Br) in the Decision Support System for Agrotechnology Transfer (DSSAT) for response to elevated temperature by comparison to observed data, and we review where changes have been made or where needed changes remain. Temperature functions for phenology and photosynthesis of the CROPGRO-Dry Bean model were modified in 2006 for DSSAT V4.5, based on observed growth and yield of Montcalm cultivar grown in sunlit, controlled-environment chambers. Temperature functions for soybean and peanut models were evaluated against growth and yield data in the same chambers and found to adequately predict growth and yield, thus have not been modified since 1998 release of V3.5. The temperature functions for the chickpea model were substantially modified for many processes, and are updated for V4.6. The millet model was re-coded and modified for its temperature sensitivities, with a new function to allow the 8–10day period prior to anthesis to affect grain set, as parameterized from field observations. For the sorghum model, the temperature effect on grain growth rate was modified to improve yield and grain size response to elevated temperature by comparison to data in controlled-environment chambers. For reliable assessments of climate change impact, it is critically important to gather additional temperature response data and to update parameterization and code of all crop models including DSSAT.

      PubDate: 2017-11-09T15:07:58Z
       
  • Inside Front Cover - Editorial Board Page
    • Abstract: Publication date: November 2017
      Source:European Journal of Agronomy, Volume 91


      PubDate: 2017-11-02T23:58:57Z
       
  • Predicting water and nitrogen requirements for maize under semi-arid
           conditions using the CSM-CERES-Maize model
    • Abstract: Publication date: Available online 27 October 2017
      Source:European Journal of Agronomy
      Author(s): Hafiz Mohkum Hammad, Farhat Abbas, Ashfaq Ahmad, Wajid Farhad, Jakarat Anothai, Gerrit Hoogenboom
      Crop models can be useful tools for optimizing irrigation water and fertilizer management to improve crop productivity. The goal of this study was to assess the performance of the Cropping System Model (CSM)-CERES-Maize for its capability to simulate soil moisture content in relation to plant growth, development and grain yield and to determine optimum irrigation and fertilizer inputs under semiarid conditions. The model simulations were compared with the observed results from field trials that were conducted during 2009 and 2010 with a combination of three irrigation regimes (full irrigation, water deficit at vegetative and at reproductive stage) and five nitrogen (N) rates using a split plot design for a total of 15 treatments. To determine the most appropriate combination of nitrogen fertilizer and irrigation, a combination of three irrigation regimes and five N rates ranging from 100 to 300kgNha−1 for a total of 15 scenarios were simulated for 35 years of historical daily weather data. The model was calibrated with an optimum treatment from the 2010 experiment, while the remainder of the data were used for model evaluation. The results showed that the model successfully predicted (R2 =0.98) soil moisture content throughout the growing season. The observed (calibrated) mean percentage differences (MPD) for the numbers of grains per ear, leaf area index (LAI) and total dry matter (TDM) were 5.98, 11.4, and 4.85%, respectively. The MPD was zero for yield, anthesis and maturity days. The normalized root mean square error (nRMSE) for grain yield was 10.4% and 11.4% in 2009 and 2010, respectively. Based on the economic analysis, the management scenario with an N fertilizer application rate of 300kgNha−1 in three splits and total irrigation of 525mm was dominant with the highest mean grain yield (7973kgha−1) and a gross margin of US $ 548ha−1. The outcomes of this study can be used for determining the optimum water and N requirements for maize production under semi-arid conditions. The modeled genetic coefficients might be helpful for plant breeders to develop maize cultivars for semi-arid regions that may give the optimum yield under above recommended N and water management practices.

      PubDate: 2017-11-02T23:58:57Z
       
  • Sowing date and maize grain quality for dry milling
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Lucas J. Abdala, Brenda L. Gambin, Lucas Borrás
      Argentina is the single exporter of non-gmo hard endosperm maize to the European Union, and is internationally known for its grain hardness. This special hard endosperm maize supply chain follows strict regulations to ensure a high quality grain. Specific values for test weight, flotation index, grain vitreousness, and screen retention are demanded by the dry milling industry. Central temperate Argentinean production system is currently changing to later sowings, and there is limited information on the effect of contrasting sowing dates over specific grain quality attributes of interest for the industry. In this study we explored the effects of delaying maize sowing dates from September-October to December on maize dry milling grain quality in the central temperate area. Eighteen commercial genotypes differing in grain hardness were sown during two growing seasons and two sowing dates. Measured traits were grain yield, individual grain weight, dry milling quality (test weight, floaters, vitreousness, 8mm screen retention), and composition (oil, protein, starch). Grain yield varied significantly among genotypes (p<0.001), and semi-dents showed higher yields when compared to hard endosperm flints (13110 and 11463kgha−1, respectively). Early and late sown maize yielded 12737kgha−1 and 11003kgha−1, respectively. Significant genotype differences were observed for all grain quality and composition attributes. Delaying the sowing date from September-October to December had minimum effects on physical grain quality traits, only evident at some genotypes (significant sowing date x genotype interaction for most traits). Genotype to genotype differences in grain quality and composition were larger than variations between sowing dates. Grain hardness was strongly determined by the genotype, making genotype selection a critical management option for attaining high quality at any sowing date. It is evident that high dry milling quality can be obtained with adequate genotypes also at later sowings.

      PubDate: 2017-10-14T08:56:20Z
       
  • Yield differences get large with ascendant altitude between traditional
           paddy and water-saving ground cover rice production system
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Lin Guo, Meiju Liu, Yanan Zhang, Yueyue Tao, Fan Zhang, Guoyuan Li, Klaus Dittert, Shan Lin
      In mountainous regions with high altitude, rice yield is mostly limited by low temperatures and insufficient irrigation facilities. The innovative ground cover rice production system (GCRPS) has a recognised potential to significantly increase rice grain yield where rice production is limited by water scarcity and low temperatures. We hypothesised that yield advantage of GCRPS over traditional Paddy might become larger at higher altitudes. We sampled 14 pairs of adjacent GCRPS and Paddy fields at altitudes of 900m and 23 pairs at 500m altitude with 3 replicates in central China. The study revealed that Badano et al. (2005) grain and straw yield were 40% and 35% greater in GCRPS compared to Paddy at 900m, while the difference was only 10% and 15% at 500m Bennie et al. (2006). Compared to Paddy, increase in productive tiller numbers, spikelets per square metre and percentage of filled grains were significantly larger in GCRPS at high than at low altitude Bennie et al. (2008). Soil temperature differences between GCRPS and Paddy were significantly higher at 900m than at 500m during the first month after transplanting. Our findings demonstrate that GCRPS has a good potential to increase rice yield in mountain regions with high altitudes where rice production is limited by low temperature and seasonal water shortage.
      Graphical abstract image

      PubDate: 2017-10-14T08:56:20Z
       
  • Trade-off between grain weight and grain number in wheat depends on GxE
           interaction: A case study of an elite CIMMYT panel (CIMCOG)
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Alejandro Quintero, Gemma Molero, Matthew P. Reynolds, Daniel F. Calderini
      Identifying the functionally linked mechanisms of grain yield (GY) and its components —i.e. grain number (GN) and grain weight (GW) is necessary for boosting GY potential of wheat. The objectives of the current study were to: (i) analyze the trade-off between GW and GN in 27 elite wheat genotypes grown in two contrasting locations with different yield potential, (ii) assess its causes, and (iii) gain a better understanding of the physiology behind the trade-off between GW and GN. A set of 27 elite wheat genotypes was evaluated during three years in Ciudad Obregón, Mexico (CO), and two years in Valdivia, Chile (Val). GY was higher in Val than CO (783gm−2 and 665gm−2, respectively) and positively associated with above-ground biomass (BM) in both locations. In CO, 15,850 grains m−2 were recorded and 15,197 grains m−2 in Val, while thousand-grain weight (TGW) was higher (P<0.001) in Val than in CO by 23% (52.2 and 42.5g, respectively). Also, individual grain weight (IGW) of most categories was higher in Val than in CO. Remarkably, the relationships between GY and GN showed contrasting responses between locations despite the similar GN. A very low GY/GN relationship was found in CO, while a positive and linear relationship was plotted in Val. The virtual lack of association found in CO (11%) was due to a clear trade-off between TGW and GN, while the positive association in Val was the result of a very low trade-off between the two main yield components. Interestingly, the IGW of grains set in the G2 and G4 positions showed negative association with GN in CO across years as well as during each year, while in Val no association was found across years, though a very low association was found in each year. The source-sink treatments applied ten days after anthesis by halving the spikes showed that, G2 and G4 responded to the increased source by 7.7% and 16%, respectively in CO, while in Val the responses were 15% and 5.1% in Valy13 and 6.5% and 9.6% in Valy14, respectively. In conclusion, the lack of association between GY and GN found in CO was due to the trade-off between the two main yield components (GW and GN), which was mainly explained by higher average temperature and lower photothermal quotient during grain filling recorded in this location than in Val. These results highlight the need to employ different strategies aimed at increasing yield potential depending on the environment. The increase of grain number could be proposed for environments with favorable growing conditions as in Val. On the contrary, increasing GW would be the objective in environments with little chance of taking advantage of increased GN such as CO.

      PubDate: 2017-10-14T08:56:20Z
       
  • Identifying crop rotation practice by the typification of crop sequence
           patterns for arable farming systems – A case study from Central Europe
    • Abstract: Publication date: January 2018
      Source:European Journal of Agronomy, Volume 92
      Author(s): Susanne Stein, Horst-Henning Steinmann
      During the last decades crop rotation practice in conventional farming systems was subjected to fundamental changes. This process was forced by agronomical innovations, market preferences and specialist food processing chains and resulted in the dominance of a few cash crops and short-term management plans. Classical crop rotation patterns became uncommon while short rotations and flexible sequence cropping characterize the standard crop rotation practice. The great variety and flexibility in cropping management as a reaction to economic demands and climatic challenges complicate the systematization of crop rotation practice and make historical systematization approaches less suitable. We present a generic typology approach for the analysis of crop rotation practice in a defined region based on administrative time series data. The typology forgoes the detection of fixed defined crop rotations but has its focus on crop sequence properties and a consideration of the main characteristics of crop rotation practice: i) the transition frequency of different crops and ii) the appropriate combination of crops with different physical properties (e.g. root system, nutritional needs) and growing seasons. The presented approach combines these characteristics and offers a diversity-related typology approach for the differentiation and localization of crop sequence patterns. The typology was successfully applied and examined with a data set of annual arable crop information available in the form of seven-year sequences for Lower Saxony in the north-western part of Germany. About 60% of the investigated area was cropped with the ten largest crop sequence types, which represent the full range of crop pattern diversity from continuous cropping to extreme diversified crop sequences. Maize played an ambivalent role as driver for simplified rotation practice in permanent cropping on the one hand and as element of diversified sequences on the other hand. It could be verified that the less diverse crop sequence types were more strongly related to explicit environmental and socio-economic factors than the widespread diverse sequence types.

      PubDate: 2017-10-14T08:56:20Z
       
  • Does intercropping enhance yield stability in arable crop production'
           A meta-analysis
    • Abstract: Publication date: November 2017
      Source:European Journal of Agronomy, Volume 91
      Author(s): Md. Raseduzzaman, Erik Steen Jensen
      The adverse effects of climate change are significantly decreasing yield levels and yield stability over time in current monocropping systems. Intercropping (IC), i.e. growing more than one species simultaneously in the same field, often increases resource use efficiency and agricultural productivity compared with growing the component crops solely and can enhance yield stability. This meta-analysis of published IC literature quantified and analysed yield stability in IC compared with the respective sole crops, focusing on the effect of intercrop components (e.g. cereal-grain legume, non-cereal-grain legume), experimental patterns (e.g. experiment over years, experiment over locations), IC design (e.g. additive and replacement) and climatic zone (e.g. tropical, subtropical, and temperate). In total, 33 articles were analysed. The coefficient of variation (%CV) of yields was used for assessing yield stability, with lower CV value indicating higher yield stability. The analysis showed that cereal-grain legume IC (CV=22.1) significantly increased yield stability compared with the respective grain legume sole crops (CV=31.7). Moreover, compared with the respective cereal and legume sole crops, IC in the cereal-grain legume systems gave higher yield stability than IC in the non-cereal-grain legume systems. Compared with the respective cereal (CV=25.3) and legume (CV=30.3) sole crops, IC (CV=19.1) in a replacement design had significantly (P<0.05) higher yield stability. Also intercropping in replacement design gave more stable yields than IC in an additive design. In tropical regions, cereal sole crops (CV=26.3) showed lower yield stability than IC (CV=17.7) and legume sole crops (CV=21.7). However, IC in all climatic zones showed higher yield stability than both sole crops. Moreover in our analysis, it was found that a higher yield level provided higher yield stability in crop production. Thus, increasing crop diversification through IC of cereals and grain legumes can enhance yield stability and food security, making an important contribution to eco-functional, ecological or sustainable intensification of global food production.

      PubDate: 2017-10-14T08:56:20Z
       
  • Predicting the slow decline of root lesion nematodes (Pratylenchus
           thornei) during host-free fallows to improve farm management decisions
    • Abstract: Publication date: November 2017
      Source:European Journal of Agronomy, Volume 91
      Author(s): J.P.M. Whish, J.P. Thompson, T.G Clewett, J. Wood, H.E. Rostad
      Pratylenchus thornei is a major pathogen of cereal and legume crops around the world, especially in the northern grains region of eastern Australia. The dominance of host species within the rotation has seen soil pathogen population densities increase. Long weed-free fallows combined with sorghum production (non host crop) to reduce population densities has been successful. However, little is known about the rate of population decline during the fallow or how long this non–host period should continue in order to reduce the population below an accepted damage threshold. The rate of decline from a range of initial starting populations (high, medium, low and very low) were monitored over a 30month weed free fallow. Fallows were initiated in November (late Spring) for three consecutive years. Nematode population densities and soil moisture were measured at eight depths down the soil profile to 1.5m and used to describe the rate of population decline over time in each soil layer. Dynamic populations of P. thornei existed within the upper layers (<0.6m) of the soil and these declined at a rate that could be described by the negative exponential model Y=ae−bt. The time taken for a population to decline was dependent on the initial population density at harvest of the previous host crop. Generally, between 300–600days of host-free fallow was required to reduce a moderately high initial population of 80 P. thornei/cm3 soil to the damage threshold of 2 P. thornei/cm3. The rate of decline varied between soil layers, particularly in the surface layer (0–0.15m), but remained constant from year to year for each layer. There was no interaction between year and soil layer. Knowing the expected rate of decline of a P. thornei population at the start of a fallow allows better management of the crop rotation to ensure populations do not continue to rise and thus reduce the yield potential of future crops.

      PubDate: 2017-10-14T08:56:20Z
       
  • Assessment of uncertainty and sensitivity analyses for ORYZA model under
           different ranges of parameter variation
    • Abstract: Publication date: November 2017
      Source:European Journal of Agronomy, Volume 91
      Author(s): Junwei Tan, Yuanlai Cui, Yufeng Luo
      We explore the effects of different ranges of parameter variation (RPV) on sensitivity and uncertainty analyses for ORYZA_V3 model. In this study, a latin hypercube sampling (LHS) technique is used to generate parameter sample sets, and a regression-based method is employed for the sensitivity analysis on 16 crop parameters. Then, a top-down concordance coefficient (TDCC) is calculated to assess the stability of parameter sensitivity rankings across diverse RPV. Furthermore, coefficients of variation (CV) and 90% confidence intervals (90CI) of daily model outputs are analyzed by considering uncertainty in observations. We find that the increasing RPV multiplies the CV of daily model outputs, whereas the RPV has no effect on the CV’s change rule over time. The 90CI of model outputs include most of the observations when the RPV is more than ±30% perturbation. The standardized regression coefficient (SRC) of some parameters are obviously minified when the RPV is ±5% or ±50% perturbation. The results highlights the importance of RPV selection in the sensitivity and uncertainty analysis of crop model, and ±30% perturbation was suggested when the RPV cannot be specifically obtained.

      PubDate: 2017-10-14T08:56:20Z
       
  • Effect of biogas digestate, animal manure and mineral fertilizer
           application on nitrogen flows in biogas feedstock production
    • Abstract: Publication date: November 2017
      Source:European Journal of Agronomy, Volume 91
      Author(s): Antje Herrmann, Henning Kage, Friedhelm Taube, Klaus Sieling
      The expansion of biogas feedstock cultivation may affect a number of ecosystem processes and ecosystem services, and temporal and spatial dimensions of its environmental impact are subject to a critical debate. However, there are hardly any comprehensive studies available on the impact of biogas feedstock production on the different components of nitrogen (N) balance. The objectives of the current study were (i) to investigate the short-term effects of crop substrate cultivation on the N flows in terms of a N balance and its components (N fertilization, N deposition, N leaching, NH3 emission, N2O emission, N recovery in harvested product) for different cropping systems, N fertilizer types and a wide range of N rate, and (ii) to quantify the N footprint of feedstock production in terms of potential N loss per unit of methane produced. In 2007/08 and 2008/09, two field experiments were conducted at two sites in Northern Germany differing in soil quality, where continuous maize (R1), maize–whole crop wheat followed by Italian ryegrass as a double crop (R2), and maize–grain wheat followed by mustard as a catch crop (R3) were grown on Site 1 (sandy loam), and R1 and a perennial ryegrass ley (R4) at Site 2 (sandy soil rich in organic matter). Crops were supplied with varying amounts of N (0–360kgNha−1, ryegrass: 0–480kgNha−1) supplied as biogas digestate, cattle slurry, pig slurry or calcium-ammonium nitrate (CAN). Mineral-N fertilization of maize-based rotations resulted in negative N balances at N input for maximum yield (Nopt), with R2 having slightly less negative balances than R1 and R3. In contrast, N balances were close to zero for cattle slurry or digestate treatments. Thus, trade-offs between substrate feedstock production and changes of soil organic matter stocks have to be taken into consideration when evaluating biogas production systems. Nitrogen losses were generally dominated by N leaching, whereas for the organically fertilized perennial ryegrass ley the ammonia emission accounted for the largest proportion. Nitrogen balance of the ryegrass ley at Nopt was close to zero (CAN) or highly positive (cattle slurry, digestate). Nitrogen footprint (NFP) was applied as an eco-efficiency measure of N-loss potential (difference of N input and N recovery) related to the unit methane produced. NFP ranged between −11 and +6kgN per 1000m3 methane at Nopt for maize-based rotations, without a significant impact of cropping system or N fertilizer type. However, for perennial ryegrass ley, NFP increased up to 65kgN per 1000m3. The loose relation between NFP and observed N losses suggests only limited suitability for NFP.

      PubDate: 2017-10-14T08:56:20Z
       
  • Cultivar placement affects pollination efficiency and fruit production in
           European pear (Pyrus communis) orchards
    • Abstract: Publication date: November 2017
      Source:European Journal of Agronomy, Volume 91
      Author(s): Muriel Quinet, Anne-Laure Jacquemart.
      European pear (Pyrus communis) requires insect pollination among compatible cultivars for fruit production. However, most commercial orchards have a limited number of cultivars arranged in monotypic blocks or rows. This can result in insufficient inter-cultivar pollination. We hypothesise that limitations in pollen transfer among cultivars could be explained by both insect behaviour and orchard design. We compared insect activity and pollination efficiency in two European pear cultivars, in orchards with different designs: (i) cultivars alternated in the same row or (ii) cultivars in separate rows. To assess limitations in pollen transfer, we also compared hand pollination with compatible pollen versus open pollination by insects. Insect visitors mainly foraged on neighbouring trees within a row, with few movements across rows (1%). Honey bees (Apis mellifera) and bumble bees (Bombus terrestris) visited significantly more flowers per tree (8.5 vs. 3) and more trees (2.1 vs. 1.3) than solitary bees (Andrena spp.) and hoverflies. Insect visitors deposited large amounts of pollen (∼500 pollen grains) on flower stigmas regardless of the insect type. Cultivar placement affected inter-cultivar pollination; less incompatibility signs were observed when cultivars alternated in the same row (5%) than when cultivars were in separate rows (38%). We observed limitations in pollen transfer as open pollination resulted in significant reduced fruit set, compared with hand pollination, in ‘Conférence’ (21% vs. 30.7%) and ‘Doyenné du Comice’ (7.2% vs. 16.8%). The foraging behaviour of the insects limited thus inter-cultivar pollen transfer in the orchards with cultivars in separate rows. Cultivars used for pollination (pollinizers) should be planted in the same rows as the main cultivar to increase inter-cultivar pollination.

      PubDate: 2017-10-14T08:56:20Z
       
  • Inside Front Cover - Editorial Board Page
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90


      PubDate: 2017-09-20T06:53:03Z
       
  • Old tall durum wheat cultivars are suited for dual-purpose utilization
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Francesco Giunta, Giovanni Pruneddu, Francesco Cadeddu, Rosella Motzo
      The lateness, tallness and high vigour of old tall durum wheat cultivars could be advantageous for dual-purpose use and their high propensity for lodging should be reduced by grazing. A 3-year field trial was performed in Sardinia, Italy, in a typical Mediterranean environment. Crops of the durum wheat cultivar Senatore Cappelli were sown in October, and grazing was simulated by clipping half of the plots at the terminal spikelet stage of development. The forage biomass derived from clipping varied greatly between seasons (from 0.8 to 3.3tha−1 dry matter) in response to the notable inter-seasonal variability in weather conditions. Cultivar Senatore Cappelli showed good recovery following clipping, with the ability to attain almost complete radiation interception well before anthesis. The high number of leaves that emerged after clipping might have contributed to this good recovery. Nevertheless, clipping reduced the dry matter produced by anthesis (16tha−1 in clipped compared to 21tha−1 in unclipped crops) as well as the final dry matter (DMMAT) (19tha−1 in clipped compared to 23tha−1 in unclipped crops), although these differences disappeared when the clipped biomass was included. The lower lodging observed at anthesis in the clipped (21%) compared with unclipped crops (63%) likely reduced the difference between treatments. The lower DMMAT of clipped treatments was reflected in a lower grain yield (GY) (3.4tha−1 vs 4.2tha−1 in the unclipped treatment). Clipping did not affect the amount of nitrogen present in the biomass, nitrogen uptake efficiency or radiation use efficiency. GY reduction after clipping was mediated by the reduction in spikes m−2 and kernels m−2 (KNO). Spike fertility was not affected by clipping, because the same amount of radiation was available for each spike (about 1MJ). The period with reduced ground cover after clipping was reflected in an increased evaporation and reduced transpiration, which did not alter the total water used and increased the transpiration efficiency in terms of DMMAT. Old tall durum wheat cultivars manifested good suitability for dual-purpose use in environments with low attainable yields because their low grain yield potential contributed to reducing the negative effects of clipping on GY. Their high straw yield and kernel protein percentage represented an advantage with respect to semi-dwarf cultivars.

      PubDate: 2017-09-02T09:58:07Z
       
  • Biological nitrogen fixation in three long-term organic and conventional
           arable crop rotation experiments in Denmark
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Arjun Pandey, Fucui Li, Margrethe Askegaard, Jørgen E. Olesen
      Biological nitrogen (N) fixation (BNF) by legumes in organic cropping systems has been perceived as a strategy to substitute N import from conventional sources. However, the N contribution by legumes varies considerably depending on legumes species, as well as local soil and climatic conditions. There is a lack of knowledge on whether the N contribution of legumes estimated using short-term experiments reflects the long-term effects in organic systems varying in fertility building measures. There is also limited information on how fertilizer management practices in organic crop rotations affect BNF of legumes. Therefore, this study aimed to estimate BNF in long-term experiments with a range of organic and conventional arable crop rotations at three sites in Denmark varying in climate and soils (coarse sand, loamy sand and sandy loam) and to identify possible causes of differences in the amount of BNF. The experiment included 4-year crop rotations with three treatment factors in a factorial design: (i) rotations, i.e. organic with a year of grass-clover (OGC), organic with a year of grain legumes (OGL), and conventional with a year of grain legumes (CGL), (ii) with (+CC) and without (−CC) cover crops, and (iii) with (+M) and without (−M) animal manure in OGC and OGL, and with (+F) mineral fertilizer in CGL. Cover crops consisted of a mixture of perennial ryegrass and clover (at the sites with coarse sand and sandy loam soils) or winter rye, fodder radish and vetch (at the site with loamy sand soil) in OGC and OGL, and only perennial ryegrass in CGL at all sites. The BNF was measured using the N difference method. The proportion of N derived from the atmosphere (%Ndfa) in aboveground biomass of clover grown for an entire year in a mixture with perennial ryegrass and harvested three times during the growing season in OGC was close to 100% at all three sites. The Ndfa of grain legumes in both OGL and CGL rotations ranged between 61% and 95% depending on location with mostly no significant difference in Ndfa between treatments. Cover crops had more than 92% Ndfa at all sites. The total BNF per rotation cycle was higher in OGC than in OGL and CGL, mostly irrespective of manure/fertilizer or cover crop treatments. There was no significant difference in total BNF between OGL and CGL rotations, but large differences were observed between sites. The lowest cumulated BNF by all the legume species over the 4-year rotation cycle was obtained at the location with sandy loam soil, i.e. 224–244, 96–128, and 144–156kgNha−1 in OGC, OGL and CGL, respectively, whereas it was higher at the locations with coarse sand and loamy sand soil, i.e. 320–376, 168–264, and 200–220kgNha−1 in OGC, OGL and CGL, respectively. The study shows that legumes in organic crop rotations can maintain N2 fixation without being significantly affected by long-term fertilizer regimes or fertility building measures.

      PubDate: 2017-09-02T09:58:07Z
       
  • Can conservation tillage mitigate climate change impacts in Mediterranean
           cereal systems' A soil organic carbon assessment using long term
           experiments
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Ileana Iocola, Simona Bassu, Roberta Farina, Daniele Antichi, Bruno Basso, Marco Bindi, Anna Dalla Marta, Francesco Danuso, Luca Doro, Roberto Ferrise, Luisa Giglio, Fabrizio Ginaldi, Marco Mazzoncini, Laura Mula, Roberto Orsini, Giuseppe Corti, Massimiliano Pasqui, Giovanna Seddaiu, Rodica Tomozeiu, Domenico Ventrella, Giulia Villani, Pier Paolo Roggero
      Simulation models, informed and validated with datasets from long term experiments (LTEs), are considered useful tools to explore the effects of different management strategies on soil organic carbon (SOC) dynamics and evaluate suitable mitigative options for climate change. But, while there are several studies which assessed a better prediction of crop yields using an ensemble of models, no studies are currently available on the evaluation of a model ensemble on SOC stocks. In this study we assessed the advantages of using an ensemble of crop models (APSIM-NWheat, DSSAT, EPIC, SALUS), calibrated and validated with datasets from LTEs, to estimate SOC dynamics. Then we used the mean of the model ensemble to assess the impacts of climate change on SOC stocks under conventional (CT) and conservation tillage practices (NT: No Till; RT: Reduced Tillage). The assessment was completed for two long-term experiment sites (Agugliano – AN and Pisa – PI2 sites) in Italy under rainfed conditions. A durum wheat (Triticum turgidum subsp. durum (Desf.) Husn.) – maize (Zea mays L.) rotation system was evaluated under two different climate scenarios over the periods 1971–2000 (CP: Present Climate) and 2021–2050 (CF: Future Climate), generated by setting up a statistical model based on canonical correlation analysis. Our study showed a decrease of SOC stocks in both sites and tillage systems over CF when compared with CP. At the AN site, CT lost −7.3% and NT −7.9% of SOC stock (0–40cm) under CF. At the PI2 site, CT lost −4.4% and RT −5.3% of SOC stocks (0–40cm). Even if conservation tillage systems were more impacted under future scenarios, they were still able to store more SOC than CT, so that these practices can be considered viable options to mitigate climate change. Furthermore, at the AN site, under CF, NT demonstrated an annual increase of 0.4%, the target value suggested by the 4 per thousand initiative launched at the 21st meeting of the Conference of the Parties in Paris. However, RT at the PI2 needs to be coupled with other management strategies, as the introduction of cover crops, to achieve such target.

      PubDate: 2017-09-02T09:58:07Z
       
  • Mid-season prediction of grain yield and protein content of spring barley
           cultivars using high-throughput spectral sensing
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Gero Barmeier, Katharina Hofer, Urs Schmidhalter
      The ability to forecast grain yields and protein contents of spring barley is of particular interest for the malting and brewing industry, as well as for plant breeding. However, methods for early prediction of grain yield and protein content should ideally be timesaving, non-destructive and inexpensive. In this 3-year study using the mobile phenotyping platform PhenoTrac 4, proximally sensed reflectance data of 34 cultivars were used to develop vegetation indices and to calibrate PLSR models, followed by subsequent validation in independent field trials. A comparison among PLSR, the NDVI and REIP indices and an optimized vegetation index indicated that PLSR and REIP (R2 =0.71-0.95) gave superior predictions of grain yield. Furthermore, it was possible to distinguish the performance of different cultivars. In contrast, protein content could not be predicted reliably. As an alternative, a PLSR model of leaf N uptake at anthesis was tested to predict grain protein content. Satisfactory correlations were obtained with R2 =0.61, but protein content was considerably overestimated. The results show that tractor-based proximal sensing is a high-throughput, non-destructive and precise method to predict the grain yield of spring barley and could be a suitable tool to deliver information for the brewing industry and plant breeders.

      PubDate: 2017-09-02T09:58:07Z
       
  • Diverse dynamics in agroecological transitions on fruit tree farms
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Marie Dupré, Thierry Michels, Pierre-Yves Le Gal
      Agroecological transition refers to the adoption by farmers of practices based on on-farm biological processes rather than imported or non-renewable inputs. Drawing from a comprehensive survey of 31 diversified farms cultivating citrus on Réunion Island (Indian Ocean, France), this study aims to understand the diverse dynamics in farmers’ agroecological transitions and to identify the factors and processes driving farmers’ choices. The analysis considers both the current protection, fertilization and weed control practices implemented by farmers in their orchards and the trajectories of change they have followed over the last thirty years. Orchard management was categorized according to the kind of inputs mobilized (i.e., “synthetic inputs”, “alternative off-farm inputs” and “alternative on-farm inputs”). Diverse managements were observed, targeting security, autonomy, ecology or simplicity. The six types of practice trajectories identified illustrate the diverse and incremental nature of agroecological transition. Drawing from these results, drivers of alternative practice adoption and lock-in effects in synthetic input reliance were characterized. Internal drivers, depending directly on the farmer and his/her farm, included the characteristics of the orchard and its environment, the labor force, and the farmer’s environmental concerns. External drivers included local citrus markets, public legislation, access to extension services, the organization of input supply and the social environment. The combination of these internal and external drivers at the farm level makes each farm relatively unique. However, three factors determine the main differences in practices: the marketing channel used, the farmer’s environmental objectives, and the farmer’s economic behavior, which is linked to the weight of the crop activity in farm revenue. Understanding farmers’ points of view and decisions regarding agroecological transition deserves the attention of scientists, agricultural advisors and policy makers when designing innovative cropping systems, new support methodologies and incentives to respond effectively to farmers’ objectives and contexts of action.

      PubDate: 2017-08-03T09:20:07Z
       
  • Understanding effects of multiple farm management practices on barley
           performance
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Libère Nkurunziza, Iman Raj Chongtham, Christine A. Watson, Håkan Marstorp, Ingrid Öborn, Göran Bergkvist, Jan Bengtsson
      Because of the complexity of farming systems, the combined effects of farm management practices on nitrogen availability, nitrogen uptake by the crop and crop performance are not well understood. To evaluate the effects of the temporal and spatial variability of management practices, we used data from seventeen farms and projections to latent structures analysis (PLS) to examine the contribution of 11 farm characteristics and 18 field management practices on barley performance during the period 2009–2012. Farm types were mixed (crop-livestock) and arable and were categorized as old organic, young organic or conventional farms. The barley performance indicators included nitrogen concentrations in biomass (in grain and whole biomass) and dry matter at two growing stages. Fourteen out of 29 farm characteristics and field management practices analysed best explained the variation of the barley performance indicators, at the level of 56%, while model cross-validation revealed a goodness of prediction of 31%. Greater crop diversification on farm, e.g., a high proportion of rotational leys and pasture, which was mostly observed among old organic farms, positively affected grain nitrogen concentration. The highest average grain nitrogen concentration was found in old organic farms (2.3% vs. 1.7 and 1.4% for conventional and young organic farms, respectively). The total nitrogen translocated in grain was highest among conventional farms (80kgha−1 vs. 33 and 39kgha−1 for young and old organic farms, respectively). The use of mineral fertilizers and pesticides increased biomass leading to significant differences in average grain yield which became more than double for conventional farms (477±24gm−2) compared to organic farms (223±37 and 196±32gm−2 for young and old organic farms, respectively). In addition to the importance of weed control, management of crop residues and the organic fertilizer application methods in the current and three previous years, were identified as important factors affecting the barley performance indicators that need closer investigation. With the PLS approach, we were able to highlight the management practices most relevant to barley performance in different farm types. The use of mineral fertilizers and pesticides on conventional farms was related to high cereal crop biomass. Organic management practices in old organic farms increased barley N concentration but there is a need for improved management practices to increase biomass production and grain yield. Weed control, inclusion of more leys in rotation and organic fertilizer application techniques are some of the examples of management practices to be improved for higher N concentrations and biomass yields on organic farms.

      PubDate: 2017-08-03T09:20:07Z
       
  • Climate change effects on leaf rust of wheat: Implementing a coupled
           crop-disease model in a French regional application
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Julie Caubel, Marie Launay, Dominique Ripoche, David Gouache, Samuel Buis, Frédéric Huard, Laurent Huber, François Brun, Marie Odile Bancal
      Leaf rust is responsible for significant wheat yield losses. Its occurrence and severity have increased in recent years, partly because of warmer climate. It is therefore critical to understand and anticipate the effects of climate change on leaf rust. Direct climate effects and indirect effects via host plants that provide a biophysical environment for disease development were both considered. The coupled STICS-MILA model simulates both crop and pathogen dynamics in a mechanistic way and their interaction is managed by two sub-models: one calculating the microclimate within the canopy and the other converting numbers of spores and lesions to affected surfaces. In this study, STICS-MILA was first calibrated and evaluated using leaf rust severity observed at various sites in France for multiple years. STICS-MILA was then run on three contrasting French sites under 2.6, 4.5 and 8.5 RCP future climate scenarios. Results focused firstly on changes in disease earliness and intensity, secondly on disease dynamics, particularly the synchronism between plant and disease developments, and finally on elementary epidemic processes. The calibration and evaluation of STICS-MILA revealed a high sensitivity to the initial amount of primary inoculum (a forcing variable in STICS-MILA) and thus the need to properly simulate the summering and overwintering pathogen survival. The simulations in the context of future climate showed a significant change in host-pathogen synchronism: in the far future, according to RCP 4.5 and 8.5 scenarios, disease onset is expected to occur not only with an advance of around one month but also at an earlier developmental stage of wheat crops. This positive effect results from rising temperatures, nevertheless partly counter-balanced during spring by lower wetness frequency. The crop growth accelerates during juvenile stages, providing a greater support for disease development. The resulting microclimate shortens latency periods and increases infection and sporulation efficiencies, thus causing more infectious cycles. An increase of final disease severity is thus forecasted with climate change.

      PubDate: 2017-08-03T09:20:07Z
       
  • Modelling fertiliser significance in three major crops
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Ben Parkes, Benjamin Sultan, Philippe Ciais, Xuhui Wang
      We present work using two long-term climate datasets to show that nitrogen fertiliser is an important aspect of yield projection for three major crops. The ability of linear models using climate variables as predictors to accurately project the yield of maize, rice and wheat over multi-decadal scales is improved with the addition of fertiliser as an input. Highly productive nations including Argentina, India, Poland and South Africa show significant improvement in yield simulations and show that fertiliser use should not be discounted when estimating yield variability. The use of nitrogen fertiliser in the generalised linear models improves yield forecast by 18% using the Princeton climate dataset and 23% using the WFDEI climate dataset. This work therefore supports the use of additional predictors than climate for improving the ability of statistical models to reconstruct yield variability.

      PubDate: 2017-07-24T09:09:46Z
       
  • Productivity of organic and conventional arable cropping systems in
           long-term experiments in Denmark
    • Abstract: Publication date: October 2017
      Source:European Journal of Agronomy, Volume 90
      Author(s): Ambreen Shah, Margrethe Askegaard, Ilse A. Rasmussen, Eva Maria Cordoba Jimenez, Jørgen E. Olesen
      A field experiment comparing different arable crop rotations was conducted in Denmark during 1997–2008 on three sites varying in climatic conditions and soil types, i.e. coarse sand (Jyndevand), loamy sand (Foulum), and sandy loam (Flakkebjerg). The crop rotations followed organic farm management, and from 2005 also conventional management was included for comparison. Three experimental factors were included in the experiment in a factorial design: 1) crop rotation (organic crop rotations varying in use of whole-year green manure (O1 and O2 with a whole-year green manure, and O4 without), and a conventional system without green manure (C4)), 2) catch crop (with and without), and 3) manure (with and without). The experiment consisted of three consecutive cycles using four-course rotations with all crops present every year, i.e. 1997–2000 (1st cycle), 2001–2004 (2nd cycle), and 2005–2008 (3rd cycle). In the 3rd cycle at all locations C4 was compared with two organic rotations, i.e. O2 and O4. The O2 rotation in the third cycle included spring barley, grass-clover, potato, and winter wheat, whereas C4 and O4 included spring barley, faba bean, potato, and winter wheat. For the O2 rotation with green manure there was a tendency for increased DM yield over time at all sites, whereas little response was seen in N yield. In the O4 rotation DM and N yields tended to increase at Foulum over time, but there was little change at Flakkebjerg. The DM yield gap between organic and conventional systems in the 3rd cycle varied between sites with 34–66% at Jyndevad, 21–44% at Foulum, and 32–52% at Flakkebjerg. The inclusion of grass-clover resulted in lower cumulated yield over the rotation than the treatment without grass-clover. The use of manure reduced the DM yield gap between conventional and organic systems on an average by 15 and 21%-points in systems with and without grass-clover, respectively, and the use of catch crops reduced the yield gap by 3 and 5%-points in the respective systems. Across all crops the agronomic efficiency of N in manure (yield benefit for each kg of mineral N applied) was greater in O4 compared with O2 for all crops.

      PubDate: 2017-07-24T09:09:46Z
       
 
 
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