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European Journal of Agronomy
Gauthier-Villars
European Journal of Agronomy

Gauthier-Villars

1161-0301

European Journal of Agronomy/Journal European Journal of AgronomyISTPSCI
正式出版
收录年代

    Soybean response and profitability upon inoculation and nitrogen fertilisation in Belgium

    Pannecoucque, J.Goormachtigh, S.Ceusters, N.Bode, S....
    10页
    查看更多>>摘要：The recent introduction of soybean cultivation in Belgium and several other north-western European countries holds great potential for sustainable agriculture. Agricultural practices must be fine-tuned to optimise yield and quality before soybean will become a profitable crop for Belgian farmers. The effect of inoculation and N fertilisation on crop yield, protein content and relative profitability of soybean in Belgium was studied. Trials with nitrogen (N) fertilisation and inoculation of soybean were performed during two seasons (2016 and 2017) at two locations (Geel and Merelbeke) in Belgium. Nitrogen was applied as mineral fertiliser at different doses (0 N, 35 N, 70 N or 140 N) at the day of sowing and/or at the R1 stage. Highest yields and protein contents were obtained upon inoculation, showing that inoculation is the most appropriate practice to increase yield and protein levels of soybean in Belgium. Inoculation also increased thousand grain weight and improved several biophysical parameters calculated from chlorophyll a fluorescence measurements. Additionally, inoculation and N fertilisation raised chlorophyll content of the soybean leaves and N content and N uptake of the aboveground biomass. Application of N inhibited nodulation of inoculated soybeans. Tolerance to lodging and oil contents were lower upon inoculation or N application. Relative profitability (RP) of inoculated soybeans was higher than for non inoculated soybeans. Application of N fertiliser to soybeans did not significantly increase RP. Optimisation of inoculation and nodulation is the best approach to maximise yield and protein content and thus to improve the economic viability of soybean cultivation for Belgian farmers in the short term.
      原文链接:
    • NSTL
    • Elsevier

    Productivity, light interception and radiation use efficiency of organic and conventional arable cropping systems

    Harbo, Laura SofieDe Notaris, ChiaraZhao, JinOlesen, Jorgen E....
    10页
    查看更多>>摘要：How the productivity of crops in organic arable farming may be sustainably increased remains a key issue. We combined measurements of crop yield, total aboveground biomass (AGB) and light interception over a 4-year crop rotation cycle from 2015 to 2018 in a long-term experiment in Denmark with arable organic and conventional cropping systems. These cropping systems comprise one conventional (CGL) and two organic (OGL and OGC) crop rotations, where CGL and OGL had three spring cereal and one grain legume crop (faba bean) in the rotation, and the faba bean was in OGC replaced with grass-clover. All crop rotations were grown with and without the use of cover crops, and the organic systems were grown with and without the manure application. The light interception was calculated from measurements of spectral reflectance, and this allowed the AGB to be decomposed into accumulated intercepted PAR (AIPAR) and radiation use efficiency (RUE). The conventional cropping system (CGL) had significantly greater AGB, AIPAR and RUE compared with the corresponding organic, grain legume-based system (OGL). AIPAR of the organic grass-clover-based cropping system (OGC) was greater than CGL, although the contrary conclusion was found in AGB and RUE. Across crops, RUE was greatest for cereals and smallest for faba bean and grass-clover. AIPAR was consistently greatest for grass-clover, and both grass-clover and faba bean had smaller variability in AIPAR between years and treatments than the cereal crops. Cover crops significantly increased AGB and AIPAR in the organic cropping systems but not in CGL. RUE was not significantly affected by the inclusion of cover crops. The use of manure in the organic systems increased AGB, AIPAR and RUE. The results show that AIPAR can be higher in organic cropping systems compared with conventional cropping systems, but this is not translated into a greater yield of cereal crops. There is, therefore, a need for novel approaches to management and the use of biomass in organic cropping systems for increasing yields for feed and food, and which sustains soil fertility.
      原文链接:
    • NSTL
    • Elsevier

    Emergence modelling of 18 species susceptible to be used as cover crops in Mediterranean semiarid vineyards

    Cabrera-Perez, CarlosRecasens, JordiBaraibar, BarbaraRoyo-Esnal, Aritz...
    14页
    查看更多>>摘要：Cover Crops (CC) are increasingly appreciated in vineyards because they can provide ecosystems services, such as preventing soil erosion and compaction, increasing soil organic matter or, controlling weeds. Many species from different botanical families can be used depending on the final purpose of the CC, but their successful estab-lishment in Mediterranean semiarid conditions of NE Spain can be challenging. Therefore, it is mandatory to understand and be able to predict the emergence patterns of the chosen species as their success is crucial to achieve a good soil cover. Different models based on thermal time (TT), hydrothermal time (HTT), photo-hydrothermal time (PhHTT) and photosolar hydrothermal time (PhSHTT) have already been used in crops and weeds for this purpose. In this paper, these four models have been developed for the 18 species susceptible of being CC, some of them being successfully validated with independent data from southern France. Results suggest that, although TT and HTT based models are accurate, their precision is improved when light is included (R-2 >0.9). Models including light could be widespread used in some species as the successful validation with independent data demonstrates. These models considerably contribute to inter-row management in vineyards as decision support systems (DSS) tools to predict CC establishments.
      原文链接:
    • NSTL
    • Elsevier

    Modeling the impact of climate warming on potato phenology

    Naz, SahrishAhmad, ShakeelAbbas, GhulamFatima, Zartash...
    13页
    查看更多>>摘要：Understanding the influence of thermal trends, crop management practices, and genetics on the crop developmental stages and phases is critical to develop adaptation strategies in the face of warming trends. The specific study objectives were to determine the correlation between observed potato phenology with the trends of rising temperature, and to investigate the impacts of thermal trend, crop management practices, and changes in cultivars using a modeling approach. The study was conducted at 12 sites in Punjab, Pakistan from 1980 to 2018 using phenological observations for both the spring and autumn potato crop. For the stages observed during spring, there was an average advance of 6.2 days decade(-1) for sowing, 6.0 for emergence, 3.8 for tuber initiation, and 2.0 for maturity. However, for the stages observed during autumn, there was an average delay of 5.2 days decade(-1) for sowing, 5.1 for emergence, 3.3 for tuber initiation, and 2.3 for maturity. The average phase duration decreased on average by 2.4 days decade(-1) for sowing to tuber initiation, 1.8 days decade(-1) for tuber initiation to maturity for spring, and 4.2 days decade(-1) for sowing to maturity. The average autumn phase duration decreased on average by 1.9 days decade(-1) for sowing to tuber initiation, 1.0 days decade(-1) for tuber initiation to maturity, and 2.9 days decade(-1) for sowing to maturity. With respect to the local weather observation, the average air temperature had increased 0.8 degrees C decade(-1) for spring and autumn from 1980 to 2018. The differences in spring and autumn phenology had a statistically significant negative correlation with the increase in temperature from 1980 to 2018. When the CSM-SUBSTOR-Potato model was used for a standard variety across locations and years, the predicted phenological stages, on average, occurred earlier due to increase in temperature from 1980 to 2018, while there was less impact on the observed phenological stages. This indicated that during the last four decade, adaptation strategies such as earlier planting for spring potato, and later planting for autumn, as well as the release of new cultivars that require more thermal time compared to the traditional cultivars have been implemented by growers have compensated for some part of temperature induced warming trends of spring and autumn potato phenology.
      原文链接:
    • NSTL
    • Elsevier

    Exploiting centimetre resolution of drone-mounted sensors for estimating mid-late season above ground biomass in rice

    Adeluyi, OluseunHarris, AngelaFoster, TimothyClay, Gareth D....
    13页
    查看更多>>摘要：Above ground biomass (AGB) is an important indicator of rice for improving agronomic management efficiency and yield monitoring in crops. In particular, rice AGB during the mid (reproductive) and late (ripening) stages are responsible for the panicles per given area, the number of spikelets or grains per panicle, the percentage of filled kernels and grains; and the weight of each grain. Consequently, proper monitoring of rice AGB, particularly during the mid to late growth stages, are important for accurate estimation of rice yield. To this end, monitoring AGB at centimetre scale has become implementable by using sensors onboard Unmanned Aerial Vehicles (UAVs) or drones. The RGB sensors capable of generating plant height estimations from digital surface models provide a viable option for monitoring rice AGB. The advancement in miniature Multi-Spectral Imager (MSI) sensors capable of generating vegetation indices (VIs) and texture metrics (TM) also provides the opportunity to ascertain the capability of the sensor to estimate rice AGB, particularly during the growth stages. The study compares the potential and relative merits of using drone-mounted consumer-grade RGB imagery and/ or scientific-grade multispectral imagery for estimating rice mid-late season above ground biomass. Plant height estimates generated from digital surface model derived from the RGB sensor were compared with in-situ measurements of biomass using a simple linear regression (SLM) model. On the other hand, VIs, TM and their combination were accessed using the Random Forest model for estimating rice AGB. We also accessed the combination of both sensors for estimating rice AGB. Results testing model quality statistically showed plant height (R-2 = 0.72; RMSE = 1.07 t/ha; MAE = 0.93 t/ha) estimates from the RGB camera performed better than VIs (R-2 = 0.59; RMSE = 1.31 t/ha; MAE = 1.06 t/ha), TM (R-2 = 0.43; RMSE = 1.58 t/ha; MAE = 1.22 t/ha) and the combination of VIs and TM when estimating rice AGB at the mid to late growing stages. When combining plant height and VIs from both cameras to estimate AGB, results suggest that the combination using random forest models improve the estimation of rice AGB. The combination of TM, VIs and Plant Height (PH) estimates produced the most statistically accurate estimates ((R2) = 0.74; RMSE = 1.02 t/ha; MAE = 0.82 t/ha). Our findings suggest that the Plant height estimates from the RGB sensor produce a more accurate estimation of AGB compared to the MSI camera. However, the most accurate estimations are seen when both sensors are combined to estimate rice AGB at the mid to late growth stage.
      原文链接:
    • NSTL
    • Elsevier

    Combining UAV multispectral imagery and ecological factors to estimate leaf nitrogen and grain protein content of wheat

    Fu, ZhaopengYu, ShanshanZhang, JiayiXi, Hui...
    15页
    查看更多>>摘要：Nitrogen is an essential element of wheat growth and grain quality. Leaf nitrogen content (LNC), a critical monitoring indicator of crop nitrogen status, plays a reference role for later estimations of grain protein content (GPC). Developments in unmanned aerial vehicle (UAV) platforms and multispectral sensors have provided new approaches for LNC monitoring and GPC estimation, with great convenience for assessing the nutritional status of plants and grains without traditional destructive sampling. The objective of this study was to evaluate the feasibility of wheat LNC monitoring and GPC estimation based on UAV multispectral imagery. Wheat experiments were carried out in Xinghua, Kunshan and Suining of Jiangsu Province during 2018-2019 and in Rugao of Jiangsu Province during 2020-2021 with different varieties and nitrogen application rates. Remote sensing images were obtained by a multi-rotor UAV carrying a multispectral camera. The destructive sampling method was used to collect LNC, GPC and other field data. Wheat LNC monitoring and GPC estimation models were established after selection of the optimal indicators. Different modelling methods were used for the comparative analysis, including unitary linear regression, multiple linear regression and artificial neural network (ANN) methods. Three techniques were adopted to improve the GPC prediction accuracy: (1) multiple factors were substituted for single factor for the prediction; (2) texture information was added through further imagery mining; and (3) ecological factors were considered to improve the prediction mechanism. The results showed that the use of UAV-based Airphen multispectral imagery had a good effect on wheat LNC monitoring and GPC estimation. The vegetation indices constructed by red-edge and near-infrared bands had good performances in LNC monitoring and GPC estimation. The addition of texture information and ecological factors further improved the modelling accuracy. In this study, the optimal wheat GPC estimation model was established by NDVI (675, 730) at the jointing stage, NDVIT (730mea., 850) at the booting stage, NDVIT (730mea., 850) at the flowering stage and NDVI (730, 850) at the early filling stage. The modelling R2, validation R2 and relative root mean square error (RRMSE) reached 0.662, 0.7445 and 0.0635, respectively. The results provide a reference for crop LNC monitoring and GPC estimation based on UAV multispectral imagery.
      原文链接:
    • NSTL
    • Elsevier

    Ensuring future agricultural sustainability in China utilizing an observationally validated nutrient recommendation approach

    He, PingXu, XinpengZhou, WeiSmith, Ward...
    10页
    查看更多>>摘要：Fertilizer has revolutionized crop production, but a lack of evidence-based fertilizer usage has resulted in negative economic and environmental ramifications, particularly for smallholder farmers. This study aimed at developing an innovative nutrient recommendation approach, Nutrient Expert (NE), for improving yields of maize, wheat, and rice while optimizing fertilizer input through adoption of 4R (applying the right source of nutrients at the right rate, time and place) nutrient stewardship technologies, and evaluating the large-scale performance on crop productivity and the environmental impact of cropping systems. Thus, we compared NE to current farmers' practice (FP) and soil test-based fertilizer application (ST) for 1,534 farm field experiments in order to validate the benefits of NE on both crop productivity and environmental protection in the main cereal production areas in China. Overall, the NE treatment achieved 4.4 % higher grain yield and 5.8 % more profit over FP, more yield for rice, but no differences for maize and wheat over ST. Nutrient Expert required 29.0 % and 14.7 % less fertilizer N than FP and ST, respectively. The NE recommendations improved the nitrogen (N) recovery efficiency by 10.8-13.4 percent points over FP across the 1,534 sites. Using the NE approach, on average, reactive N losses and greenhouse gas (GHG) emissions were reduced by 36.2 % and 21.5 % over FP, 16.0 % and 9.9 % over ST, respectively. The NE, as a user-friendly tool, is widely applicable across farm types and climatic regions. It could be beneficial for improving fertilizer use efficiency and maintaining strategic food security for smallholder production areas in China where N fertilizer is inappropriate and usually over applied. This approach could potentially be expanded to help reduce N losses and GHG emissions in other regions globally.
      原文链接:
    • NSTL
    • Elsevier

    Short phases of tropical forage legumes increase production of subsequent cereal crops in the seasonally dry tropics of eastern Indonesia

    Bell, Lindsay W.Hossang, Evert Y.Traill, Skye R.Dalgliesh, Neal P....
    12页
    查看更多>>摘要：In temperate systems, it is well known that forage legumes can improve both nitrogen (N) supply and yields of subsequent cereal crops. While this is assumed to be true in tropical systems, it is less well tested, particularly in smallholder settings where forage is often cut and removed from the field. This paper confirms the potential of short phases of tropical forage legumes to provide N to subsequent crops in seasonally dry tropical farming systems. Across five experiments, maize and rice grain yields increased by up to 80 % after 4-8 month rotations of forage legumes, but the benefits were smaller when legume growth was reduced, biomass was removed for forage, or the yield potential of cereal crops was lower. We found that the additional N cycling from legumes can last for at least 2 years, although the benefit diminishes with time. When all legume material was retained as mulch, the estimated additional N provided to subsequent no-till maize crops was the equivalent of 9-15 kg urea-N per tonne of above-ground legume biomass produced but fell to 1.5-3 kg urea-N/t if forage was removed. After shoot removal, more legume N cycled to a subsequent rice crop (equivalent of 11-13 kg urea-N/t of legume biomass) than to a no-till maize crop, presumably because more below-ground material mineralised. Of the legumes tested, Clitoria ternatea grew best across a variety of environments and use patterns and provided the largest yield benefits to subsequent crops. This research demonstrates the potential to integrate short phases of tropical herbaceous forage legumes into smallholder crop-livestock systems in the seasonally dry tropics, and, in doing so, improve or maintain staple grain crop production and household food self-sufficiency.
      原文链接:
    • NSTL
    • Elsevier

    Lodging resistance in maize: A function of root-shoot interactions

    Zhang, PingYan, YeGu, ShuangchengWang, Yuanyuan...
    12页
    查看更多>>摘要：The differences in root and stem structure between lodging resistant (LR) and susceptible (LS) genotypes have yet to be fully understood in maize (Zea mays L.). To clarify these differences, lodging rates and yield of LS genotype XunDan20 (XD20) and LR genotype FuMin985 (FM985) across five locations in China from 2014 to 2018 were investigated. Simultaneously, field experiments including genotypes XD20 and FM985 and two plant densities of 75,000 (D75000) and 105,000 plant ha(-1) (D105000) were specifically performed at two locations in North China Plain in 2018. Stem and root lodging rates of XD20 were significantly higher than that of FM985 mainly because FM985 had a larger root system and a stronger basal stem. Compared to XD20, FM985 had significantly larger values in root crown width, root angle, length (+37.1 %), volume (+25.5 %), and length density (+29.9 %) in 0 10 cm soil. Although FM985 had longer and thinner basal stem internodes, the larger sclerenchyma and more compact distribution of epidermal cells in the rind resulted in greater rind penetration strength in FM985 than in XD20. Results from C-13 and N-15 isotope labelling revealed that the high stem strength and root anchorage strength of FM985 were related to the large assimilate allocations to roots and basal internodes. With increased plant density, XD20 had larger reductions in stem morphological parameters, leading to a smaller stem lodging resistance; FM985 showed larger reductions in root traits but still had a high root lodging resistance at high plant density due to the large root system. LR maize allocates more photosynthetic assimilates to roots and stems and maintains a higher capacity of nutrient absorption, reflecting a function of root-shoot interactions during formation and maintenance of lodging resistance.
      原文链接:
    • NSTL
    • Elsevier

    Microclimate estimation under different coffee-based agroforestry systems using full-sun weather data and shade tree characteristics

    Merle, IsabelleVillarreyna-Acuna, RogelioRibeyre, FabienneRoupsard, Olivier...
    13页
    查看更多>>摘要：In Central America, coffee is mainly grown in agroforestry systems. This practice modifies the microclimate, which, in turn, influences coffee growth and development. However, modeling these microclimate modifications is a challenge when trying to predict the development of a disease in the understory crop, based on variables usually monitored in weather stations exposed to full sunlight. Furthermore, critical variables for plant disease development, such as leaf wetness duration and leaf temperatures, are generally not measured by weather sta-tions. In our study, we sought to build models explaining daily minimum and maximum coffee leaf temperatures, daily coffee leaf wetness duration, and minimum and maximum air temperatures in agroforestry systems with a single shade tree species, which are common in Central America, and which were characterized by shade tree height, canopy openness and light gap distribution. The modeled variables were mainly explained by one or more meteorological variables provided by reference weather stations exposed to full sunlight. The presence of shade trees resulted in a buffer effect, reducing daily maximum air and leaf temperatures, and increasing daily mini-mum air and leaf temperatures. Moreover, except for the daily minimum air temperature under shade, shade tree characteristics affected these microclimatic variables. Indeed, the buffer effect on the daily maximum air tem-perature increased with shade trees 7 m tall or over, whereas for extreme leaf temperatures, this effect seemed to be further intensified by a dense and homogeneous canopy. The tallest shade trees also tended to provide conditions that reduced coffee leaf wetness duration. The coffee leaf stratum affected the daily maximum leaf temperature, with a top layer intercepting radiation for the lower strata, but had no effect on the daily minimum leaf temperature, detected at night. The models developed were simple equations allowing interpretation of shade tree height, the effects of canopy characteristics on the microclimate and were therefore useful for designing and managing agroforestry system. The more accurate models could be incorporated into an early warning system for coffee pests and diseases in the region.
      原文链接:
    • NSTL
    • Elsevier