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W Diepenbrock - One of the best experts on this subject based on the ideXlab platform.
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integrated nitrogen management strategies to improve seed yield oil content and nitrogen efficiency of Winter Oilseed rape brassica napus l a review
Agriculture Ecosystems & Environment, 2006Co-Authors: G W Rathke, T Behrens, W DiepenbrockAbstract:Winter Oilseed rape (Brassica napus L.) is the dominant Oilseed crop in northern Europe. Generally, it requires high amounts of nitrogen (N) but is characterized by low N-efficiency, which is defined as produced seed dry weight per unit of accumulated N-fertilizer. Consequently, there is a strong need to resume all the relevant information on N in relation to cropping of Winter Oilseed rape and environmental impact to improve the efficiency of rape production. To enhance the productivity of Winter Oilseed rape cropping, integrated N-management strategies are needed including optimized N-supply due to varied crop rotations or fertilization, best soil and crop management practices. This paper reviews various N-management strategies in relation to seed yield and N-efficiency of Winter Oilseed rape. Comparing different previous crops, Winter Oilseed rape yielded considerably lower after cereal crops than following legumes. The seed yield is not only affected by the position within the crop rotation but also by the length of the break between two Winter Oilseed rape crops and type of cultivar. The use of N-efficient cultivars with reduced N-demand led to lower N-balance surpluses. Since the optimal N-treatment varies with cultivar, year and site condition, the maximum quantity of N-fertilizer for highest seed yield are discussed. A comparison of N-fertilizers reveals that N-fertilizers work different due to their chemical composition. Moreover, rate of N-recovery varies among methods and timing of N-application. Adjusted to the timing of optimum N-demand of the crop, timing of N-doses effectively increases production efficiency of Winter Oilseed rape. Apart from these integrated N-management strategies soil cultivation, seeding, application of plant protection agents and plant growth regulators as well as soil fertilization and harvesting are closely interacting with N-efficiency of Winter Oilseed rape. Altogether, amount and timing of N-fertilizer as well as cultivar selection had the strongest influence on productivity followed by smaller effects due to previous crop and type of fertilizer. Using N-efficient management strategies like choice of variety, form and timing of N-application adapted to site conditions, a remarkable reduction in fertilizer N-demand (up to 50% of fertilizer input) is possible leading to lower N-balance surpluses in Winter Oilseed rape production, thus minimizing environmental pollution.
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energy balance of Winter Oilseed rape brassica napus l cropping as related to nitrogen supply and preceding crop
European Journal of Agronomy, 2006Co-Authors: G W Rathke, W DiepenbrockAbstract:Data from a field experiment (1995–2000) conducted on a fertile sandy loess in the Hercynian dry region of central Germany were used to determine the energy efficiency of Winter Oilseed rape ( Brassica napus L.) as affected by previous crop and nitrogen (N) fertilization. Depending on the previous crop, Winter Oilseed rate was cultivated in two different crop rotations: (1) Winter barley ( Hordeum vulgare L.)–Winter Oilseed rape–Winter wheat (Triticum aestivum L.), and (2) pea (Pisum sativum L.)–Winter Oilseed rape–Winter wheat. Fertilizer was applied to Winter Oilseed rape as either calcium ammonium nitrate (CAN) or cattle manure slurry. The N rates applied to Winter Oilseed rape corresponded to 0, 80, 160 and 240 kg N ha −1 a −1 . Results revealed that different N management strategies influenced the energy balance of Winter Oilseed rape. Averaged across years, the input of energy to Winter Oilseed rape was highly variable ranging from 7.42 to 16.1 GJ ha −1 . Lowest energy input occurred when unfertilized Winter Oilseed rape followed Winter barley, while the highest value was obtained when Winter Oilseed rape received 240 kg N ha −1 organic fertilization and followed Winter barley. The lowest energy output (174 GJ ha −1 ), energy from seed and straw of Winter Oilseed rape, was observed when Winter Oilseed rape receiving 80 kg N ha −1 as organic fertilizer followed Winter barley. The energy output increased to 262 GJ ha −1 for Winter Oilseed rape receiving 240 kg N ha −1 as mineral fertilizer followed pea. The energy efficiency was determined using the parameters energy gain (net energy output), energy intensity (energy input per unit grain equivalent GE; term GE is used to express the contribution that crops make to the nutrition of monogastric beings), and output/input ratio. The most favourable N rate for maximizing energy gain (250 GJ ha −1 ) was 240 kg N ha −1 , while that needed for minimum energy intensity (91.3 MJ GE −1 ) was 80 kg N ha −1 and for maximum output/input ratio (29.8) was 0 kg N ha −1 .
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effects of nitrogen source and rate on productivity and quality of Winter Oilseed rape brassica napus l grown in different crop rotations
Field Crops Research, 2005Co-Authors: G W Rathke, Olaf Christen, W DiepenbrockAbstract:Data from a field experiment (1995‐2000) conducted on a fertile sandy loess in the Hercynian dry region of central Germany were used to determine the productivity of Winter Oilseed rape (Brassica napus L.) as affected by previous crop and nitrogen (N) fertilization. The crop rotations compared wereWinter barley (Hordeum vulgareL.)‐Winter Oilseed rape‐Winter wheat (Triticum aestivum L.), and pea (Pisum sativum L.)‐Winter Oilseed rape‐Winter wheat. Fertilizer was applied to Winter Oilseed rape as either calcium ammonium nitrate (CAN) or cattle manure slurry. The N rates applied to Winter Oilseed rape corresponded to 0, 80, 160, and 240 kg N ha 1 a 1 . Management effects on seed yield, seed oil and crude protein contents, and energy and CO2 storage in the seed were assessed. The different N management strategies influenced productivity of Winter Oilseed rape. Data averaged across all years indicated that the lowest productivity in terms of seed yield (2.79 t ha 1 ), energy storage (7.90 GJ ha 1 ), and CO2 storage (7.69 t ha 1 ) occurred when unfertilised Winter Oilseed rape followed Winter barley. Highest values for all these traits were obtained at 240 kg ha 1 mineral N fertilization when the effects of the previous crop were small. Pooled maximum seed yields for the high fertilizer rate ranged from 4.79 to 4.90 t ha 1 . Storage of energy and CO2 by the seeds ranged from 13.6 to 13.9 GJ ha 1 and 13.2 to 13.5 t ha 1 , respectively. Under high N rates, the lowest oil contents (43.8‐44.1%) were observed. In contrast, highest oil concentrations were found for the unfertilised plots (46.8‐47.7%). Crude protein contents of 21.6% and 17.7% were measured at high and low N rates, respectively. Results emphasize that N fertilization rate had the strongest influence on the productivity of Winter Oilseed rape followed by smaller effects due to previous crop and type of fertilizer and interactions between these treatment factors. # 2004 Elsevier B.V. All rights reserved.
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yield analysis of Winter Oilseed rape brassica napus l a review
Field Crops Research, 2000Co-Authors: W DiepenbrockAbstract:Abstract This paper reviews the most important biological processes that determine the yield of Winter Oilseed rape ( Brassica napus L.). Biological yield is the product of growth rate and duration of the growing period, both of which indicate the potential for improvement in yield. Likewise, a greater harvest index leads to a higher seed yield. A brief survey of five recently published rapeseed crop models is given. Most of these models are poor predictors of biomass and yield; there is a lack of information about key physiological processes involved in establishment of the stand, the production of biomass and formation of yield, cessation of growth in Winter, flowering and post-anthesis growth. During flowering and pod set, the relation between source and sink regulates the availability of assimilates necessary for seed filling. The most source-limiting process is related to small photosynthetically active area, caused by a drastic decline in the leaf area index from the start of flowering despite a slow increase in the assimilating pod area. To analyse yield, it is necessary to understand the structure of the yield and the primary and secondary components, which determine seed yield. Plant density governs the components of yield and, thus, the yield of individual plants. A uniform distribution of plants per unit area is a prerequisite for yield stability. The number of pods per plant is decisive for seed yield; this trait is ultimately determined by the survival of branches, buds, flowers and young pods rather than by the potential number of flowers and pods. Seed number per pod is correlated with pod length. It is, therefore, concluded that pod length is a suitable trait for indirect selection in plant breeding.
Bruce D L Fitt - One of the best experts on this subject based on the ideXlab platform.
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Effects of a penthiopyrad and picoxystrobin fungicide mixture on phoma stem canker (Leptosphaeria spp.) on UK Winter Oilseed rape
European Journal of Plant Pathology, 2016Co-Authors: Thomas R Sewell, Steven Moloney, Mike Ashworth, Faye Ritchie, Alla Mashanova, Henrik U. Stotz, Yongju Huang, Bruce D L FittAbstract:In the UK, fungicides are often used to control phoma stem canker on Winter Oilseed rape. Field trials were established near Boxworth, Cambridgeshire for four cropping seasons (2011/2012, 2012/2013, 2013/2014 and 2014/15) to test the efficacy of a new fungicide mixture Refinzar® (penthiopyrad + picoxystrobin) by comparison to an existing fungicide Proline 275® (prothioconazole) against phoma stem canker (Leptosphaeria spp.) and the effect on Winter Oilseed rape (cv. Catana) yield. In each season, weather data were collected from a weather station at Boxworth and the release of ascospores was monitored using a nearby Burkard spore sampler. The patterns of ascospore release differed between seasons and related to weather conditions. Fungicides penthiopyrad + picoxystrobin and prothioconazole were applied in October/November when 10 % of plants had phoma leaf spotting (T1, early), 4/8 weeks after T1 (T2, late) or at both T1 and T2 (combined). When phoma leaf spot symptoms were assessed in autumn/Winter, penthiopyrad + picoxystrobin and prothioconazole both decreased numbers of phoma leaf spots caused by L. maculans; there were few leaf spots caused by L. biglobosa. Penthiopyrad + picoxystrobin and prothioconazole both reduced phoma stem canker severity before harvest compared to the untreated control but did not increase yield in these seasons when epidemics were not severe. In 2013/2014, the presence of L. maculans and L. biglobosa in upper stem lesions or stem base cankers was determined by species-specific PCR. The proportions of stems with L. maculans DNA were much greater than those with L. biglobosa DNA for both upper stem lesions and basal stem cankers. These results suggest that both penthiopyrad + picoxystrobin and prothioconazole can decrease phoma stem canker severity on Winter Oilseed rape in severe disease seasons.
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adaptation to increasing severity of phoma stem canker on Winter Oilseed rape in the uk under climate change
The Journal of Agricultural Science, 2010Co-Authors: Andrew Barnes, Neal Evans, Anita Wreford, Michael H Butterworth, Mikhail A Semenov, Dominic Moran, Bruce D L FittAbstract:Various adaptation strategies are available that will minimize or negate predicted climate change-related increases in yield loss from phoma stem canker in UK Winter Oilseed rape (OSR) production. A number of forecasts for OSR yield, national production and subsequent economic values are presented, providing estimates of impacts on both yield and value for different levels of adaptation. Under future climate change scenarios, there will be increasing pressure to maintain yields at current levels. Losses can be minimized in the short term (up to the 2020s) with a ‘low’-adaptation strategy, which essentially requires some farmer-led changes towards best management practices. However, the predicted impacts of climate change can be negated and, in most cases, improved upon, with ‘high’-adaptation strategies. This requires increased funding from both the public and private sectors and more directed efforts at adaptation from the producer. Most literature on adaptation to climate change has had a conceptual focus with little quantification of impacts. It is argued that quantifying the impacts of adaptation is essential to provide clearer information to guide policy and industry approaches to future climate change risk.
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relationships between phoma leaf spot and development of stem canker leptosphaeria maculans on Winter Oilseed rape brassica napus in southern england
Annals of Applied Biology, 2000Co-Authors: Bruce D L Fitt, Peter Gladders, S J WelhamAbstract:Models were constructed to describe the relationships between incidence of phoma leaf spot at different growth stages in autumn/Winter or early spring and incidence of stem canker (basal canker or stem lesions) in summer on Winter Oilseed rape in southern England. Model 1, describing the phoma leaf spot/basal canker relationship, was y(1) = beta (0) + beta (1)x(1) + beta (2)(x(2) - x(1)) if x(2) > x(1), and y(1) = beta (0) + beta (0) + beta (1)x(1) if x(2) less than or equal to x(1), in which y(1) was the incidence (Ic plants affected) of basal canker at harvest,x(1) was the maximum incidence of phoma leaf spot during the period from sowing to growth stage (G.S.) 1,6-1,7 (about 100 days after sowing) and x(2) was the maximum incidence of phoma leaf spot between G.S. 1,7 and G.S. 2,0 (start of stem extension). Model 2, describing the phoma leaf spot/stem lesion relationship, was y(2) = alpha (0) + alpha (1)x(3) + alpha (2)x(4), in which y(2) was the incidence of stem lesions at harvest, x(3) was the incidence of phoma leaf spot at G.S. 3,3-3,5 (flower buds visible) and x(4) was the incidence of phoma leaf spot at G.S. 4,5-5,5 (flower buds opening). Data from field experiments with four Winter Oilseed rape cultivars at Boxworth or Rothamsted in the 1992/93, 1993/94, 1996/97, 1997/98 or 1998/99 seasons were used to test the models. The values of R-2 for the regression equations testing model 1 for the phoma leaf spot/basal canker relationship were 0.75, 0.93, 0.91 and 0.89 for cvs Apex, Bristol, Capitol and Envol, respectively. The values of R-2 for the regression equations testing model 2 for the phoma leaf spot/stem lesion relationship were 0.58, 0.57, 0.54 and 0.71 for cvs Apex, Bristol, Capitol and Envol, respectively. The phoma leaf spot/basal canker relationship (model 1) could also be fitted to the combined data set for all four cultivars (R-2 = 0.65), whereas the phoma leaf spot/stem lesion relationship (model 2) could not to be fitted to the combined data set for the four cultivars. The relationships between incidence and severity of stem canker were examined and the values of R-2 for the regressions of severity on incidence were 0.91 for basal canker and 0.89 for stern lesions.
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Epidemiology in Relation to Methods for Forecasting Light Leaf Spot (Pyrenopeziza brassicae) Severity on Winter Oilseed Rape (Brassica napus) in the UK
European Journal of Plant Pathology, 2000Co-Authors: Tijs Gilles, Bruce D L Fitt, Neal Evans, Michael J. JegerAbstract:Pyrenopeziza brassicae , cause of light leaf spot of Oilseed rape, has a complex polycyclic life cycle. It can be difficult to control light leaf spot in Winter Oilseed rape in the UK since it is not easy to optimise fungicide application timing. Early autumn infections are usually symptomless and recognisable lesions do not develop until the epidemic has progressed further by the spring. Light leaf spot often has a patchy distribution in Winter Oilseed rape crops and estimation of disease incidence can be difficult. There is evidence that epidemics are initiated primarily by ascospores produced from apothecia that survive the summer inter-crop period on infected debris. Subsequent development of the epidemic during the Winter and spring is maintained by rain-splashed conidia that spread light leaf spot from initial foci. Understanding the relative roles of ascospores and conidia in the light leaf spot life cycle is crucial for forecasting epidemic severity and developing control strategies. The current web-based regional forecast system provides an autumn forecast of the incidence of light leaf spot that can be expected the following spring. This is based on survey data which assesses the occurrence of disease the previous July, and weather factors, such as deviations from summer mean temperature and Winter rainfall. The forecast can be updated throughout the autumn and Winter and includes crop-specific elements so that growers can adjust risks by inputting information about cultivar, sowing date and fungicide use. Crop-specific forecasts can be confirmed by assessing the incidence of light leaf spot. Such assessments will become easier when immunodiagnostic methods for detection of the disease become available. Incorporation of information on spore biology (e.g. apothecial maturation, ascospore release and infection conditions) is considered as a component of the interactive, continuously updated, crop-specific, web-based forecasts which are needed in the future.
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Epidemiology of Leptosphaeria maculans in relation to forecasting stem canker severity on Winter Oilseed rape in the UK
Annals of Applied Biology, 1999Co-Authors: Jon S. West, J.e. Biddulph, Bruce D L Fitt, Peter GladdersAbstract:SUMMARY In the UK, ascospores of Leptosphaeria maculans first infect leaves of Oilseed rape in the autumn to cause phoma leaf spots, from which the fungus can grow to cause stem cankers in the spring. Yield losses due to early senescence and lodging result if the stem cankers become severe before harvest. The risk of severe stem canker epidemics needs to be forecast in the autumn when the pathogen is still in the leaves, since early infections cause the greatest yield losses and fungicides have limited curative activity. Currently, the most effective way to forecast severe stem canker is to monitor the onset of phoma leaf spotting in Winter Oilseed rape crops, although this does not allow much time in which to apply a fungicide. Early warnings of risks of severe stem canker epidemics could be provided at the beginning of the season through regional forecasts based on disease survey and weather data, with options for input of crop-specific information and for updating forecasts during the Winter. The accuracy of such forecasts could be improved by including factors relating to the maturation of ascospores in pseudothecia, the release of ascospores and the occurrence of infection conditions, as they affect the onset, intensity and duration of the phoma leaf spotting phase. Accurate forecasting of severe stem canker epidemics can improve disease control and optimise fungicide use.
Jiahui Han - One of the best experts on this subject based on the ideXlab platform.
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estimation and mapping of Winter Oilseed rape lai from high spatial resolution satellite data based on a hybrid method
Remote Sensing, 2017Co-Authors: Chuanwen Wei, Jingfeng Huang, Lamin R Mansaray, Weiwei Liu, Jiahui HanAbstract:Leaf area index (LAI) is a key input in models describing biosphere processes and has widely been used in monitoring crop growth and in yield estimation. In this study, a hybrid inversion method is developed to estimate LAI values of Winter Oilseed rape during growth using high spatial resolution optical satellite data covering a test site located in southeast China. Based on PROSAIL (coupling of PROSPECT and SAIL) simulation datasets, nine vegetation indices (VIs) were analyzed to identify the optimal independent variables for estimating LAI values. The optimal VIs were selected using curve fitting methods and the random forest algorithm. Hybrid inversion models were then built to determine the relationships between optimal simulated VIs and LAI values (generated by the PROSAIL model) using modeling methods, including curve fitting, k-nearest neighbor (kNN), and random forest regression (RFR). Finally, the mapping and estimation of Winter Oilseed rape LAI using reflectance obtained from Pleiades-1A, WorldView-3, SPOT-6, and WorldView-2 were implemented using the inversion method and the LAI estimation accuracy was validated using ground-measured datasets acquired during the 2014–2015 growing season. Our study indicates that based on the estimation results derived from different datasets, RFR is the optimal modeling algorithm amidst curve fitting and kNN with R2 > 0.954 and RMSE <0.218. Using the optimal VIs, the remote sensing-based mapping of Winter Oilseed rape LAI yielded an accuracy of R2 = 0.520 and RMSE = 0.923 (RRMSE = 93.7%). These results have demonstrated the potential operational applicability of the hybrid method proposed in this study for the mapping and retrieval of Winter Oilseed rape LAI values at field scales using multi-source and high spatial resolution optical remote sensing datasets. Details provided by this high resolution mapping cannot be easily discerned at coarser mapping scales and over larger spatial extents that usually employ lower resolution satellite images. Our study therefore has significant implications for field crop monitoring at local scales, providing relevant data for agronomic practices and precision agriculture.
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mapping above ground biomass of Winter Oilseed rape using high spatial resolution satellite data at parcel scale under waterlogging conditions
Remote Sensing, 2017Co-Authors: Jiahui Han, Chuanwen Wei, Weiwei Liu, Yaoliang Chen, Peilin Song, Dongdong Zhang, Anqi Wang, Xiaodong Song, Xiuzhen Wang, Jingfeng HuangAbstract:Oilseed rape (Brassica napus L.) is one of the three most important oil crops in China, and is regarded as a drought-tolerant Oilseed crop. However, it is commonly sensitive to waterlogging, which usually refers to an adverse environment that limits crop development. Moreover, crop growth and soil irrigation can be monitored at a regional level using remote sensing data. High spatial resolution optical satellite sensors are very useful to capture and resist unfavorable field conditions at the sub-field scale. In this study, four different optical sensors, i.e., Pleiades-1A, Worldview-2, Worldview-3, and SPOT-6, were used to estimate the dry above-ground biomass (AGB) of Oilseed rape and track the seasonal growth dynamics. In addition, three different soil water content field experiments were carried out at different Oilseed rape growth stages from November 2014 to May 2015 in Northern Zhejiang province, China. As a significant indicator of crop productivity, AGB was measured during the seasonal growth stages of the Oilseed rape at the experimental plots. Several representative vegetation indices (VIs) obtained from multiple satellite sensors were compared with the simultaneously-collected Oilseed rape AGB. Results showed that the estimation model using the normalized difference vegetation index (NDVI) with a power regression model performed best through the seasonal growth dynamics, with the highest coefficient of determination (R2 = 0.77), the smallest root mean square error (RMSE = 104.64 g/m2), and the relative RMSE (rRMSE = 21%). It is concluded that the use of selected VIs and high spatial multiple satellite data can significantly estimate AGB during the Winter Oilseed rape growth stages, and can be applied to map the variability of Winter Oilseed rape at the sub-field level under different waterlogging conditions, which is very promising in the application of agricultural irrigation and precision agriculture.
Jingfeng Huang - One of the best experts on this subject based on the ideXlab platform.
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estimation and mapping of Winter Oilseed rape lai from high spatial resolution satellite data based on a hybrid method
Remote Sensing, 2017Co-Authors: Chuanwen Wei, Jingfeng Huang, Lamin R Mansaray, Weiwei Liu, Jiahui HanAbstract:Leaf area index (LAI) is a key input in models describing biosphere processes and has widely been used in monitoring crop growth and in yield estimation. In this study, a hybrid inversion method is developed to estimate LAI values of Winter Oilseed rape during growth using high spatial resolution optical satellite data covering a test site located in southeast China. Based on PROSAIL (coupling of PROSPECT and SAIL) simulation datasets, nine vegetation indices (VIs) were analyzed to identify the optimal independent variables for estimating LAI values. The optimal VIs were selected using curve fitting methods and the random forest algorithm. Hybrid inversion models were then built to determine the relationships between optimal simulated VIs and LAI values (generated by the PROSAIL model) using modeling methods, including curve fitting, k-nearest neighbor (kNN), and random forest regression (RFR). Finally, the mapping and estimation of Winter Oilseed rape LAI using reflectance obtained from Pleiades-1A, WorldView-3, SPOT-6, and WorldView-2 were implemented using the inversion method and the LAI estimation accuracy was validated using ground-measured datasets acquired during the 2014–2015 growing season. Our study indicates that based on the estimation results derived from different datasets, RFR is the optimal modeling algorithm amidst curve fitting and kNN with R2 > 0.954 and RMSE <0.218. Using the optimal VIs, the remote sensing-based mapping of Winter Oilseed rape LAI yielded an accuracy of R2 = 0.520 and RMSE = 0.923 (RRMSE = 93.7%). These results have demonstrated the potential operational applicability of the hybrid method proposed in this study for the mapping and retrieval of Winter Oilseed rape LAI values at field scales using multi-source and high spatial resolution optical remote sensing datasets. Details provided by this high resolution mapping cannot be easily discerned at coarser mapping scales and over larger spatial extents that usually employ lower resolution satellite images. Our study therefore has significant implications for field crop monitoring at local scales, providing relevant data for agronomic practices and precision agriculture.
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mapping above ground biomass of Winter Oilseed rape using high spatial resolution satellite data at parcel scale under waterlogging conditions
Remote Sensing, 2017Co-Authors: Jiahui Han, Chuanwen Wei, Weiwei Liu, Yaoliang Chen, Peilin Song, Dongdong Zhang, Anqi Wang, Xiaodong Song, Xiuzhen Wang, Jingfeng HuangAbstract:Oilseed rape (Brassica napus L.) is one of the three most important oil crops in China, and is regarded as a drought-tolerant Oilseed crop. However, it is commonly sensitive to waterlogging, which usually refers to an adverse environment that limits crop development. Moreover, crop growth and soil irrigation can be monitored at a regional level using remote sensing data. High spatial resolution optical satellite sensors are very useful to capture and resist unfavorable field conditions at the sub-field scale. In this study, four different optical sensors, i.e., Pleiades-1A, Worldview-2, Worldview-3, and SPOT-6, were used to estimate the dry above-ground biomass (AGB) of Oilseed rape and track the seasonal growth dynamics. In addition, three different soil water content field experiments were carried out at different Oilseed rape growth stages from November 2014 to May 2015 in Northern Zhejiang province, China. As a significant indicator of crop productivity, AGB was measured during the seasonal growth stages of the Oilseed rape at the experimental plots. Several representative vegetation indices (VIs) obtained from multiple satellite sensors were compared with the simultaneously-collected Oilseed rape AGB. Results showed that the estimation model using the normalized difference vegetation index (NDVI) with a power regression model performed best through the seasonal growth dynamics, with the highest coefficient of determination (R2 = 0.77), the smallest root mean square error (RMSE = 104.64 g/m2), and the relative RMSE (rRMSE = 21%). It is concluded that the use of selected VIs and high spatial multiple satellite data can significantly estimate AGB during the Winter Oilseed rape growth stages, and can be applied to map the variability of Winter Oilseed rape at the sub-field level under different waterlogging conditions, which is very promising in the application of agricultural irrigation and precision agriculture.
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assessing Winter Oilseed rape freeze injury based on chinese hj remote sensing data
Journal of Zhejiang University-science B, 2015Co-Authors: Bao She, Jingfeng Huang, Ruifang Guo, Hongbin Wang, Jing WangAbstract:The Winter Oilseed rape (Brassica napus L.) accounts for about 90% of the total acreage of Oilseed rape in China. However, it suffers the risk of freeze injury during the Winter. In this study, we used Chinese HJ-1A/1B CCD sensors, which have a revisit frequency of 2 d as well as 30 m spatial resolution, to monitor the freeze injury of Oilseed rape. Mahalanobis distance-derived growing regions in a normal year were taken as the benchmark, and a mask method was applied to obtain the growing regions in the 2010–2011 growing season. The normalized difference vegetation index (NDVI) was chosen as the indicator of the degree of damage. The amount of crop damage was determined from the difference in the NDVI before and after the freeze. There was spatial variability in the amount of crop damage, so we examined three factors that may affect the degree of freeze injury: terrain, soil moisture, and crop growth before the freeze. The results showed that all these factors were significantly correlated with freeze injury degree (P<0.01, two-tailed). The damage was generally more serious in low-lying and drought-prone areas; in addition, Oilseed rape planted on south- and west-oriented facing slopes and those with luxuriant growth status tended to be more susceptible to freeze injury. Furthermore, land surface temperature (LST) of the coldest day, soil moisture, pre-freeze growth and altitude were in descending order of importance in determining the degree of damage. The findings proposed in this paper would be helpful in understanding the occurrence and severity distribution of Oilseed rape freeze injury under certain natural or vegetation conditions, and thus help in mitigation of this kind of meteorological disaster in southern China.
Tao Ren - One of the best experts on this subject based on the ideXlab platform.
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assessing leaf nitrogen concentration of Winter Oilseed rape with canopy hyperspectral technique considering a non uniform vertical nitrogen distribution
Industrial Crops and Products, 2018Co-Authors: Balint Jakli, Tao Ren, Shishi Liu, Jin Ming, Shanqin WangAbstract:Abstract Timely estimation of the vertical heterogeneity of leaf nitrogen concentration (LNC) from canopy reflectance using hyperspectral sensing is important for precision N management during Winter Oilseed rape productivity. However, current research pays little attention to LNC assessments by only taking LNC’s vertical distribution into consideration, leading to limited accuracy and reduced applied value of the results. The main goal of this work was to quantitatively define the contributions of LNC in different layers to Winter Oilseed rape canopy raw (R) hyperspectra and to its transformation technique (i.e., first derivative reflectance, FDR), and develop a monitoring model considering the vertical LNC gradient using spectral data. Two field experiments were conducted for two consecutive years (2015–2017) with different N rates, cultivars and growth stages. At seedling and budding stage, canopy hyperspectral reflectance and LNC were measured in situ. Canopies of each treatment were divided into three layers of equal vertical (upper, middle, lower). Partial least square (PLS), lambda-lambda r2 (LL r2) and support vector machine (SVM) models were used to analyze the relationships between LNC in different layers and the hyperspectral reflectance measured from above the canopy. Field sampling revealed that a vertical distribution pattern of LNC existed, presenting an evident decline from the upper to lower layer. The FDR-PLS model for LNC prediction in different layers yielded a relatively higher accuracy compared to the R-PLS based on the full range hyperspectra, the coefficient of determination (r2 val) was 0.872 for LNC in the upper layer, 0.903 in the middle layer, and 0.837 in the lower layer, with a relative percent deviation (RPD val) of 2.794, 3.052, and 2.328, respectively. Finally, seven (437, 565, 667, 724, 993, 1084 and 1189 nm), six (423, 570, 598, 659, 725 and 877 nm), and five bands (420, 573, 597, 667 and 718 nm) were identified as effective wavelengths for assessing the vertical LNC distribution in the upper, middle and lower layer, respectively. The newly-developed SVM-FDR regression model using the effective wavelengths also performed well for upper (r2 val = 0.828, RPD val = 2.358), middle (r2 val = 0.844, RPD val = 2.556), and lower (r2 val = 0.781, RPD val = 2.029) layer LNC prediction. Our results indicate that estimation of LNC using hyperspectral reflectance data is most effective for the upper and middle layers of Oilseed rape canopies. Moreover, the calibration model developed in this study has great potential to assess the N status of the whole Oilseed rape canopy.
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storage nitrogen co ordinates leaf expansion and photosynthetic capacity in Winter Oilseed rape
Journal of Experimental Botany, 2018Co-Authors: Tao Liu, Tao Ren, Philip J White, Rihuan CongAbstract:Storage nitrogen (N) is a buffer pool for maintaining leaf growth and synthesizing photosynthetic proteins, but the dynamics of its forms within the life cycle of a single leaf and how it is influenced by N supply remain poorly understood. A field experiment was conducted to estimate the influence of N supply on leaf growth, photosynthetic characteristics, and N partitioning inthe sixth leaf of Winter Oilseed rape (Brassica napus L.) from emergence through senescence. Storage N content (Nstore) decreased gradually along with leaf expansion. The relative growth rate based on leaf area (RGRa) was positively correlated with Nstore during leaf expansion. The water-soluble protein form of storage N was the main N source for leaf expansion. After the leaves fully expanded, the net photosynthetic rate (An) followed a linear-plateau response to Nstore, with An stabilizing at the highest value above a threshold and declining below the threshold. Non-protein and SDS (detergent)-soluble protein forms of storage N were the main N sources for maintaining photosynthesis. For the leaf N economy, storage N is used for co-ordinating leaf expansion and photosynthetic capacity. N supply can improve Nstore, thereby promoting leaf growth and biomass.
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ability of models with effective wavelengths to monitor nitrogen and phosphorus status of Winter Oilseed rape leaves using in situ canopy spectroscopy
Field Crops Research, 2018Co-Authors: Shanqin Wang, Tao Ren, Quanquan Wei, Jin Ming, Rihuan CongAbstract:Abstract Till date, studies using canopy hyperspectral data to monitor crop nutrient status have focused mainly on biomass, water and nitrogen (N) prediction, and only a few have attempted to monitor phosphorus (P). This study aimed to evaluate the potential of the canopy raw spectra (R) in combination with a partial least square (PLS) regression model for estimating the leaf N and P concentration (LNC and LPC), compared to the potential of other hyperspectral transformation techniques such as log-transformed spectra (Log(1/R)), the continuum removal (CR) method and first derivative reflectance (FDR) for Winter Oilseed rape. Field experiments were conducted over three consecutive growing seasons (2013–2016) at different sites (Wuxue, Wuhan and Shayang) in Hubei, China, using different N and P application rates, planting patterns, cultivars and ecological sites. Data from the conventionally managed fields of 25 farmers in 2015–2016 were also collected to test the transferability of the established optimal monitoring model for LNC and LPC prediction. Canopy hyperspectral reflectance data were acquired over a wavelength range from 400 to1300 nm (the visible and near-infrared region, VNIR), and quantitative correlations between LNC and LPC and their spectra were determined. The results showed that the FDR-PLS model yielded the highest retrieval accuracy for LNC and LPC predictions. The coefficient of determination of the validation dataset (r2val) between the observations and predictions was 0.89 for LNC and 0.82 for LPC, with a relative percent deviation (RPDval) of 2.41 and 2.22, respectively. The variable importance in projection (VIP) values of the FDR-PLS model with full spectral range were applied to identify the effective wavelengths and to decrease the high dimensionality of the canopy hyperspectral reflectance dataset. Seven wavelengths centred at 445, 556, 657, 764, 985, 1082, and 1194 nm and six wavelengths at 755, 832, 891, 999, 1196, and 1267 nm were identified as effective wavelengths for predicting the LNC and LPC values. The newly-developed FDR-PLS models for LNC (r2val = 0.85, RPDval = 2.10) and LPC (r2val = 0.78, RPDval = 1.94) provided accurate estimations based on field experiment validations using the effective wavelengths. The validation in the farmers’ fields also indicated an excellent accuracy between the observed and predicted values for LNC (r2val = 0.82, RPDval = 2.09) and LPC (r2val = 0.75, RPDval = 2.01). The overall results demonstrated the applicability and feasibility of the FDR-PLS model for estimating the N and P status of Winter Oilseed rape using in situ canopy hyperspectral reflectance data.
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methods for estimating leaf nitrogen concentration of Winter Oilseed rape brassica napus l using in situ leaf spectroscopy
Industrial Crops and Products, 2016Co-Authors: Shanqin Wang, Rihuan Cong, Quanquan Wei, Tao RenAbstract:Abstract Accurate and nondestructive assessment of leaf nitrogen (N) nutritional status is important for site-specific N management in Winter Oilseed rape production. To develop a method for determining leaf N concentration (LNC) in Oilseed rape, a field experiment with different N fertilizer levels was conducted in two successive years by measuring leaf spectral reflectance (400⿿1300 nm) and LNC at varying developmental stages. A partial least square (PLS) regression analysis was performed with four spectral methods: (i) the raw spectral reflectance (R), (ii) inverse-log reflectance data (log(1/R)), (iii) continuum removal (CR) method and (iv) first derivative reflectance (FDR). The results indicated that LNC and leaf reflectance significantly varied with the levels of N fertilization, and a good correlation was observed for all the spectral methods. Using a calibration dataset, the best results were obtained with the FDR-PLS method, which yielded the highest coefficient of determination (r 2 cal ) of 0.963, the ratio prediction to deviation (RPD cal ) of 5.207, and the lowest root mean square error (RMSE cal ) of 0.294. Tests with the independent validation dataset also showed that the FDR-PLS method could well predict LNC in Oilseed rape, with the values of r 2 val , RPD val , and RMSE val being 0.966, 5.488 and 0.276, respectively. The variable importance in projection (VIP) scores resulting from this PLS regression analysis were used to determine the effective wavelengths and reduce the dimensionality of the spectral reflectance data. The newly-developed FDR-PLS model using the effective wavelengths (432, 467, 519, 614, 772, 912 and 1072 nm) performed well in LNC prediction with r 2 val = 0.884, RPD val = 2.971 and RMSE val = 0.508. The overall results indicate that the LNC of Winter Oilseed rape could be reliably estimated with the in situ developed FDR-PLS method in this study.
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evaluating chlorophyll density in Winter Oilseed rape brassica napus l using canopy hyperspectral red edge parameters
Computers and Electronics in Agriculture, 2016Co-Authors: Tao Ren, Rihuan Cong, Shanqin Wang, Quanquan Wei, Shishi LiuAbstract:Novel red-edge area indices for evaluating chlorophyll density (ChD) were developed.Optimal red-edge spectral parameters (ORSPs) were characterized and determined.Noise Equivalent (NE) model was used to evaluate the sensitivity of the ORSPs.The novel ORSPs enhances ChD estimation from hyperspectral reflectance data. Accurate assessments of chlorophyll density (ChD) using hyperspectral techniques are important for effective evaluation of plant productivity and precise nitrogen (N) management in Winter Oilseed rape. To develop a quantitative estimation model for determining ChD in Winter Oilseed rape, field experiments with different N fertilizer levels were conducted over two successive years by measuring canopy hyperspectral reflectance and ChD at various developmental stages. The relationships between two types of parameters (existing red-edge spectral parameters and newly-developed red-edge area parameters) and ChD were investigated to determine the optimal red-edge spectral parameters (ORSPs) for ChD predictions. The Noise Equivalent (NE) model was adopted to evaluate the sensitivity and accuracy of the ORSPs for detecting changes in ChD across different growth stages. The results indicated that canopy hyperspectral reflectance and its first derivative spectra significantly varied with the levels of N fertilization. A strong correlation also existed between canopy reflectance data and ChD. Using a training dataset, the best results for assessing ChD status were observed when using the newly-developed red-edge area parameter, which indicated a difference between the double-peak areas based on the position of the main peak (DIDRmid). DIDRmid was the ORSP and exhibited a significant exponential relationship with ChD, with a coefficient of determination (R2) of 0.88 and a standard error (SE) of 0.312. Tests conducted on the independent validation dataset showed that DIDRmid can be used to accurately predict ChD in Oilseed rape, with a relative root mean square error (RRMSE) of 0.091 and a mean relative error (MRE) of 7.22%. Additionally, this ORSP also had relatively lower NE values and higher sensitivity and accuracy with respect to ChD estimation. Consequently, the ChD of Winter Oilseed rape can be stably estimated with the hyperspectral red-edge methods established in this study because the newly-developed red-edge area spectral parameter was effective and accurate in evaluating ChD.
