Autumn-based vegetation indices for estimating nitrate leaching during autumn and winter in arable cropping systems

Agriculture, Ecosystems and Environment 290 (2020) 106786

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Autumn-based vegetation indices for estimating nitrate leaching during autumn and winter in arable cropping systems

T

Jin Zhao*, Chiara De Notaris, Jørgen Eivind Olesen Department of Agroecology, Aarhus University, Blichers Allé 20, DK-8830 Tjele, Denmark

A R T I C LE I N FO

A B S T R A C T

Keywords: Vegetation index Cover crop Nitrate leaching Cropping system

Nitrate leaching losses from arable cropping systems cause severe damage to environmental services worldwide. There is a considerable need for methods that allow rapid, easy and area covering detection of nitrate leaching to guide nitrogen (N) management. We used three years of data from the 5th cycle of a long-term crop rotation experiment in Denmark to quantify the relationships between nitrate leaching in autumn and winter and field conditions in autumn as defined by three vegetation indices [VIs; Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), Ratio Red Edge (RRE)] in autumn. Following cereal crops, cover crops significantly reduced nitrate leaching in autumn and winter, whereas this was only the case for one out of the three years after faba bean. In autumn and winter, a negative relationship was found between nitrate leaching and cover crop aboveground biomass or aboveground N, and the thresholds were ∼2 Mg ha−1 for aboveground cover crop biomass and 60 kg N ha−1 for aboveground cover crop N, above which nitrate leaching was low and stable. A significant positive linear relationship was found between nitrate leaching and soil water nitrate concentration in autumn and winter with a slope of 4.0 kg N ha−1 per mg L−1 of nitrate-N in the soil. Although all three VIs showed significant negative relationships with nitrate leaching during autumn and winter, the sensitivities of RVI and NDVI to estimated nitrate leaching were lost sharply when nitrate leaching exceeded 100 kg N ha−1 and 50 kg N ha−1, while RRE exhibited consistent low noise equivalent values for the nitrate leaching in autumn and winter. These results provide evidence for the scope of assessing risk of nitrate leaching from agricultural soils based on newly launched satellite remote sensing platforms with NDVI and red edge bands. To maximize the application of these technologies it will be necessary to combine remote sensing with information on cropping systems and biophysical conditions.

1. Introduction Nitrogen (N) fertilization is an indispensable agricultural practice all around the world, serving the survival of half of the global population (Zamanian et al., 2018), for N is essential for crop growth (Dinnes et al., 2002). However, a considerable portion of agricultural N application is lost to the environment, potentially severely damaging the environment (Dobermann and Cassman, 2005; Erisman et al., 2008; Galloway et al., 2008). In arable cropping systems, large amounts of N that remain in soil or are mineralized after harvest may be leached before the next crop is established. Therefore, N leaching in cultivated lands has caused much concern worldwide due to globally declining N fertilizer use efficiency (NUE) and, more seriously, due to contamination of both groundwater and surface waters (Vos and Putten, 1997; Yang et al., 2015). In Northern Europe, surplus precipitation during winter often induces considerable amounts of N leaching to the

⁎

environment (Pedersen et al., 2009). In particular, the N pollution pressure from agriculture has been severe in Denmark (Dalgaard et al., 2014). Nitrate leaching mainly depends on vegetation cover and field management in autumn (Askegaard et al., 2005, 2011). Cover crops (or catch crops) are grown after the main crop to take up and retain surplus mineral soil N that would otherwise be leached from the root zone (Thorup-Kristensen et al., 2003). Additionally, the N retained by cover crops is mainly returned to the surface soil layer when it is killed, either during winter frost or by spring tillage, acting as fertilizer for the following crop. In this way, cover crops during the fallow periods change the annual patterns of N uptake and mineralization, reduce downward movement of N, retrieve N from deep soil layers, and fix atmospheric N2, if the cover crops are legume-based (Kaspar and Singer, 2011). A meta-analysis has documented that non-legumes used as cover crops (e.g. ryegrass, winter rye, and fodder radish) reduce N leaching by 70 %

Corresponding author. E-mail address: [email protected] (J. Zhao).

https://doi.org/10.1016/j.agee.2019.106786 Received 8 May 2019; Received in revised form 27 November 2019; Accepted 29 November 2019 0167-8809/ © 2019 Elsevier B.V. All rights reserved.

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strategies. The main objectives were 1) to quantify the relationships between nitrate leaching in autumn and winter and field conditions in autumn (i.e., cover crop biomass and N uptake); 2) using VIs in autumn to explore the relations to soil nitrate N concentration and nitrate leaching in autumn and winter.

compared with bare fallow on average (Tonitto et al., 2006). Besides, cover crops may also provide a range of other benefits, such as reducing soil erosion and related nutrient losses (Dabney, 1998) and improving soil structural quality (Bronick and Lal, 2005). Because of the strong effect of cover crops on N leaching, countries such as Denmark promote the use of cover crops as a key element to not only reduce N leaching, but also increase N retention and crop N supply (Dalgaard et al., 2014; Pandey et al., 2018). The different efficiencies of cover crops to retain mineral N depend on many factors (Vos and Putten, 1997; Sapkota et al., 2012). For example, cover crops with varying growth patterns have to be undersown in cereals and may compete with the main crop and thus reduce main crop yield (Munkholm and Hansen, 2012; Valkama et al., 2015). Therefore, it is crucial to choose the optimal species and cultivars of cover crop for a specific cropping system (Munkholm and Hansen, 2012). Ideally cover crops should have a positive effect on the N balance of cropping system, while reducing N leaching and fertilizer N application (Thorup-Kristensen and Dresbøll, 2010). In another metaanalysis, non-legume cover crops were reported to reduce N leaching loss by 50 % on average, but legumes did not decrease the leaching risk (Valkama et al., 2015). However, legume-based cover crops can provide a green manuring service that increases N availability in the soil for the subsequent crop (Tribouillois et al., 2016), which is particularly valuable in organic arable cropping systems (Valkama et al., 2015; De Notaris et al., 2018). By having both legumes and non-legumes in the cover crop mixture, the provision of ecosystem services can by optimized, providing a green manuring service and reducing N leaching (Tribouillois et al., 2016; Couëdel et al., 2018; De Notaris et al., 2018; Vogeler et al., 2019). Traditional methods for measuring N leaching in cropping systems depend on plant and soil sampling from the field and analytic assay in the lab (Roth et al., 1989; Zhou et al., 2018). Although the results from these protocols are relatively reliable, the procedures are laborious and time-consuming (Zhu et al., 2008; Zhou et al., 2018). Remote sensing of vegetation indices (VIs), mainly performed by obtaining the light spectra reflectance from the vegetation canopy, has been used extensively in agriculture to determine crop growth and N status (Li et al., 2014; Xue and Su, 2017; Zhou et al., 2017). The advantage of canopy spectral reflectance stems from its ability to deliver instantaneous information on N status and guide N management (Scharf et al., 2011; Barker and Sawyer, 2012). Spectral reflectance-based N fertilization has proven an effective way to improve NUE (Raun et al., 2002; Evert et al., 2012; Nigon et al., 2014). Because N leaching from cropping systems are determined by plant growth and autumn field management (Askegaard et al., 2011), VIs could also be an effective way to estimate N leaching in cropping systems. However, few studies have addressed this issue (Fontes et al., 2019). In this study, three commonly used vegetation indices, Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), and Ratio Red Edge (RRE), were measured in the autumn during 3 years under different cropping systems and management

2. Materials and methods 2.1. Experiment location To study productivity and environmental impacts of different arable crop rotations and managements over a long period, a crop rotation experiment was initiated in 1997 at Foulum (56°30′N, 9°34′E), Denmark, using a randomized factorial design with two replicates (Olesen et al., 2000a,b). Currently, the study includes one conventional and two organic crop rotations, with and without of use of animal manure and cover crops. Previous studies have investigated the effect of different management strategies on nitrate leaching, one of the focus points of the experiment (Askegaard et al., 2005, 2011; Jabloun et al., 2015; De Notaris et al., 2018; Pandey et al., 2018). In particular, ceramic suction cups were installed in all plots in 2011, providing a unique source of information on the impacts of the main crops and cover crops on nitrate leaching. The current study is based on the first three years in the fifth cycle of the experiment (2015–2017). The soil is a sandy loam, with 78 % sand, 13 % silt and 9 % clay and a soil organic carbon (SOC) content of around 23 g kg−1 (Djurhuus and Olesen, 2000). In 2015 the average soil measured as pH (CaCl2+0.5) was 6.0, and the carbon content in the topsoil (25 cm) was 14.4 g kg−1. 2.2. Experiment design and management In this crop rotation experiment, three cropping systems were included: organic rotation with grass-clover (OGM, O2), organic rotation with grain legume (OGL, O4), and conventional rotation with grain legume (CGL, C4). The main crop sequence was the same in OGL and CGL systems: spring barley (Hordeum vulgare L.), faba bean (Vicia faba L.), spring wheat (Triticum aestivum L.), and spring oats (Avena sativa L.). In OGM, grass-clover, a mixture of perennial ryegrass (Lolium perenne L.), white clover (Trifolium repens L.) and red clover (Trifolium pretense L.), was undersown in spring barley and kept on the field for the following year. All four crops in the crop rotations were represented each year in two replicates. In 2015, the harvest dates of spring wheat, spring barley, oat, and faba bean were 8 Sept., 9 Sept., 9 Sept., and 29 Sept., respectively, which were 25 Aug., 17 Aug., 17 Aug., and 13 Sept. in 2016 and 29 Aug., 17 Aug., 23 Aug., and 25 Sept. in 2017. The crop sequences in the plots from 2015 to 2017 are listed in Table 1. In the two organic systems (OGM and OGL), treatment factors were the use of animal manure (+/–M) and legume-based cover crops (+/−CC), resulting in three treatments: +M/−CC, +M/+CC, and –M/+CC. In the conventional systems (CGL), the plots were

Table 1 Main crop sequence during the fifth cycle of the experiment (2015–2017). Cropping system OGM

OGL/CGL

Field 1 2 3 4 1 2 3 4

2015 cc

Oat Grass-clover S.wheatcc S.barley:grass-clover S.barleycc S.wheatcc Oatcc Faba beancc

2016

2017

S.barley: grass-clover S.wheatcc Oatcc Grass-clover Faba beancc Oatcc S.barleycc S.wheatcc

Grass-clover Oatcc S.barley: grass-clover S.wheatcc S.wheatcc S.barleycc Faba beancc Oatcc

OGM = organic with green manure; OGL = organic with grain legume; CGL = conventional with grain legume; S.=spring; GM = green manure; cc = cover crop (indicates cc were established following this main crop in the rotation in + CC treatments). 2

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2.5. Canopy spectral reflectance

characterized by use of mineral fertilizers (F) and non-legume cover crops (+/−CC), for a total of two treatments: +F/+CC and + F/ −CC. In the organic systems, plots under + M treatment received anaerobically digested animal manure, while plots under –M treatment received Patentkali®, a potash fertilizer suitable for organic farming containing 30 % K2O, 10 % MgO and 43 % SO3 in water-soluble forms. In the conventional system, crops were fertilized with mineral nitrogen (N), phosphorus (P), potassium (K) and sulphur (S). Nitrogen was applied at rates according to Danish national standards. In the current study, we considered different cases of vegetation in autumn, in particular with and without cover crops (+/−CC). In OGM, grass-clover was undersown in spring barley and performed as a cover crop during autumn; therefore, results of these plots were grouped in + CC treatments. Additionally, grass-clover was treated as a separate case in the analysis, and grass-clover cuttings were removed in the + M treatment, but returned as surface mulch in the –M treatment (De Notaris et al., 2018). Cover crop consisted of perennial ryegrass, chicory (Chicorium intybus L.), white clover and red clover undersown in the main crop in May in OGM and OGL. In CGL, the cover crop consisted of perennial ryegrass undersown in May or a mixture of fodder radish (Raphanus sativus L.) and winter rye (Secale cereale L.) sown shortly after harvest. In the following spring, cover crop biomass was always incorporated by ploughing before sowing of the main crop. In OGM and OGL, weeds were controlled mechanically, while pesticides were used in CGL.

Canopy spectral reflectance was measured before plant sampling in autumn by a RapidSCAN CS-45 instrument (Holland Scientific, Lincoln, NE, USA). The measurements were taken in each plot within the area where suction cups had been installed. The operator walked 20 m along the row direction with the instrument held by hand at about 1.2 m above the ground. The sensors measured crop/soil reflectance at 670 nm [red (R)], 730 nm [red edge (RE)], and 780 nm [near-infrared (NIR)] bands, respectively. Three commonly used VIs (RVI, NDVI, and RRE) were calculated by Eqs. (1)–(3):

NIR R

RVI=

NDVI=

RRE=

NIR − R NIR + R

NIR RE

(1) (2) (3)

2.6. Data analysis The aboveground biomass in autumn, plant N in autumn, and soil nitrate concentration in autumn and winter were compared among the three experimental years, and then, the effects of cropping system and treatment were analyzed separately for each year. The effects of treatment on final accumulated nitrate leaching during autumn and winter were analyzed separately for each main crop and each year. Statistical analysis was conducted using R 3.5.1 (R Core Team, 2018). Analysis of variance was conducted through mixed effects models using the function lmer from R package lme4 (Bates et al., 2015) to evaluate each factor. Mean values were compared using LSD.test function provided in the agricolae package (de Mendiburu, 2017) at the 5 % significance level. Linear and natural logarithmic regression models (4) and (5) were used to estimate the relationships among VIs in autumn, crop biomass and plant N concentration in autumn, and average soil nitrate concentration and nitrate leaching in autumn and winter.

2.3. Plant and soil water sampling in autumn and winter Aboveground biomass in autumn was measured by harvesting two 0.5 m2 subplots in each plot at 2 cm height. Grass-clover main crop plots were harvested on 24 Sept. 2015, 20 Sept. 2016, and 22 Sept. 2017. Plots under + CC treatment were harvested on 13 Nov. 2015, 25 Oct. 2016, and 23 Oct. 2017. Plots under −CC treatment were harvested on 16 Nov. 2015, 31 Oct. 2016, and 30 Oct. 2017. Plant samples were oven-dried (60 °C for 48 h) to a constant weight, and then finely milled for total N determination by the Dumas method (Hansen, 1989). Biomass and plant N were recorded as 0 in the plots where autumn vegetation had been eliminated either mechanically or by herbicides. All plots were equipped with ceramic suction cups at 1 m depth in 2011. Every one to four weeks, depending in weather conditions, water samples were collected by applying a suction of approximately 80 kPa three days prior to sampling. In total, we collected the water samples 10, 6, and 11 times during the studied period in 2015, 2016, and 2017, respectively. Then nitrate-N content of water samples was subsequently determined (Askegaard et al., 2005). To indicate nitrate-N content in the soil water during autumn and winter, average value of the measured soil water nitrate-N content from Oct. 1st to Mar. 31st was calculated in each plot.

y= ax+ b

(4)

y= a∙ln(x) + b

(5)

Sensitivities of the different VIs in autumn for estimating nitrate leaching in autumn and winter was tested through the Noise Equivalent (NE) by:

NE=

RMSE (VIvsNitrateleaching ) d (VI )/ d (Nitrateleaching )

(6)

in which, d(VI)/d(Nitrate leaching) is the first derivative of the fit function between the three VIs in autumn and nitrate leaching in autumn and winter; RMSE is the root mean square error of the fit function between the three VIs in autumn and nitrate leaching in autumn and winter, which were calculated by rmse function in the Metrics package in R (Hamner and Frasco, 2018). The higher absolute values of NE, the lower the sensitivity of the VI to nitrate leaching, which allows a direct comparison among the VIs with different scales and dynamic ranges (Viña et al., 2011; Li et al., 2014).

2.4. Nitrate leaching in autumn and winter The daily drainage in each plot was calculated with the EVACROP model (Olesen and Heidmann, 1990), which has been validated in Denmark against measurements of soil water contents during growing season (Olesen et al., 2000a,b). The EVACROP model applies a simple cascading model of soil water, using data on daily precipitation, air temperature, and reference evapotranspiration from a meteorological station located close to the experimental field. Nitrate leaching in each period between two observations was estimated by the trapezoidal rule (Lord and Shepherd, 1993), assuming that nitrate concentrations in the extracted soil water represented average flux concentrations (Askegaard et al., 2005). Daily nitrate leaching was calculated for each plot by multiplying daily drainage with flow-weighted interpolated daily nitrate-N concentration. The cumulated nitrate leaching in autumn and winter was calculated for the period from 1 Oct. to 31 Mar.

3. Results 3.1. Climate In 2015 and 2016, the accumulated precipitation during autumn and winter (October to March) were 360 mm and 364 mm, respectively, which were higher than the average value (340 mm) in 1961–1990 (Olesen et al., 2000a,b). However, the accumulated precipitation 3

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Fig. 1. Monthly cumulated precipitation and mean air temperature from April in 2015 to March in 2018 at the experimental site.

grass-clover, higher nitrate leaching was found under –M treatment than + M treatment in 2016 and 2017, while there was no difference between the two treatments in 2015. In faba bean and cereal crops (spring barley, spring wheat, and oat) plots, the effect of +/–M treatment was less significant than that of +/−CC treatment on the nitrate leaching, but variable among cropping systems and years. In faba bean, +CC (with cover crop) treatment only reduced the nitrate leaching in 2016, and there was no significant difference between + CC and −CC in 2015 and 2017. However, nitrate leaching during autumn and winter was reduced significantly by cover crops in the cereals in all cropping systems in 2016 and 2017. Fig. 3 shows that the differences in daily accumulated nitrate leaching during autumn and winter differed between +/−CC treatments for each main crop. In 2015, the effects of +/−CC treatments were negligible. On the other hand, +CC treatment reduced daily nitrate leaching in 2016 and 2017, and the effects of cover crops were smaller in spring barley and faba bean than in spring wheat and oat plots in October and November.

during autumn and winter was slightly lower in 2017 (321 mm) than two other years and the long-term average value, even though in 2017 the months of July to September had been very wet. The average monthly temperature of the period from October to March were 4.6 °C, 4.0 °C, and 3.3 °C in 2015, 2016, and 2017, respectively, and they were all higher than the average value (2.4 °C) in 1961–1990. Fig. 1 shows the accumulated precipitation and monthly average temperature from April in 2015 to March in 2018 at the experimental site. 3.2. Aboveground biomass, plant N, and soil nitrate concentration Fig. 2 shows the variations of aboveground biomass in autumn, plant N in autumn, and soil nitrate concentration in autumn and winter under different treatments in each cropping system in the three experimental years. Across all treatments and years, the average aboveground biomass and plant N in autumn were 1.3 Mg ha−1 and 38 kg N ha−1. The lowest average biomass (0.8 Mg ha−1) and plant N (24 kg N ha−1) in autumn were observed in 2015, while there was no difference in aboveground biomass and plant N between 2016 (1.9 Mg ha−1 and 52 kg N ha−1) and 2017 (1.2 Mg ha−1 and 36 kg N ha−1). Grass-clover plots had the highest aboveground biomass (3.8 Mg ha−1) and plant N (113 kg N ha−1) in autumn in all three years. In all three years, there was no vegetation in the field under −CC treatments in the two organic cropping systems (OGM and OGL), and the manure application (+/–M) did not affect aboveground biomass and plant N. In CGL, 0.6 Mg ha−1 aboveground biomass and 11 kg N ha−1 were harvested on average across years from the plots under −CC treatments, but they were still lower than those under + CC treatment (0.8 Mg ha−1 and 24 kg N ha−1). In 2015, the grass-clover plots had lower average soil nitrate concentration (4.1 mg L−1 with manure and 6.7 mg L−1 without manure, respectively) than other cropping systems (8.0∼14.6 mg L−1) during autumn and winter. In the grass-clover, higher soil nitrate concentration were found in the plots under –M treatment than + M treatment in 2016 and 2017. In OGM, OGL, and CGL systems, the soil nitrate concentration under −CC treatment (17.4 mg L−1 in 2016 and 15.5 mg L−1 in 2017) were higher than + CC treatment (5.2 mg L−1 in 2016 and 7.1 mg L−1 in 2017). Under −CC treatment, the highest soil nitrate concentration were found in OGM (23.4 mg L−1 and 20.1 mg L−1), followed by OGL (17.1 mg L−1 and 15.2 mg L−1) and CGL (11.9 mg L−1 and 11.1 mg L−1) in 2016 and 2017, respectively. However, soil nitrate concentration were similar under + CC treatment in all the three cropping systems, ranging from 4.2 mg L−1 to 8.5 mg L−1.

3.4. Correlations between nitrate leaching and aboveground biomass, plant N, and soil nitrate concentration Close relationships were found between nitrate leaching in autumn and winter and aboveground biomass in autumn, plant N in autumn, and soil nitrate concentration in autumn and winter (Fig. 4). For both plant biomass and plant N in autumn, a negative logarithmic function fitted to nitrate leaching in autumn and winter, which means that nitrate leaching decreased sharply with the increasing aboveground plant biomass and plant N, but decreased slowly above the threshold values (∼2 Mg ha−1 and 60 kg N ha−1). Nitrate leaching was linearly related to average soil nitrate concentration in autumn and winter, corresponding to leaching of 4.0 kg N ha−1 for each 1 mg L−1 nitrate in soil water. 3.5. Correlations between vegetation indices and nitrate leaching in autumn and winter Shortly before plant sampling in autumn, spectral measurements were taken to calculate three commonly used VIs (RVI, NDVI, and RRE) to indicate plant N status in all the plots in 2015, 2016, and 2017 (Fig. 5). Grass-clover always had higher VIs than cover crops following other crops. Grass-clover under + M treatment had lower RVI and RRE than –M treatment, but the differences in NDVI were not obvious. For the two organic cropping systems (OGM and OGL), all three VIs were higher under + CC treatment than −CC treatment in all three years, while there was no difference between + M and –M treatments. In the conventional cropping system (CGL), the median values were higher with cover crops than without, but the ranges were similar.

3.3. Nitrate leaching in autumn and winter Nitrate leaching during autumn and winter differed between main crops and treatments in the different cropping systems (Table 2). In the 4

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Fig. 2. Aboveground biomass in autumn, plant nitrogen in autumn, and soil nitrate concentration in autumn and winter under different treatments in each cropping system in 2015, 2016, and 2017. The black points indicate the average values for different treatments, with all crops pooled together. Error bars show the standard errors. G-C indicates grass-clover system; OGM, OGL, and CGL indicate cropping systems of organic with green manure, organic with legume, and conventional with grain legume, respectively. +/–M indicates with/without animal manure; +/−CC indicates with/without legume based cover crops; +F indicates the use of mineral fertilizers. Different lower case letters indicate significant differences in aboveground biomass in autumn, plant nitrogen in autumn, and soil nitrate concentration in autumn and winter among different treatments and cropping system during each year at P = 0.05.

Although NDVI in autumn had a higher R2 than RVI and RRE, it also had the highest noise equivalent values (most negative values) when the nitrate leaching during autumn and winter exceeded 50 kg N ha−1 (Fig. 8). RVI had the highest sensitivity for detecting nitrate leaching during autumn and winter when the nitrate leaching was below 100 kg N ha−1, but the sensitivity was lost sharply when nitrate leaching exceeded this threshold value. RRE exhibited consistent low noise equivalent values for the nitrate leaching in autumn and winter.

All three VIs (RVI, NDVI, and RRE) in autumn were linearly related to aboveground biomass and plant N in autumn, with coefficients of determination (R2) ranging from 0.56 to 0.79 (Fig. 6 and Table 3). The best performing VI was RVI, explaining 76 % of plant aboveground biomass and 79 % of plant N in autumn. RRE was the second best VI for estimating plant biomass and plant N in autumn with R2 of 0.70 and 0.69, respectively. NDVI only explained 57 % of plant biomass and 56 % of plant N, and NDVI showed a saturation response at around 0.8, when plant biomass exceeded ∼2.0 Mg ha−1 and plant N ∼60 kg N ha−1. Negative logarithmic relationships were found between VIs in autumn and soil water nitrate concentration in autumn and winter. The R2 ranged from 0.25 to 0.38. NDVI performed best and explained 38 % of soil water nitrate concentration in autumn and winter, while RVI and RRE explained 32 % and 25 % of soil water nitrate concentration, respectively. As for soil water nitrate concentration, all the three VIs showed negative logarithmic relationships with nitrate leaching during autumn and winter, and R2 ranged from 0.29 to 0.41 (Fig. 7 and Table 3).

4. Discussion 4.1. Nitrate leaching in autumn and winter In Europe, N leaching generally occurs approximately from the end of September to the beginning of April (Vos and Putten, 2004), and this is also the case in Denmark (Askegaard et al., 2005). Therefore, N leaching losses from the cropping systems highly depend on field conditions during autumn (Askegaard et al., 2011). In the current study, 5

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nitrate leaching during autumn and winter (from 1 Oct. to 31 March) were compared under different treatments in three cropping systems in three years. Although N leaching was affected by several interacting factors, differences in nitrate leaching were mainly determined by vegetation cover in autumn, in particular by the use of cover crops (Table 2 and Fig. 3). In the plots under + CC treatments, most of the biomass in autumn was from cover crops with a small fraction of weeds and volunteers. Under −CC treatments, there was no plant biomass in OGM and OGL plots, which were mechanically cultivated in autumn for weed control, while 0.6 Mg ha−1 aboveground biomass and 11 kg N ha−1 were harvested on average across years from the plots without cover crops in CGL (Fig. 2). In agreement with previous studies on different crop rotations at the same and other sites (Askegaard et al., 2005, 2011; Doltra and Olesen, 2013; De Notaris et al., 2018; Pandey et al., 2018), significant negative relationships were found between nitrate leaching in autumn and winter and aboveground biomass and plant N in autumn. As aboveground biomass and plant N in autumn increased, nitrate leaching initially decreased sharply, but decreased slowly above threshold values (Fig. 4). De Notaris et al. (2018) also reported that above a threshold in cover crop biomass, N leaching was reduced to a low stable level in spring wheat and potato plots. Since grass-clover was undersown in spring barley in the previous year, grass-clover plots produced higher aboveground biomass and plant N in autumn, and had low nitrate leaching in autumn and winter in all three years. In the grass-clover field, grass itself is efficient at utilizing soil mineral N, and clover-based swards with biological

Table 2 Nitrate leaching (kg N ha−1) during autumn and winter (from 1 Oct. to 31 Mar.) grouped by main crop under different treatments in three cropping systems in 2015, 2016, and 2017. Data from spring barley, spring wheat and oat was pooled as cereal crops. Different letters in columns indicate significant differences in nitrate leaching among different treatments and cropping system in the plots with same main crop during each year at P = 0.05. OGM, OGL, and CGL indicate cropping systems of organic with green manure, organic with legume, and conventional with grain legume, respectively. +/–M indicates with/without animal manure; +/−CC indicates with/without cover crops; +F indicates the use of mineral fertilizers. Main crop

Cropping system

Treatment

2015

2016

2017

Grass-clover

OGM

Faba bean

OGL

–M +M –CC + M +CC–M +CC + M –CC + F +CC + F –CC + M +CC–M +CC + M –CC + M +CC–M +CC + M –CC + F +CC + F

14 29 84 38 70 52 78 63 40 44 35 34 36 34 25

44 a 14 b 80 a 27 b 38 b 80 a 29 b 91 a 18 de 20 d 59 b 10 ef 13 def 34 c 8f

32 a 6b 62 a 47 a 42 a 64 a 51 a 69 a 29 c 22 cd 50 b 14 d 21 cd 30 c 13 d

CGL Cereals

OGM

OGL

CGL

a a a b ab ab a a ab ab ab ab ab ab b

Fig. 3. Daily accumulated nitrate leaching for main crops during autumn and winter (from 1 Oct. to 31 Mar.) under –/+CC treatment in three cropping systems in 2015, 2016, and 2017. All the lines are daily average cumulated nitrate leaching across cropping systems and treatments with the same main crop and shaded areas represent their variabilities (standard errors). The symbols indicated the significance of differences between the final accumulated values under + CC and −CC treatments. ns, not significant (P > 0.05); *, significant at P < 0.05; **, significant at P < 0.01; ***, significant at P < 0.001. 6

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Fig. 4. The relationships between nitrate leaching in autumn and winter and aboveground biomass in autumn, plant N in autumn, and soil nitrate in autumn and winter.

fixation of atmospheric N represent a more environmentally acceptable and sustainable alternative to fertilizer-based swards (Ryden et al., 1984; Cuttle et al., 1998). However, introduction of grazing animals reduces NUE and increases the risk of N loss in grass-clover systems (Ryden et al., 1984), and careful management is needed to limit nitrate leaching (Berntsen et al., 2006). The higher nitrate leaching in grazing based systems is a consequence of higher recycling of N in this system. In our experiment, grass-clover cuttings were removed in the + M treatment, but returned as surface mulch in the –M treatment (De Notaris et al., 2018). This higher return of N by mulching of grassclover is likely the reason for the significantly higher nitrate leaching from grass-clover of the –M treatment, as found for grazing based systems (Table 2). Faba bean is a grain legume crop and able to fix atmospheric N symbiotically (Köpke and Nemecek, 2010). In the current experiment during the 3rd cycle, Pandey et al. (2018) estimated a biological N fixation of faba bean of about 300 kg N ha−1. Since a relatively large proportion of this biological N fixation was returned to the soil in crop residues, an increased nitrate leaching potential was shown under precipitation surplus conditions (Aschi et al., 2017). In the current study, nitrate leaching was higher from faba bean than from cereal crops under all the treatments in OGL and CGL systems (Table 2). Planting cover crops could still be an efficient way to mitigate nitrate leaching after faba bean (Justus and Köpke, 1995; Vocanson et al., 2006), as found in both organic and conventional cropping systems in the current study (Table 2). However, the later harvesting of faba bean relative to cereal crops reduces growth of the cover crops in autumn, which may explain the relatively high nitrate leaching in faba bean compared with cereals in + CC plots (Fig. 3). In the cereal crops (spring wheat, spring barley, and oat), nitrate leaching during autumn and winter was reduced significantly by + CC treatments in all OGM, OGL, and CGL systems in 2016 and 2017, with legume-based cover crop mixtures performing as effectively as non-legumes alone. Since greater nitrate leaching in 2015 was only found under + CC treatments compared to the other two years, similar nitrate leaching between +/−CC treatments in 2015 is likely caused by the poor establishment and growth of cover crops. Late harvest of the main crop and the associated late start of cover crop growing period in 2015 affected the growth of cover crops and their efficiency to retain N during autumn (Vos and Putten, 1997; Teixeira et al., 2016). Furthermore, when cover crops are undersown, a competitive main crop can limit the growth of cover crops (Doltra and Olesen, 2013). This means that favorable weather patterns for the growth of the main crop would

lead to suppression of the establishment of the cover crop and reduce the ability to deplete soil N (De Notaris et al., 2019). The great biomass accumulation from the main crop in 2015 (data not shown) suggests that the low cover crop biomass could have been caused by both competition from the main crop and a short growing season after harvest of the main crop. Although manure application increases crop yields, there has been little effect on N leaching (Olesen et al., 2007, 2009; Doltra et al., 2011; Pandey et al., 2018). This was corroborated by results of the current study, where we found that the effects of +/–M treatment were smaller than those of +/−CC treatments on the nitrate leaching during autumn and winter in the cereal crops bean in the two organic systems.

4.2. Vegetation indices and nitrate leaching Vegetation indices have been widely used to detect the N status of crops (e.g., plant N and uptake) to guide farmers for N management (Raun et al., 2002; Li et al., 2014; Nigon et al., 2014; Zhou et al., 2018), because the light reflectance of the canopy in the red wave-bands is highly sensitive to leaf chlorophyll and N concentrations (Lamb et al., 2002). Based on the relationships between VIs and plant N or biomass, spectral reflectance-based N fertilization has been suggested to remove N stress or surplus (Lamb et al., 2002; Hansen and Schjoerring, 2003; Zhou et al., 2018), improve NUE and yield, and reduce nitrous oxide emissions (Fitzgerald et al., 2010; Frels et al., 2018). Besides, VIs also offer potential for estimating risk of nitrate leaching, since nitrate leaching is highly related to biomass and N uptake of vegetation during autumn (Macdonald et al., 2005; De Notaris et al., 2018). In the current study, we found that nitrate leaching during autumn and winter declined with increasing value of the VIs with a negative logarithmic response, which means that nitrate leaching decreased sharply with increasing plant aboveground biomass and plant N but decreased slowly above the threshold values (Fig. 4, ∼2 Mg ha−1 and 60 kg N ha−1). De Notaris et al. (2018) also related the biomass of cover crops to yearly nitrate leaching and found thresholds of 0.9 Mg ha−1 and 1.5 Mg ha−1 cover crop biomass following spring wheat and potato, respectively, above which the nitrate leaching was reduced to low stable levels. In the current study, all three VIs (RVI, NDVI, and RRE) in autumn showed significant positive linear relationships with aboveground biomass and plant N in autumn (Fig. 6 and Table 3), which is consistent with previous studies (Gao et al., 2013; Jiang et al., 2015; Li et al., 2016). In contrast, negative logarithmic relationships were found 7

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Fig. 5. Ratio Vegetation Index, Normalized Difference Vegetation Index, and Ratio Red Edge in autumn under different treatments in three cropping systems in 2015, 2016, and 2017. Values are pooled for all the crops to make the box-plots. The horizontal lines in the box indicate the median values, and the lower and upper hinges correspond to the first and third quartiles (the 25th and 75th percentiles). The upper and lower vertical lines from the hinge indicate the largest and smallest values at 1.5 * IQR (where IQR is the inter-quartile range, or distance between the first and third quartiles, a roughly 95 % confidence interval for comparing medians). G-C indicates grass-clover system; OGM, OGL, and CGL indicate cropping systems of organic with green manure, organic with legume, and conventional with grain legume, respectively. +/–M indicates with/without animal manure; +/−CC indicates with/without cover crops; +F indicates the use of mineral fertilizers.

management (Li et al., 2014). Red edge-based VIs are not only sensitive to chlorophyll and N status, but can also overcome the saturation problem in NDVI (Nguy-Robertson et al., 2012; Zhou et al., 2018). In our study, RRE provided good estimation of plant aboveground biomass and plant N in autumn with R2 of 0.70 and 0.69, respectively. To assess how well the regressions capture the relationship between VIs in autumn and nitrate leaching in autumn and winter (Fig. 8), noise equivalent values were calculated, which account for both scattering of the measured points and slopes of fitting functions (Gitelson, 2013). Although NDVI and RVI in autumn had a higher R2 than RRE, they also had higher noise equivalent values when the nitrite leaching during autumn and winter exceeded 50 kg N ha−1 and 100 kg N ha−1, respectively, and the sensitivity was lost sharply when nitrate leaching exceeded the threshold value. RRE exhibited consistent low noise equivalent values for the nitrate leaching in autumn and winter. This illustrates that red edge-based VIs may improve quality of ground and satellite or aerial remote sensing technologies for estimating plant N uptake and its effects on nitrate leaching. According to Danish legislation, mandatory cover crops was listed

between VIs and soil water nitrate concentration and nitrate leaching in autumn and winter. Among the three VIs, RVI and NDVI are the most commonly used for estimating biomass and N status (Yao et al., 2010; Li et al., 2014, 2016). RVI provided the best estimation and explained 76 % of plant aboveground biomass and 79 % of plant N in autumn. However, RVI is sensitive to atmospheric effect, especially in the case of sparse vegetation coverage (less than 50 %) (Xue and Su, 2017), and it is not applicable with data collected by satellite sensors in regional and global assessments. NDVI is more reliably estimated using satellite imagery in the large scale, but this only explained 57 % of aboveground biomass and 56 % of plant N. The linear relationships between NDVI and aboveground biomass and plant N were not as well as two other VIs, at least when the grass-clover data were included. This may be due to the saturation of the index at moderate to high canopy coverage conditions (Zhou et al., 2018) or to the grass-clover data not fitting well with the other data. To complement the deficiency of the NDVI index, newly launched high spatial resolution satellites have better sensitivities in the red edge bands, which can monitor crop growth and guide precision N 8

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Fig. 6. Relationships between vegetation indices [Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), and Ratio Red Edge (RRE)] in autumn and aboveground biomass in autumn, plant N in autumn, and soil water nitrate concentration in autumn and winter under different treatments in three cropping systems in 2015, 2016, and 2017. Points in each plot show results from each plot and each year.

Table 3 Estimated parameters and coefficient of determination (R2) for the regression models between vegetation indices [Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), and Ratio Red Edge (RRE)] in autumn and aboveground biomass in autumn (Mg ha−1), plant N in autumn (kg N ha−1), soil water nitrate concentration in autumn and winter (mg L−1), and nitrate leaching in autumn and winter (kg N ha−1) under different treatments in three cropping systems in 2015, 2016, and 2017. Linear regression was used for aboveground biomass and plant N in autumn, whereas logarithmic regression models were used for the average soil water nitrate concentration and cumulated nitrate leaching in autumn and winter. RVI

Aboveground biomass Plant nitrogen Soil nitrate concentration Nitrate leaching

NDVI 2

a

b

R

0.21 6.38 −4.21 −18.28

−0.06 −4.35 15.53 62.50

0.76 0.79 0.32 0.36

RRE 2

a

b

R

4.92 145.06 −7.99 −33.96

−1.77 −53.63 4.15 13.56

0.57 0.56 0.38 0.41

9

a

b

R2

4.34 128.41 −19.29 −84.75

−5.39 −160.58 16.97 69.16

0.70 0.69 0.25 0.29

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Fig. 7. Relationships between vegetation indices [Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), and Ratio Red Edge (RRE)] in autumn and nitrate leaching in autumn and winter under different treatments in three cropping systems in 2015, 2016, and 2017. Points in each plot show results from each plot and each year.

governmental officials, which is both a laborious effort and may also not always give a good impression of the efficiency of cover crops. In the current study, the results provided a possibility of using satellite imagery or unmanned aerial vehicle (UAV) with VIs to monitor the risk of nitrate leaching from agricultural soils and the effectiveness of cover crops. However, before the VIs are used as tools practically, they need to be validated in other years. We did a cross-validation about nitrate leaching in autumn and winter based on our dataset, with two-years data used to train the model and the other one year data used for the test (not shown). Our models gave an acceptable estimation when the observed nitrate leaching was less than 30 kg N ha−1. Nevertheless, the predicted leaching cannot exceed 60 kg N ha−1, which indicates a low efficiency of VIs to monitor a serious risk of nitrate leaching. To test if using VIs allows to assess nitrate leaching reduction to the same extent as comparing treatments of +/−CC and the efficiency of cover crops, we compared average nitrate leaching above and below thresholds under all treatments and + CC treatment in different cropping systems (excluding grass-clover) (Table 4). Absolute errors between the reduced nitrate leaching by + CC and above the values were calculated with the ranges of 2∼5 and step of 1 for RVI, 0.3∼0.6 and 0.1 for NDVI, and 1.3∼1.6 and 0.1 for RRE, respectively. The values with the lowest mean absolute errors were selected as the thresholds (RVI = 4, NDVI = 0.5, and RRE = 1.3) in the current study. In OGM and OGL, it is an effective method of using the thresholds of NDVI and RRE to evaluate the reduced nitrate leaching by cover crops. Compared to the actual reduced nitrate leaching by cover crops (45.6 and 27.6 kg N ha−1), the errors of estimated reductions were 4.7 and 2.7 kg N ha−1 by NDVI and 0.1 and 0.7 kg N ha−1 by RRE in OGM and OGL, respectively. However, the reduction in nitrate leaching was

Fig. 8. Noise equivalent of nitrate leaching estimation during autumn and winter by vegetation indices.

as one of the good agricultural practices to regulating nitrogen uses and discharges, and farmers must have a certain proportion of their farmland in cover crops depending on farming system and local conditions (Dalgaard et al., 2014). For example, to comply with the “Danish Nitrate Action Programme 2008–2015”, cover crops must be established on 10 % or 14 % of owned and leased area to reduce the nitrate losses by 17 or 25 kg N ha−1, depending on whether the N application rate is below or above 80 kg N ha−1. However, this is controlled by manual inspection and the number of plants in the field is simply counted by

Table 4 Reduced nitrate leaching (kg N ha−1) with above and below the thresholds of vegetation indices under + CC and all treatments in different cropping systems. Cropping system

OGM

OGL

CGL

Treatment

+CC –CC Reduction +CC –CC Reduction +CC –CC Reduction

All

28.7 74.3 45.6 27.2 54.8 27.6 24.9 40.1 15.2

Threshold

Above Below Reduction Above Below Reduction Above Below Reduction

RVI = 4

NDVI = 0.5

RRE = 1.3

All

+CC

All

+CC

All

+CC

24.9 59.2 34.3 19.9 51.7 31.8 20.5 37.5 17.0

24.9 41.5 16.6 19.9 46.1 26.2 14.4 31.2 16.8

26.7 67.6 40.9 22.4 52.7 30.3 28.0 40.5 12.5

26.7 47.4 20.7 21.5 48.0 26.5 13.2 41.2 28.0

28.7 74.4 45.7 26.1 54.4 28.3 31.5 38.4 6.9

27.7 69.8 42.1 24.0 60.7 36.7 23.3 35.9 12.6

10

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underestimated by 11.3 kg N ha−1 in OGM but overestimated by 4.2 kg N ha−1 in OGL. In CGL, the error of estimated leaching reduction by RRE was 57 %, while those values were 12 % and 18 % by RVI and NDVI, respectively. Under only + CC treatment, VIs are also able to indicate the effectiveness of cover crops for reducing nitrate leaching in all three cropping systems. The average values of nitrate leaching above the thresholds of RVI and NDVI were from 16.6 to 28.0 kg N ha−1 lower than those below the thresholds. Such monitoring could be the basis of new regulations that substitute mandatory cover crop requirements, with requirements for a proportion of crops to have VIs above specific thresholds. The estimation of thresholds would need to be established across different farming systems and local conditions in future studies. Moreover, proper platform application should be tested under practical condition. On one hand, the three main platforms (satellite, UAV, and handheld sensors) could provide comparable results (Matese et al., 2015; Rudd et al., 2017); models from spectral data collected at the point scale with handheld instruments can be upscaled to estimate potential nitrate leaching reduction due to establishing cover crops at larger scales by satellite imagery or UAV. On the other hand, the efficiency of data collection should also be considered, because each platform has its own set of shortcomings (Rudd et al., 2017). Groundbased sensors are inefficient over a large area, although the data is highly accurate; satellite imagery has a low spatial resolution and relatively long revisit frequencies, and it is hard to collect under cloudy conditions during autumn; UAV can be expensive and the efficiency of data collection may also be affected by windy and rainy weather. Furthermore, there are important uncertainties related to complex soil process in the current method to detect aboveground vegetation thresholds for low nitrate leaching during autumn and winter. For example, greater nitrate leaching and lower cover crop effectiveness in reducing nitrate leaching were found in soils with low water holding capacity than in soils with high water holding capacity (Teixeira et al., 2016). This means that threshold values of VIs should be adjusted based on different soil types. Therefore, the estimation of thresholds would need to be established across different farming systems and local conditions in future studies.

Declaration of Competing Interest The authors declare no competing interests. Acknowledgement The study was financially supported by the VIRKN project under the Green Growth and Development programme (GUDP) under Danish Ministry of Environment and Food, and by the RowCrop project funded under Organic RDD2 by the Green Growth and Development programme (GUDP) under Danish Ministry of Environment and Food and coordinated by International Centre for Research in Organic Food Systems (ICROFS). References Aschi, A., Aubert, M., Riah-Anglet, W., Nélieu, S., Dubois, C., Akpa-Vinces, M., Trinsoutrot-Gattin, l, 2017. Introduction of Faba bean in crop rotation: impacts on soil chemical and biological characteristics. Appl. Soil Ecol. 120, 219–228. Askegaard, M., Olesen, J.E., Kristensen, K., 2005. Nitrate leaching from organic arable crop rotations: effects of location, manure and catch crop. Soil Use Manag. 21, 181–188. Askegaard, M., Olesen, J.E., Rasmussen, I.A., Kristensen, K., 2011. 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5. Conclusions In all three autumns (2015, 2016, and 2017), grass-clover produced the highest aboveground biomass and plant N, and the biomass and plant N were higher under + CC treatment than −CC treatment in all cropping systems. Soil water nitrate concentration and nitrate leaching was lower under + CC than −CC. In cereals, cover crops significantly reduced nitrate leaching, while in faba bean reduced nitrate leaching was only observed in 2016. In autumn and winter, negative relationships were found between nitrate leaching and aboveground plant biomass or plant N, and the thresholds were ∼2 Mg ha−1 and 60 kg N ha−1, above which nitrate leaching was low and stable. In addition, a significantly positive linear relationship was found between nitrate leaching and soil nitrate concentration in autumn and winter, and 4.0 kg N ha−1 were leached for each mg L−1 of additional nitrate-N in the soil. All the three VIs showed significant negative logarithmic relationships with nitrate leaching during autumn and winter. However, the sensitivities of RVI and NDVI to estimate nitrate leaching were lost sharply when nitrate leaching exceeded 100 kg N ha−1 and 50 kg N ha−1, respectively, while RRE exhibited consistent low noise equivalent values for nitrate leaching in autumn and winter. Furthermore, we demonstrated the potential to assess nitrate leaching loss assessment and N management using newly launched satellite remote sensing platforms with NDVI and red edge bands for assessment of autumn vegetation cover as an effective means for reducing nitrate leaching. This study provides insights for using satellite imagery or UAV with VIs to monitor the risk of nitrate leaching from agricultural soils by assessing the effectiveness of cover crop management. 11

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