Cereal production in Europe

Cereals are grown on half of the European Union's (EU) farms, occupying a third of EUs agricultural area and accounting for a quarter of its crop production value. On a global scale, Europe accounts for 20% of the total cereal production, of which about 63% is produced in the countries of the EU28. Cereals in the EU28 are mainly used for animal feed (61%) and human consumption (24%), while smaller other purposes include alcoholic beverages (5%), bio-energy (4%) and seeds (3%) (EU, 2016). Wheat and rye are used almost equally for animal feed and human consumption, while barley, maize, sorghum, oats and triticale are predominantly used for animal feed. In recent years, Europe has been a net exporter of around 15% of its cereal production (FAO Food Outlook, 2016). The exported cereals are mainly wheat and barley, while the imports consist mainly of maize.

Approach

The global yield gap atlas presents actual and potential yields for wheat, barley and maize in Europe. Together these three crops represent 90% of the European cereal production. We use a country-by-country bottom-up approach to establish statistical estimates of actual grain yield, and compare these to modelled estimates of potential yields. In brief, the approach distinguishes the following main steps: (1) selection of representative climate zones (CZ) based on dominant crop areas, (2) selection of reference weather stations (RWS) that represent the selected CZs, (3) selection of dominant soil types and cropping systems in a 100 km radius around the RWS, (4) crop model simulations to establish rainfed or irrigated yield potential, and (5) estimation of actual yields from statistical surveys. Detailed information and justification is available in separate publications on climate zones, upscaling from RWS to CZ and national scale with area-weighted averages, and data selection methods. For 22 out of the 39 countries, country agronomists were involved, representing 94% of the wheat and barley area, and 82% of the maize area. They had a pivotal role in data access, expert estimates and evaluation of results. The next sections present a point-by-point account of the underlying data and methods used for Europe.

Selected climate zones

On average, there are 15 CZs per country, but it varied from 2 (the Netherlands) to 48 (Spain). Harvested areas for wheat, barley and grain maize were taken from the Spatial Production Allocation Model (SPAM) of Harvestchoice, presenting harvested areas around the year 2005 at a 5' grid, which is the most recent version to date. Both layers were combined to calculate the harvested area per climate zone per country. The harvested areas of wheat (34 Mha), barley (20 Mha) and maize (13 Mha) were distributed over 80 CZs for wheat and barley, and 75 CZs for maize (Table).

Selection of the CZs was carried out in two steps, with the aim to cover at least 50% of the harvested area. First, all CZs with at least 5% of the national harvested area were selected. However, for some countries with many relatively small climate zones this approach resulted in a low crop area covered by the CZs. Therefore, also CZs with less than 5% of the national harvested area were selected if a suitable weather station was present for that particular CZ. The final number of selected CZs was on average 5 per country, with a range of 1 (Luxemburg) to 16 (Spain). On average, 43% of the number of CZs in a country were selected representing on average 88% of the national crop area, but it ranged from 26% (Bosnia Herzegovina – maize) to 100% (the Netherlands) of the national crop area.

Reference weather stations (RWS)

Weather data were collected for stations in the selected CZs with at least ten years of consecutive daily data and less than 20% missing data for each variable. Precipitation, minimum and maximum temperature, vapour pressure and wind speed were used from stations in the NOAA Global Surface Summary of the Day (https://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.ncdc:C00516). If suitable weather stations with adequate data were unavailable, gridded weather data from Agri4Cast (http://agri4cast.jrc.ec.europa.eu/) were used. Daily radiation was derived from NASA (http://power.larc.nasa.gov/). For precipitation, zero was assigned to missing values, while for other variables linear interpolation was used to fill data gaps.

The total number of selected RWSs for wheat, barley and maize was 287, 271 and 202, respectively. This equates to an average of 1.3 weather stations per climate zone. In 22 cases (Albania, Bosnia Herzegovina, Kosovo, Macedonia, Moldova and Montenegro) a suitable RWS with actual weather data was unavailable, and gridded data were used that represented the location of the specific weather station.

Soils and crops

Data on water content at field capacity (pF=2.5) minus water content at wilting point (pF=4.2), root penetrable soil depth and hydrogeological class of soils were taken from the 1 km x 1 km grid of the European Soil Database. Within the 100 km zone around each RWS, the three dominant Soil Map Units (SMUs) were selected, based on the harvested area. Each SMU comprises a varying number of Soil Type Units (STUs) of which the soil parameters were used as input to the model.

The yield gap assessment in this study covers rainfed wheat, barley and maize, as well as irrigated maize. For wheat and barley, both spring sown and autumn sown cropping systems were taken into account if they covered at least 15% of the total wheat or barley area (Table). Common wheat is the default wheat type, but for Mediterranean regions durum wheat was also considered. In this study the term "maize" stands for grain maize; forage maize was not included.

Crop modelling

We implemented the WOFOST crop model version 7.1.7, which was calibrated for many regions throughout Europe. WOFOST computes daily biomass accumulation and its distribution over crop organs during the growth period using a photosynthesis minus respiration approach. Crop yield was simulated for the potential (Yp) and the water-limited (Yw) production situation. Yp is determined by temperature, day length, solar radiation and genetic characteristics assuming absence of any water or other stress factors. Yw is limited by water supply, and hence influenced by rainfall, soil type and depth. Soil water dynamics in the root zone were simulated with a daily time step. The model does not account for capillary rise of water from below the root zone. To prevent overestimation of water limitation for soils with shallow groundwater (e.g. large parts of the Netherlands and the Po valley in Italy), Yw was assumed to equal Yp in these regions. For both Yp and Yw non-limiting nutrient supply was assumed. Yield losses caused by pests, diseases, weed and/or extreme weather events were considered for neither Yp nor Yw. Vernalization was not implemented in WOFOST and crop growth and phenological development for autumn sown crops were therefore calculated from January 1st onwards, assuming a fixed initial dry biomass of 210 kg ha-1.

The original crop parameters for European regions were updated in two steps to represent conditions covering approximately the last 15 to 20 years. First, additional phenology data were collected from a variety of sources, comprising either geo-referenced networks of observations, experimental sites or expert estimates by country agronomists. For spring sown crops, the observations consisted of day of sowing, emergence, anthesis and maturity. For autumn sown crops, emergence was fixed on January 1st. All phenology data were grouped per country per climate zone, and subsequently temperature sums between sowing and emergence, between emergence and anthesis, and between anthesis and maturity were calculated for each RWS. Initial model runs were carried out with these data and the simulated harvest index (HI) and maximum leaf area index (LAIM) were checked against a plausible range.. If more than 10% of the number of simulations were outside the plausible range for HI (minimum: 0.35 to 0.40; maximum 0.55 to 0.60, depending on crop) or LAIM (minimum 3 to 4; maximum 6 to 7, depending on crop), crop parameters were adjusted within biologically plausible values as per the guidelines for regional calibration of WOFOST. The relevant parameters for calibration were, in order of importance, SLATB (specific leaf area [ha kg-1]), the partitioning of assimilates to the various organs (FSTB for stems, FLTB for leaves and FOTB for storage), SPAN (life span of leaves growing at 35oC [d]) and AMAX (maximum leaf CO2 assimilation [kg ha-1 h-1]). The final evaluation step consisted of an expert assessment by the country agronomist, and if available, supported by annual maximum yields observed in variety trials or agronomic experiments. If the average simulated yields were more than 15% lower or higher than the observed maximum yields, or if the experts qualified the simulations not plausible, further fine-tuning of the crop parameters, as described above, was carried out.

The simulations were carried out for each STU within a RWS zone. The simulation results were up-scaled successively to SMU, RWS, CZ and country, using harvested area per STU as weighing factor. All simulated crop yields are presented at standard moisture content, i.e. 13.5% for wheat and barley, and 15.5% for maize.

Actual yields

The actual annual grain yields (Ya) were obtained from national statistical offices at the best available spatial resolution (NUTS levels 1, 2 or 3 representing increasing regional resolution; http://ec.europa.eu/eurostat/web/nuts/overview) and at the most disaggregated crop and cropping system level (spring sown or autumn sown common or durum wheat, spring sown or autumn sown barley, rainfed maize, and irrigated maize). Yield data were collected for a recent period of 10 years for rainfed crops and 5 years for irrigated crops. A linear trend analysis was carried out to identify countries with a significant (P<0.05) increasing trend. For those countries with increasing trends, only the recent 5 year period was used to avoid effects of technological developments. The actual yields were re-scaled from the NUTS region to the RWS zone, and subsequently to CZ and country, using the harvested area as weighing factor. All actual crop yields are presented at standard moisture content, i.e. 13.5% for wheat and barley, and 15.5% for maize.

More details and references are presented in Schils et al. (2018) Cereal yield gaps across Europe https://doi.org/10.1016/j.eja.2018.09.003

Table. Harvested areas of wheat, barley and grain maize around 2005 (You et al., 2014) (a-c), cropping systems included in the analysis (d-i), including the proportion of spring sown and autumn sown wheat (d,e) and barley (f,g), the total number of climate zones (CZs) (j), and per crop the area covered by those selected CZs (l,n,p).

Country

a

 

Wheat area

 

(1,000 ha)

b

 

Barley area

 

(1,000 ha)

c

 

Maize area

 

(1,000 ha)

d

 

Spring sown wheat

 

(%)

e

 

Autumn sown wheat

 

(%)

f

 

Spring sown barley

 

(%)

g

 

Autumn sown barley

 

(%)

h

 

Rainfed maize

i

 

Irrigated maize

j

 

All CZs

 

(n)

l

 

Area cover wheat

 

(%)

n

 

Area cover barley

 

(%)

p

 

Area cover maize

 

(%)

Albania

78

2

47

 

100

 

100

 

Y

13

70

69

74

Austria

289

197

177

 

100

55

45

Y

 

12

94

93

96

Belarus

357

617

29

20

80

100

 

Y

 

11

97

97

85

Belgium

211

43

55

 

100

 

100

Y

 

5

98

96

99

Bosnia Herzegovina

81

21

195

 

100

 

100

Y

 

13

37

37

26

Bulgaria

1,031

258

341

 

100

 

100

Y

 

23

97

96

93

Croatia

180

52

346

 

100

 

100

Y

 

17

95

93

93

Cyprus

6

52

   

100

 

100

   

10

67

93

 

Czech Republic

822

507

93

 

100

71

29

Y

 

14

94

94

97

Denmark

662

679

   

100

100

     

3

99

99

 

Estonia

85

138

 

63

37

100

     

4

97

97

 

Finland

209

560

 

85

15

100

     

6

99

98

 

France

5,244

1,631

1,645

 

100

29

71

Y

Y

26

95

95

97

Germany

3,128

1,981

435

 

100

30

70

Y

 

16

97

98

91

Greece

808

93

235

 

100

 

100

 

Y

37

73

54

70

Hungary

1,120

312

1,197

 

100

40

60

Y

 

8

98

98

97

Ireland

94

170

 

30

70

84

16

   

5

98

97

 

Italy

2,131

318

1,139

 

100

 

100

 

Y

33

84

83

84

Kosovo

83

1

42

 

100

 

100

Y

 

15

41

41

44

Latvia

190

142

 

33

67

100

     

7

85

87

 

Lithuania

356

341

2

38

62

100

     

11

93

89

 

Luxemburg

12

10

0

 

100

 

100

   

4

89

99

 

Macedonia

102

47

33

 

100

 

100

Y

 

22

69

72

46

Moldova

336

118

492

 

100

44

56

   

7

99

99

100

Montenegro

1

1

3

 

100

 

100

Y

 

6

100

100

83

Netherlands

133

47

20

 

100

100

 

Y

 

2

100

100

100

Norway

83

147

 

85

15

100

     

5

88

87

 

Poland

2,233

1,115

351

 

100

85

15

Y

 

17

95

96

97

Portugal

138

31

117

 

100

 

100

 

Y

36

89

89

69

Romania

2,239

406

2,774

 

100

38

62

Y

 

26

87

83

87

Serbia

531

92

1,155

 

100

 

100

Y

 

21

79

77

81

Slovakia

365

204

152

 

100

100

 

Y

 

14

96

97

98

Slovenia

31

16

43

 

100

 

100

Y

 

7

99

98

97

Spain

2,122

3,177

412

 

100

 

100

 

Y

48

82

82

66

Sweden

367

357

   

100

100

     

11

98

97

 

Switzerland

90

37

19

 

100

 

100

Y

 

10

99

99

95

Ukraine

5,790

4,659

1,881

 

100

100

 

Y

 

30

86

85

81

United Kingdom

1,881

933

   

100

60

40

   

13

98

98

 

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