Innovative cropping systems designed to reach both environmental and production targets: Data set of biotic and abiotic variables from a twelve-year French field trial

The data set describes variables collected from a French (N 48.84°, E 1.95°) field trial, over a twelve-year period (2009-2020), in which four innovative cropping systems designed to reach multiple environmental and production goals were assessed. The four cropping systems were designed with new combinations of agricultural practices; they differed in terms of pesticide uses, nitrogen inputs, tillage practices, and crop sequences. Both biotic and abiotic variables were measured. In a previous data paper, we focused on nitrogen fluxes collected from two systems, over eight years (2009-2016). In the present one, we enlarge the scope of the variables, including more crop descriptions and environmental indicators, from all four systems, and over a longer period (2009-2020). The biotic data are: growth stages; aboveground plant nitrogen content and biomass collected at different growth stages, depending on the species; yield components of all the crops; and yield harvested with a combine machine. No weed, crop disease, and pest data are described. The abiotic data are physical and chemical properties of the soil (i.e. texture, calcium carbonate content, pH, organic carbon contents, and nitrogen contents) collected at different assessment periods. All agricultural practices, and climate were regularly recorded, and the treatment frequency indexes and the energy consumptions were computed. These data could be used for benchmarking, to design low-input systems, to improve models for parameterization and validation, and to increase the predictive accuracy of models of crop growth and development, specifically for orphan species such as linseed, faba bean or hemp, and for soil carbon and soil nitrogen fluxes in various conditions.


a b s t r a c t
The data set describes variables collected from a French (N 48.84 °, E 1.95 °) field trial, over a twelve-year period (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020), in which four innovative cropping systems designed to reach multiple environmental and production goals were assessed.The four cropping systems were designed with new combinations of agricultural practices; they differed in terms of pesticide uses, nitrogen inputs, tillage practices, and crop sequences.Both biotic and abiotic variables were measured.In a previous data paper, we focused on nitrogen fluxes collected from two systems, over eight years (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016).In the present one, we enlarge the scope of the variables, including more crop descriptions and environmental indicators, from all four systems, and over a longer period (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020).The biotic data are: growth stages; aboveground plant nitrogen content and biomass collected at different growth stages, depending on the species; yield components of all the crops; and yield harvested with a combine machine.No weed, crop disease, and pest data are described.The abiotic data are physical and chemical properties of the soil (i.e.texture, calcium carbonate content, pH, organic carbon contents,

Value of Data
• The data were collected from four innovative cropping systems, designed with multiple environmental and production objectives, assessed in a wide (6.2 ha) and long-term (2009-2020) field experiment in France (N 48.84 °, E 1.95 °).• The data were used to assess the environmental and production performances of the systems [ 3 , 4 , 5 , 6 ], and to write a previous data paper [7] .Here, the data cover the entire assessment period of the cropping systems, and encompass a wider range of variables.• These data provide ongoing research material for benchmarking, to design new systems that eliminate pesticide use and decrease energy consumption, nitrogen losses, and greenhouse gas emissions, in northern Europe.• The data could be used to improve models of plant growth, soil nitrogen fluxes, and soil carbon sequestration, and to enhance their predictive accuracy.• The data can also be used to calculate new indicators based on nitrogen flux, and soil carbon sequestration measurements.

Background
The aim of the "Innovative Cropping systems under Constraints" project was to design four innovative cropping systems, combining multiple environmental and production objectives to deliver ecosystem services [3] , and to assess them in a wide (6.2 ha) and long-term (2009-2020) field trial in France (N 48.84 °, E 1.95 °) [ 4 , 5 ], and [6] .
The objective of this data paper is to pull together the highest number of data collected from this experiment.Compared to the previous data paper driven from the same project [7] , we added a wide range of variables (i.e.growth stages, yield components, soil carbon contents), and environmental indicators (i.e.treatment frequency indexes, energy consumption).Data were provided from all four systems, and the collection period was longer (twelve years) than that presented previously (seven years), for all the variables including those already gathered in [7] .No data on weeds, crop diseases, or pests are provided in this paper.Due to the COVID pandemic in 2020, no agricultural practice over the spring period was allowed, resulting in low yields, and all measurements were banned.Despite such unusual cropping system management, some data were delivered to further understanding relating to the soil carbon content measured in October 2020.

Data Description
We classified the data in five groups: (1) plant measurements; (2) soil properties; (3) agricultural practices; (4) environmental indicator results; and (5) climate.The four cropping systems are denoted as follows: productive with high environmental performances (PHEP); no pesticide use (No-Pest); low energy consumption (L-EN); and low greenhouse gas emissions (L-GHG).In all the files, MD stands for missing data.

File: glossary_species_2023
This file contains meanings of species abbreviations.There are two columns: (1) abbreviation; and (2) meaning of the abbreviation.

File: glossary_growth_stage_2023
This file includes meanings of growth stage abbreviations.There are three columns: (1) growth stage abbreviation; (2) meaning of the abbreviation; and (3) code of growth stage.
3.1.5.5.File: data_yield_component_rape_2023.This file includes data relating to the yield components of winter rape, sown in the productive with high environmental performances system, the low energy consumption system, and the low greenhouse gas emissions system, over the 2009-2020 period.There are fourteen columns: (1) year of harvest (YYYY); (2) name of cropping system (productive with high environmental performances, PHEP; low energy consumption, L-EN; and low greenhouse gas emissions, L-GHG); (3) number of replicate (1 to 3); (4) number of plot (1, 3, 4, 5, 6, 7, 9, 10, and 12); ( 5) number of the sample (1 to 12; 1_0N to 3_0N); ( 6) surface of sample (m ²); (7) date of the measurement (DD/MM/YYYY); ( 8) number of plants per sample; (9) total number of branches per sample; (10) total number of fertile pods per sample; (11) total number of short peduncles (corresponding to sterile pods) on the branches in the sample; (12) total number of long peduncles (corresponding to sterile pods) on the branches in the sample; (13) total number of burst pods (sterile pods) in the sample; and ( 14) total potential number of pods (both fertile and sterile) in the sample.

File: data_yield_combine_all_species_2023
This file contains data of yields for all species, collected on each plot in the four cropping systems, each year over the 2009-2020 period.There are eleven columns: (1) year of harvest (YYYY); (2) name of the cropping system (productive with high environmental performances, PHEP; no pesticide use, No-Pest; low energy consumption, L-EN; and low greenhouse gas emissions, L-GHG); (3) number of replicate (1 to 3); (4) number of plot (1 to 12); ( 5) number of the sample; (6) species (for precise meanings see file "glossary_species"); (7) date of measurement (DD/MM/YYYY); (8) surface area of the sample (expressed in m ²); (9) moisture of the sample expressed in percent of dry biomass (((wet soil mass -dry soil mass)/ dry soil mass) * 100); (10) thousand-kernels weight (0% of dry matter); and (11) yield of the sample (for all species except hemp: expressed in q.ha −1 per hectare, 0% of dry matter; for hemp: expressed in tons of dry matter per hectare, 0% of dry matter).

File: data_soil_pH_2023
This file contains data of soil pH, collected at the same time, from the twelve plots, in 2009 and 2020.There are six columns: (1) years of sampling (YYYY); (2) name of the cropping system (productive with high environmental performances, PHEP; no pesticide use, No-Pest; low energy consumption, L-EN; and low greenhouse gas emissions, L-GHG); (3) number of replicate (1 to 3); (4) number of plot (1 to 12); (5) soil layer (cm); and (6) pH values.

Crop management 3.3.1. File: data_crop_sequence_2023
This file includes data on crop sequences, collected from the three replicates of the four cropping systems, over the 2009-2020 period.There are six columns: (1) year of harvest (YYYY); (2) name of the cropping system (productive with high environmental performances, PHEP; no pesticide use, No-Pest; low energy consumption, L-EN; and low greenhouse gas emissions, L-GHG); (3) number of replicate (1 to 3); (4) number of plot (1 to 12); (5) type of the crop (cover crop, CI; main crop, CR); and (6) species (for precise meanings see file "glossary_species").

Experimental Design; Materials and Methods
The metadata were classified in six groups: (1) the innovative cropping systems and the field trial; (2) the plant measurements; (3) the soil properties; (4) the agricultural practices; (5) the environmental indicators; and (6) the climate.

The innovative cropping systems and the field trial
The four innovative cropping systems and the long-term field experiment were already widely detailed within [ 3 , 4 , 5 , 6 , 7 ].We give the main characteristics of the innovative cropping systems and the field trial in the "Supplementary Materials" section (Figure S1).

Plant measurements 4.2.1. Growth stages
We used growth decimal codes specific to each species: √ for cereals: [ 8 , 9 ], with some adaptations in table as follows: • to take into account the 0 before the number, e.g. for 9, we wrote x before 09 resulting in x09.

Glossary of growth stages
Some customizations were added for cereals, legumes, rape, and linseed.

Plant biomass and nitrogen content
Plant biomass resulted from oven drying, at 80 °C for 48 hours, of each plant sample.Due to the cost of nitrogen content analysis, two or three samples, depending on species and growth stage, were pooled and ground.A subsample was analyzed following the Dumas combustion method [16] .

4.2.3.1.
Crops.For all crops, samples were collected at the beginning of flowering and at maturity, except for winter rape for which samples were gathered at stage 8.0 [14] .There were some supplementary collection periods for oilseed and cereal species: √ oilseed species (winter rape, winter linseed): aboveground parts and taproots were collected both before and after winter; √ cereals (barley, oat, triticale, wheat): aboveground parts were collected at the beginning of stem extension.
Depending on measurement dates and species, there were: √ various numbers of samples: six samples until flowering stage, and nine to twelve samples at maturity.At maturity, samples were also used for yield component measurements.There are some peculiarities of samples.At maturity, due to the high aboveground biomass for maize every year, except in 2009, each sample was divided into two subsamples (called A and B).For the same reason, in 2010, the samples were halved for the productive with high environmental performances system (plot 10; sample 2), for the low energy consumption system (plot 12; samples 7 and 8), and for the low greenhouse gas emissions system (plot 6; sample 4).The second subsample was called "_bis"; √ various sizes of samples: two adjacent rows of one meter resulted in various size samples (0.25 m ² to 3 m ²) depending on the seeder machine (see metadata of agricultural practices, Table 1 ).There was a peculiarity in 2009: 5.22 m ² for the maize sample in the no pesticide use system.The sampling method used at maturity is provided in the section "Yield components".For all crops, at maturity, kernels were separated from the vegetative parts of the plant, i.e. straws and pod walls for legumes (stems_pods), straws and rachis for cereals (straws_rachis_ears), straws and panicles for oat (straws_panicles), and stalks and cobs for maize (stalks_cobs).For rape, the different aboveground parts (stems, pods and green seeds) were pooled.

Cover crops, volunteers, and weeds.
Six samples of 1 m ² were taken in the autumn (from mid-November to mid-December).Sometimes, each species of the cover crop mixture was weighted separately.As we were required to simulate soil carbon sequestration, some estimations were provided for missing data: in 2009 for plots 1, 2, 5, 8, and 9; in 2010 for plots 7, 8, and 10; in 2011 for plots 4, 8, 9, and 10; in 2012 for plot 12.
Depending on their growth, we also collected volunteers and weeds with the same method, i.e. six samples of 1m ² each.

Yield components
For all species except maize, and due to the difficulties of separating the plants at maturity, the number of plants were counted early using samples dedicated to the biomass measurements: √ for cereals: at the beginning of tillering (stage BBCH 21 [ 8 , 9 ] i.e. mid-March) or over the spring, √ for legumes: at the beginning of flowering or at maturity (stages BBCH 61 and 92 respectively [ 9 , 10 , 13 ]), √ for linseed: at the end of winter or beginning of spring), based on 6 to 7 samples.
Sometime, the number of plants were managed at maturity, but with less accuracy.For maize, the number of plants were counted at maturity (stage BBCH 92 [ 9 , 10 ]).In 2019, there was one supplementary counting in June.
For the other yield components, nine to twelve samples were collected at maturity (stage BBCH 92 [10] ), and three more samples (1_0N, 2_0N, 3_0N) were harvested in a specific nonfertilized area.These samples were also used to measure aboveground biomass and N content.For winter rape, counting was done at stage 8.0 [14] to avoid losses of dried pods which occurred at maturity.Area sizes were two adjacent rows of one meter for cereals and legumes, two adjacent rows of 2.5 meters for maize, and 0.5 m ² and 1 m ² for linseed and winter rape respectively.Surface areas varied according to the seeder machine (see metadata on agricultural practices in Table 1 ).All plants (aboveground parts and roots, or taproots for winter rape) were collected from the field trial, except for maize for which only aerial parts were harvested.In laboratory, roots were removed from the samples, and number of branches were counted.
For all species, except for winter rape, reproductive and vegetative parts were separated (see metadata on "Aboveground biomass and N content").Depending on the species, either a subsample (linseed, cereals) or the whole sample of each kernel sample was used to calculate the thousand-kernels weight (gram; 0% of dry matter).
Depending on the species, there were some specific counting.
For linseed, we counted: (1) the number of fertile branches (with capsules with at least one kernel) and sterile branches (without capsule, or with capsules without kernel); and (2) the number of fertile capsules (with kernels) and sterile capsules (without kernel).
For cereals, at the beginning of tillering, from each sample a subsample of 20 plants was used to count number of tillers with more than three sub-tillers.There were some sample peculiarities as follows: (1) in 2009, there were 12 samples for spring oat (plot 5); (2) in 2009, due to take-all disease on winter wheat (plot 11), three samples (1_PE, 2_PE, 3_PE) were collected from the diseased area; (3) in 2010, due to the large plant biomasses of winter wheat, two subsamples were collected and called "_bis" (plot 6, sample 4; plot 10, sample 2; plot 12, samples 7 and 8); and (4) in 2020, due to growth problems for winter wheat (plots 4, 8 and 12), spring barley (plot 7), and triticale (plots 2 and 9), no yield components were provided, except for the total number of plants.For spring barley, there were nine samples.
For legumes, the number of fertile pods (with kernels) and the number of sterile pods (without kernel) were counted.
For maize, the specific counting were as follows: (1) the number of fertile cobs (with kernels); (2) the number of all cobs (fertile and sterile cobs); (3) the average number of rows per cob, resulting from the mean of the row numbers counted from all the cobs of the sample.In 2009, samples 13, 14, and 15 corresponded to an area where there was a second sowing.

Yield harvested with a combine harvester
Yield.Six samples per plot were collected, each year, at maturity, with a combine harvester.Sample surfaces ranged from 75 m ² to 140 m ², depending on the harvester (i.e.widths of the cutter bar were 1.5 m for linseed, 4 m for maize, and 3 m for all other crops), and the length of the harvested plot (i.e. to avoid border effects we excluded 6 to 8 m on each side).Each kernel sample was weighted separately.From each sample, a subsample of almost 500 grams was quickly collected to measure the moisture (% of dry matter; the subsamples were ovendried at 80 °C for 48 hours).Yield values (q.ha −1 , 0% of dry matter for all species, except for hemp) were calculated as the ratio between the kernel weight and the surface harvested.
Thousand-kernels weight.After the drying process of each kernel sample, a subsample of 70-80 grams was used to calculate the thousand-kernels weight (expressed in grams).
For hemp, different harvesting methods were used, depending on the combine harvester.In 2011, 2012 and 2013, only straws were harvested, while both straws and grains were harvested separately in 2017 and 2019.Yields were expressed for kernels in q.ha −1 (0% of dry matter), and for straws in ton (t) dry matter.ha−1 (0% of dry matter).Data were available in both files: "File: data_plant_biomass_nitrogen_content_2023", and "File: data_yield_combine_all_species_2023".
Particularity of soybean: due to the manual harvest in 2014, the twelve samples had a lower size than the other (almost 39 m ²).No grain moisture was measured.
In 2011 and 2012, there were 10 samples for the linseed plot.

Soil pH
Soil samples were collected according to the same method as that used in 2009 and 2020 to measure soil structural properties.The pH data were measured according to the NF ISO 10390 process (pH in water).

Soil nitrogen (nitrate and ammonia) content
Measurements were collected at three different periods over the year: at the beginning of winter around November 15; in late winter around February 15; and about eight days post harvesting of the main crop.In each plot, six soil samples were collected manually with an auger and stored in a cold box (4 °C) until analysis.Five layers were measured: 0-30 cm, 30-60 cm, 60-90 cm, 90-120 cm, and 120-150 cm.Three samples from each layer were pooled to generate two soil samples per layer for each plot.Water content was measured gravimetrically, according to the international standard method (NF ISO 11465).Analysis of nitrate (N-NO 3 − ) and ammonia (N-NH 4 + ) contents were precisely described in [7] , according to the international standard method (NF ISO 14255).Results were expressed in kg N per hectare.

Soil organic carbon content, soil total nitrogen content, bulk density, and residual soil moisture
The measurements were carried out on each replicate plot of the four cropping systems, in 2014 and 2020, for four layers ( ∼0-10 cm, ∼10-20 cm, ∼20-30 cm and ∼30-40 cm).Because the cropping practices and the crop sequence prior to 2009 (the year of the trial implementation) were homogeneous across the whole field trial, only half of the plots (i.e. the productive with high environmental performances, and low greenhouse gas emissions plots) were analyzed in 2009.Same method was applied throughout the study.

Table 4
Energy (direct and indirect) inputs, and main products (fertilizers, pesticides, and seeds) of agricultural practices.Consumptions, based on [2] took into account: (1) for farm machinery: tractor power, width of the machine or number of ploughshares, and the working hours; and (2) for pesticides: active ingredient quantities (g.kg −1 or g.l −1 ), and specific pesticide energy coefficients (0.204, 0.295, and 0.282 MJ per gram of active ingredient for fungicides, herbicides, and molluscicides respectively).

Details of agricultural practices
For hemp, harvest operation includes cutting and straw swathing.The direct seeder machine had two hoppers that allowed the sowing of two species simultaneously, one sowing and one nitrogen fertilizer spreading, or one sowing and one molluscicide spreading.
Descriptions were given for: (1) the corresponding surface of two adjacent rows of one meter for different seeders ( Table 1 ) required to compute the amounts of aboveground biomasses and the quantity of nitrogen produced per hectare; (2) the thousand-kernels weight of different species ( Table 2 ) needed to calculate the indirect energy consumption for cover crop seeding operations; and (3) the depth of soil tillage ( Table 3 ) used to calculate soil carbon sequestration.

Treatment frequency index
The treatment frequency indexes were computed according to [1] .The recommended doses, required for the calculations, were found at https://alim.agriculture.gouv.fr/ift/doses-reference/2018 .These references were regularly updated to take into account the pesticide market withdrawal.Seed treatments were excluded from the treatment frequency index computations.

Energy consumption
The energy consumption (MJ.ha −1 ) was computed annually from each plot, based on [ 2 , 17 ], and [18] .Direct energy consumptions included fuel, lubricants and electricity used to power farm machines and tractors.For farm machines, we took into account tractor power, width of the machine or number of ploughshares, and working hours.Indirect energy consumption resulted from the energy used in the manufacture, formulation, packaging and maintenance of inputs, such as machines, seeds, fertilizers and pesticides.We used specific pesticide energy coefficients for computations: 0.204, 0.295, and 0.282 MJ per gram of active ingredient for fungicides, herbicides, and molluscicides respectively ( Table 4 ).When straws were removed from the plots, energy computation took into account only swathing operations.Fossil fuel used for input transportation from the manufacturing site to the trial were not included in the computations.

Climate
The data were collected from an automated INRAE meteorological station (no.78615002: latitude 48.838 °N, longitude 1.953 °E, elevation: 125 m), located 150 m from the trial.

Limitations
Due to the COVID pandemic, no agriculture practices or measurements were recorded in spring 2020.It would therefore be difficult to include this year within plant growth model simulations.
Several measurements of pests (insects, diseases, and weeds) were managed.However, due to the workload it requires, they were collected in an irregular manner over the twelve years.

Conclusion
All these data have been used in others papers to describe the agricultural practices of the innovative cropping systems in order (1) to compare the new and the current cropping systems [ 3 , 4 , 5 ], and [6] ; to assess the ability of the four innovative systems to meet the constraints and goals [4] ; to quantify the yield in a pesticide free cropping system and the associated environmental impacts [5] ; to quantify the production of a very low-energy cropping system and its environmental performances [6] ; and to identify how these performances were reached (agronomic diagnostics were included in each paper), and the technical lock-ins that still exist.

Ethics Statement
The authors have read and followed the ethical requirements for publication in Data in Brief and hereby confirm that the current work does not involve human subjects, animal experiments, or any data collected from social media platforms.

Table 1
Characteristics of seeder machines.