Method for evaluating an agricultural input

Abstract

Method for evaluating an agricultural input The present invention relates to a method for evaluating an agricultural input, the method being characterized in that it comprises the implementation by processing means (11) of a server (1) of steps of: Obtaining the values ​​for said agricultural input of a set of descriptive parameters; For a plurality of indicators each associated with a criterion of a predefined set of criteria for evaluating said agricultural input, calculation, as a function of said descriptive parameters, of at least one score of the indicator representative of an impact of said agricultural input on the criterion to which it is associated, said score being of value between a maximum score corresponding to a maximum positive impact observed in a base of reference agricultural product productions and a minimum score corresponding to a maximum negative impact observed in said base of reference agricultural product productions;Aggregation of the scores of each indicator into an overall score. Figure for the abbreviation: Fig. 1;

Description

Title of the invention: Method for evaluating an agricultural input [0001 ] GENERAL TECHNICAL FIELD

[0002] The present invention relates to the field of computer-assisted agriculture.

[0003] More precisely, it concerns a method for evaluating an agricultural input.

[0004] STATE OF THE ART

[0005] Labeling systems are known that allow products, particularly food products, to be "rated" so as to provide the consumer with simple, reliable and intuitive information to guide them in their choice.

[0006] In particular, the Nutri-Score® is a five-level system, ranging from A to E and from green to red, established according to the nutritional value of a food product. Its aim is to encourage consumers to choose healthier products from a nutritional point of view and thus to participate in the fight against cardiovascular diseases, obesity and diabetes.

[0007] Proposed in 2014 and implemented at the initiative of the French government in 2016 as part of the law to modernize the health system, it was then taken up in other countries such as Belgium, Spain, Germany and the Netherlands, and its use is recommended by the World Health Organization.

[0008] On environmental and social aspects, the implementation of such a labelling system has recently been made compulsory, and in particular "information relating to the environmental impacts and compliance with social criteria of a good, service or category of goods or services placed on the national market", such as the CO2 equivalent.

[0009] So we have a lot of things aimed at the consumer, but in practice nothing aimed at professionals, particularly in the agricultural sector, whereas choices on this scale (seeds, fertilizers, plant protection products, etc.) can have much more impact than those of consumers, and this over a broader spectrum.

[0010] Indeed, the choice of inputs has an impact on farmers' remuneration, but also on biodiversity, the carbon footprint, and even the health quality of the final food product.

[0011] The problem is that it is not easy to evaluate these agricultural aspects, and even less to aggregate them in the form of simple, reliable and intuitive labeling, to compare with the Nutri-score® which is simply calculated according to a few numerical values ​​(calorie intake per hundred grams of product, sugar content, saturated fat content, salt content, etc.).

[0012] Moreover, while for the Nutri-score® we can simply analyze the com- position of the product, the same analysis for an agricultural input will provide little information. Indeed, a plant protection product that is "less harmful" to the environment may ultimately prove ineffective and have more serious implications for the health qualities of agricultural production or the quality of life of the farmer.

[0013] The present invention improves the situation. PRESENTATION OF THE INVENTION

[0014] The present invention provides a method for evaluating an agricultural input, the method being characterized in that it comprises the implementation by processing means of a server of steps of:

[0015] a. Obtaining values ​​for said agricultural input from a set of descriptive parameters; b. For a plurality of indicators each associated with a criterion of a predefined set of evaluation criteria for said agricultural input, calculation, based on said descriptive parameters, of at least one score of the indicator representative of an impact of said agricultural input on the criterion with which it is associated, said score having a value between a maximum score corresponding to a maximum positive impact observed in a base of productions of reference agricultural products and a minimum score corresponding to a maximum negative impact observed in said base of productions of reference agricultural products; c. Aggregation of said scores for each indicator into an overall score.

[0016] According to advantageous and non-limiting characteristics:

[0017] Said indicator score presents a predefined intermediate value corresponding to a neutral impact observed in said base of production of reference agricultural products.

[0018] Said input is chosen from a seed, a plant protection product, a plant nutrition product and an agricultural service.

[0019] Said predefined set of evaluation criteria for said agricultural input comprises the following criteria:

[0020] - Sanitary qualities - Nutritional qualities - Fair and sustainable remuneration - Quality of life - Carbon - Biodiversity

[0021] The health quality criterion is associated with the indicators:

[0022] - Produce without GMOs - Aim for no residue - Produce without pathogenic molecules that are toxic to health

[0023] The nutritional qualities criterion is associated with the indicators:

[0024] - Produce more plant proteins - Produce more unsaturated fatty acids, especially Omega 3 - Produce flawless wines - Encourage diversity of productions - Encourage atypical productions

[0025] The carbon criterion is associated with the indicators:

[0026] - Reduce the carbon footprint by favoring inputs / services with low GHG emissions (manufacturing + use) - Reduce the carbon footprint by promoting inputs / services with higher nitrogen efficiency - Participate in carbon storage in the soil by favoring a significant return of biomass to the soil - Promote inputs / services with high energy recovery - Be resilient to water and thermal stress - Implement inputs / services to reduce the risk of erosion (carbon)

[0027] The biodiversity criterion is associated with the indicators:

[0028] - Limit the risk of toxicity to the environment - Avoid or reduce synthetic phytopharmaceutical treatments - Limit the risk to bees - Promote food supply for pollinators - Promote cultivated biodiversity - Reduce the risk of the presence of trace metal elements in soils - Prioritize inputs / services that limit the risk of soil contamination - Participate in the increase of organic matter by favoring a significant potential for returning biomass to the soil - Prioritize inputs / services that are least dangerous for earthworms

[0029] The fair and sustainable remuneration criterion is associated with the indicators:

[0030] - Make the economic investment of the input / service profitable - Access markets of specific technological quality - Access to markets valued by the UAB mention - Access markets valued by compatibility with labels or notebooks charges - Favor low volatility of the purchase price - Sow crops with a stable selling price - Ensure reliable production despite hazards

[0031] The quality of life criterion is associated with the indicators:

[0032] - Limit the number of sprayer outputs - Limit the risk of re-sowing - Reduce mental load through good flexibility in input / service positioning - Limit the impact on the health of the applicator (IRSA, Dephyto) - Promote inputs / services with a positive image (UAB, biocontrol) - Reduce the mental load through weak regulatory constraints - Reduce mental load through good selectivity of input.

[0033] There is at least one indicator per evaluation criterion of said agricultural input of the predefined set, step (c) comprising the calculation of a score of each evaluation criterion from said scores of each indicator associated with said criterion, then the calculation of said overall score from the scores of each evaluation criterion.

[0034] Step (b) comprises calculating a plurality of sub-scores of the indicator, each representative of an impact at a given level of said input on the criterion with which it is associated, the sub-scores of the indicator being aggregated into the score of the indicator.

[0035] There are four sub-scores of the indicator respectively representative of an impact:

[0036] - of the input market, - from the input segment, - the composition of the input, - of the input itself.

[0037] Each sub-score of the indicator either has a value or is “not applicable”, the score of the indicator being calculated as an average of the sub-scores having a value weighted with a number of points of the level.

[0038] The method comprises a step (d) of marking a package of said input with said overall score.

[0039] According to a second aspect, the invention relates to a method for evaluating agricultural production involving the use of a set of agricultural inputs, the method being characterized in that it comprises the implementation by processing means of a server of steps of:

[0040] A. For each input of said set, implementing the method according to the first aspect so as to obtain an overall score of said input. B. Aggregation of said overall scores of each input of said set into a total score.

[0041] According to a third and a fourth aspect, the invention relates to a computer program product comprising code instructions for executing a method according to the first or second aspect of evaluating an agricultural input or an agricultural production; and a storage means readable by an electronic equipment computer software in which a computer program product comprises code instructions for carrying out a process according to the first or second aspect of evaluating an agricultural input or agricultural output. BRIEF DESCRIPTION OF THE FIGURES

[0042] Other characteristics and advantages of the present invention will appear on reading the following description of a preferred embodiment. This description will be given with reference to the appended drawings in which:

[0043] [Fig. 1] is a diagram of an architecture for implementing the method according to the invention;

[0044] [Fig.2] represents the steps of a preferred embodiment of the method according to the invention.

[0045] DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT

[0046] The present method for evaluating an agricultural input is implemented within an architecture such as represented by [Fig.l], comprising a server 1 and generally at least one client 2. The server 1 is at least one piece of equipment implementing the processing steps, and the client 2 is equipment for viewing and / or using the evaluation results, for example equipment for labeling the agricultural product. Note that by "server" 1 we can mean in practice several remote pieces of equipment sharing the tasks, and we can in particular have a server dedicated to storing a database of productions of reference agricultural products. For convenience, it will be assumed in the remainder of this description that the server 1 is a single piece of equipment.

[0047] Each equipment 1, 2 is typically a remote computer equipment connected to a local network or a wide area network such as the Internet network for the exchange of data. Each comprises data processing means 11, 21 of the processor type, and data storage means 12, 22 such as a computer memory, for example a flash memory or a hard disk. The client 2 typically comprises a user interface 23 with display means such as a screen for interaction, this may be for example a mobile terminal.

[0048] By agricultural input, we mean all the products and services used by farmers to grow their crops, i.e. seeds, plant protection products, plant nutrition products, agricultural services.

[0049] Plant protection products (abbreviated as PPP in the remainder of this description) designate in particular plant protection products (commonly called phytosanitary products) intended in particular to protect plants against all harmful organisms (pests, pathogens) or to prevent their action, to destroy undesirable plants (weeds), but also to limit stress biotics undergone by the plant via stimulation of its defenses. Plant nutrition products include in particular fertilizers and biostimulants (these two subcategories will be treated separately in the rest of the description). Agricultural services include, for example, decision support tools, precision agriculture, etc. Thus, it will be understood that for convenience, the concept of agricultural input also covers the concept of agricultural service, which is not a "physical" product but has an impact. In this description, the term "product" will be found as a synonym for input.

[0050] “The evaluation” of an input is understood in the broad sense, and more precisely with regard to different identified consumer expectations. These expectations are three in number: Food, Environment and Farmer. To rephrase further, this process is a process for evaluating an agricultural input in terms of its impact on food, the environment and the farmer.

[0051] By evaluation of the agricultural input we mean the rating of said input with respect to said expectations at the same time, i.e. without favoring one expectation over another: all expectations must be met as best as possible for the product to be judged to be of "quality". The output of the present method is an overall score between a minimum value and a maximum value, in particular between 0 and 100. The higher the score, the more said expectations are considered to be met.

[0052] The aim of this evaluation is to be able to compare the inputs in an objective manner, i.e. by making an order relationship possible.

[0053] In practice, the input is evaluated via the consequences it will have in the production of an agricultural product (i.e. any product resulting from agricultural production, without processing, for example a cereal). Indeed, rather than reasoning on the input as a chemical product for example, the present method proposes to exhaustively observe the agricultural products obtained using or not using this input, and to deduce the impact of the latter.

[0054] To have an overall view, the present method defines “specific issues” which are criteria for evaluating the quality of said agricultural inputs specifically targeted and each linked to one of the expectations. A set of criteria for evaluating the quality of said predefined agricultural input is assumed, and in particular the following 6 criteria:

[0055] - Health qualities - linked to food expectations (no pathogens, residues of phytopharmaceutical products, presence of toxic molecules, etc.) - Nutritional qualities - related to the expectation of food (providing in adequate quantities the various nutrients necessary for the health and well-being of an individual) - Fair and sustainable remuneration - linked to the farmer's expectations (allowing the farmer to live with dignity from his work) - Quality of life - linked to farmer expectations (controlled working conditions and hours) - Carbon - linked to environmental expectations (low CO2 footprint and ability to produce despite climate change) - Biodiversity - linked to environmental expectations (promotes the complexity and richness of living beings and ecosystems)

[0056] Input data

[0057] The present method of an agricultural input is implemented by the processing means 11 of the server 1 and begins with a step (a) of obtaining the values ​​for said input of a set of descriptive parameters, these parameters being called “references”. It is understood that said parameters are generic regardless of the input, however there are advantageously lists by input segment (seed, PPP, fertilizer, etc.).

[0058] The values ​​of the parameters can be either measured directly, or entered by a farmer, or directly retrieved from a base of observed values ​​of said parameters (for a plurality of real productions of various agricultural products), called a learning base, in particular stored on the data storage means 12 of the server 2. For example, for a given seed variety, the value of a protein content parameter does not have to be entered if it is known for this variety: the data processing means 11 can directly read it from said base of observed values ​​of said parameters as a function of the variety.

[0059] These values ​​can be a boolean (yes / no), one of several given classes, or a numeric value in a predefined unit.

[0060] Very advantageously, here is a possible list of descriptive parameters of an input, with a reference identifier, sorted by type

[0061] REFERENCES ON SEED VARIETIES

[0062] - Culture (REF073) - Description: Seed culture. Link with the Culture reference. - Seed available in AB (REF001) - Description: Variety usable in Organic Agriculture Yes / No - Status Cover mix (REF002) - Description: Seeds corresponding to a cover mix Yes / No - Companion plant status (REF003) - Description: Seeds corresponding to a companion plant pack Yes / No - Certified Seed Status (REF004) - Description: Certified Seed Yes / No Protein richness (REF005) - Description: Protein richness of the variety, expressed in class from 1 to 9. Omega 6 and Omega 3 Contents (REF006) - Description: Average grain Omega 6 content and average grain Omega 3 content. Both data are expressed in g / 100 g. Technological class (REF007) - Description: Classification of the variety according to its technological characteristics. • Soft winter wheat - 5 classes: • Strength Improving Wheat (SIF) • Superior Bread Wheat (BPS) • Bread Wheat (BP) • Biscuit Wheat (BB) • Other • Durum wheat - 8 classes: • Elite Durum Wheat • HQ Durum Wheat • Durum Wheat Color • Quality Durum Wheat • Durum Wheat Protein • Medium Durum Wheat • Standard Durum Wheat • Fair Durum Wheat • Barley - 3 classes: • Barley superior to the control (class A) • Barley equivalent to the control (class B) • Barley lower than the control / fodder (class F) • Rapeseed and Sunflower - 2 classes: • Variety rich in oil • Other variety • Protein peas - 2 classes: • Variety rich in protein • Other variety GMO Status (REF008) - Description: GMO Variety Yes / No VTH Status (REF009) - Description: Herbicide tolerant variety Yes / No. Potentially affected crops are: Sunflower, Rapeseed, Beetroot, Corn. Status Conservation variety (REF010) - Description: Variety registered on the GNIS list of conservation varieties Yes / No. CEPP variety note (REF012) - Description: Note associated with the variety within the framework of the Certificates of Economy of Phytosanitary Products (CEPP), expressed per number of grains or per kg. Variety Market Share (REFOI4) - Description: Percentage of the crop market covered by the variety. Link to the Crop Reference. Nitrogen requirement coefficients b of the wheat variety (REFOI5) - Description: Unit nitrogen requirement coefficient (coef b) of the wheat variety. Average sowing rate of the variety (REF077) - Description: Average sowing rate of the variety in kg of seeds / ha or in number of grains or in doses / ha Average gross margin (REF079) - Description: Average gross margin of the variety, expressed in € / ha. Covering power of the variety (REF084) - Description: Covering power of the variety, assessed using a score from 1 (= very low) to 9 (= very high). For some crops, several covering power ratings may be carried out, at different stages. Varietal type (REF085) - Description: Type of variety, either line or hybrid. Leaf habit of the variety (REF087) - Description: Classification of the variety according to its characteristics in terms of leaf habit. 5 classes can be distinguished: • Upright leaf habit • Semi-erect leaf shape • Leaf shape semi-erect to semi-drooping or semi-spreading • Semi-drooping or semi-spreading leaf shape • Leaf shape drooping or spreading Fusarium wilt resistance score (REF092) - Description: Fusarium wilt resistance score of the variety, from 1 to 9. Ergot Resistance Score (REF093) - Description: Ergot resistance score of the variety, from 1 to 9. Panel price (REF068) - Description: Panel price of the variety over the last 5 campaigns, expressed in € / product unit. Variety cold resistance score (REF113) - Description: Variety cold resistance score, rated from 1 (= very sensitive) to 9 (= resistant). Variety water stress sensitivity (REF114) - Description: Variety water stress sensitivity, categorized into 3 classes: • Variety sensitive to fairly sensitive to water stress = 1 • Variety moderately sensitive to water stress = 2 • Variety little to very little sensitive to water stress = 3

[0063] REFERENCES ON PLANT PROTECTION PRODUCTS (PPP)

[0064] - PPP Segment (REFOI6) - Description: PPP Market Segment: Herbicide / Fungicide / Insecticide / Molluscicide / Regulator / Adjuvant / Acaricide - Average PPP dose (REF017) - Description: Average applied dose of PPP per hectare, according to Panel statistics. - PPP application mode (REF018) - Description: Possible PPP application modes: • Seed Treatment (TS): Yes / No • Foliar treatment: Yes / No - PPP adjuvant status (REF019) - Description: PPP formulated with an adjuvant Yes / No - Biocontrol Status (REF020) - Description: Belongs to the official list of biocontrol products Yes / No - UAB status (REF021) - Description: PPP usable in Organic Agriculture Yes / No - Authorized crops (REF022) - Description: List of crops on which the PPP is approved - Dephyto indicators: IRSA and IRTE (REF023) - Description: Indicators of danger to human health (IRSA) and ecotoxicity (IRTE) of the PPP applied at its average dose. - LD50 concentration "bee" of the active substance (REF024) - Honeybees concentration - Contact acute LD^^, expressed in mg / kg - Persistence in soil of the active substance in soil DT50 field and DT50 lab (REF025) - Description: Time after which the quantity of active substance is reduced by half by natural degradation (measured in the field if DT50 field or under controlled conditions if DT50 lab) - Organic carbon - water partition coefficient Koc and Kfoc (REF026) - Organic carbon / water partition coefficient, giving an indication of the ability of the active substance to be adsorbed onto soil organic matter - LC50 concentration "earthworms" of the active substance (REF027) - Description: Concentration Earthworms - Acute 14 day LC^^, expressed in mg / kg - Cautionary phrase SPe8 (REF028) - Description: Presence of the cautionary phrase SPe8 (bees) on the PPP: Yes / No - Mention Bees (REF029) - Description: Exemption from use for products with the Spe8 warning phrase. 3 possible labels: • 1 - “Use authorized during flowering outside the presence of bees » • 2 - “Use authorized during periods of exudate production, apart from the presence of bees" • 3 - “Use authorized during flowering and during periods of production of exudates, outside the presence of bees" Hazard statements (REF030) - Description: List of PPP Hazard statements according to CLP regulations Composition of PPP (REF031) - Description: Composition of PPP in active substances and content of these substances. Component type (REF086) - Description: Typology of the substance composing the PPP: • Chemical • Microorganism • Macro-organism • Etc. Chemical family of the active substance (REF032) - Description: Chemical family of the active substance: • Triazole? Yes / No • Folpel? Yes / No • Copper? Yes / No • Sulfur? Yes / No • Zinc? Yes / No Status Controversial substance of the active substance (REF033) - Description: Controversial substance likely to be prohibited in charter or label specifications (Yes / No). Status of active substance residues (REF034) - Description: Belonging of the active substance to one of the following lists: • List A: active substances quantified at values ​​around 10 ppb = “ZRP” threshold • List B: active substances detected but poorly quantified (around 5 ppb) or source of cross-contamination • List C: all other substances PPP Herbicide Selectivity Rating (REF035) - Description: From 1-Non-selective to 5-Very Selective ZNT and riparian ZNT (REF036) - Description: Value of the maximum ZNT (Untreated Zone) watercourse and the maximum riparian ZNT of the PPP DRE (REF090) - Description: Time to re-enter the plot after maximum application of the PPP, expressed in hours CEPP PPP rating (REF037) - Description: Rating associated with the product within the framework of the Certificates of Economy of Phytosanitary Products (CEPP) BBCH min and BBCH max (REF038) - Description: Min and max crop development stages of use. Expressed according to the BBCH scale, from 0 to 99. Persistence class (REF039) - Description: Persistence of action of the PPP, qualitative scale from 1-Very little persistent to 5-Very persistent. Urgency level of use (REF072): Description: Urgency level of use, according to the DGAL classification: PI Emergency / PI / P2 short term / P2 / Others PPP Trace Metal Element (TME) Content (REF075) - Description: Sum of the Trace Metal Element (TME) Contents of the PPP in g / g of product or in g / g of active substance, namely Cd, Cu, Zn, Pb, Ni, Cr and Hg PPP herbicide with anti-dicotyledonous spectrum (REF076) - Description: PPP herbicide with a spectrum of action on dicotyledonous weeds Yes / No Application flexibility (REF060): Description: Ability of the product to maintain its level of performance in the face of pedoclimatic hazards at the time of its application. Qualitative scale from 1 = not very flexible to 5 = very flexible therefore reliable. Average gross margin (REF080) - Description: Average gross margin of the PPP, expressed in € / ha. Average herbicide efficacy (REF081) - Description: Average efficacy of the herbicide PPP, expressed in %. Use of Seed Treatment (REF089) - Description: Description of the use of the Seed Treatment: Crow Repellent / Mushrooms other than Pythiaceae / Mushrooms (Pythiaceae) / Other / None Use of PPP (REF094) - Description: Description of the PPP use Average score of the Vine PPP (REF095) - Description: Average of the scores between the effectiveness of the Vine PPP (between 1 = insufficient effectiveness and 5 = effectiveness close to 100%) and its cost / ha (1 = competitive, 5 = not very competitive). Pathogenic risk (REF091) - Description: Use concerned by a pathogenic risk on human health: Yes / No Direct Pathogenic Efficacy (REF096) - Description: Average efficacy of the PPP on human health pathogens, expressed between 50 and 100. Indirect pathogenic efficacy (REF097) - Description: Efficacy of the PPP on reservoirs of human health pathogens, equivalent to the market reference Yes / No. - Active substance emission factor (REF100) - Description: Greenhouse gas emission factor associated with the manufacture and transport of the active substance, expressed in kgCO2e / kg of substance - Average price of the segment (REF064) - Description: Average price index of the PPP segment over the last 5 years, without unit. - Panel price (REF066) - Description: Panel price of the PPP over the last 5 campaigns, expressed in € / product unit.

[0065] REFERENCES ON FERTILIZERS

[0066] - Fertilizer type (REF040) - Description: Characterization of the fertilizer type in the Organic / Organo-mineral / Mineral list - Type of organic fertilizer (REF041) - Description: Characterization of the type of organic fertilizer according to the C / N ratio: Type I (C / N > 8) or Type II (C / N < 8) - Starter Fertilizer Status (REF042) - Description: Starter type fertilizer = applied at sowing Yes / No - Composition of the fertilizer (REF043) - Description: • For all fertilizers: presence Yes / No of each of the following fertilizing elements: • Nitrogen • Phosphorus • Potassium • Magnesium • Calcium • Quicklime • For organic or organo-mineral fertilizers: • Nitrogen content NH4 in kg / kg of product - Form of mineral fertilizer (REF044) - Description: Characterization of the form of the mineral fertilizer: Liquid or Solid - Form of mineral nitrogen fertilizer (REF045) - Description: Characterization of the form of mineral nitrogen fertilizer: • Urea • Urea with urease inhibitor • Solution • Ammonium nitrate • Other form - UAB status of the fertilizer (REF046) - Description: Fertilizer usable in Organic Agriculture Yes / No - ETM content of the fertilizer (REF074) - Description: Sum of the contents in Trace Metal Elements (TME) of the fertilizer in g / g DM, namely Cd, Cu, Zn, Pb, Ni, Cr and Hg - Average application rate of fertilizer (REF099) - Description: Average application rate, in kg / ha, of each main fertilizing element: • Nitrogen • Phosphorus • Potassium • Magnesium • Calcium

[0067] A single dose per element, valid for all fertilizer products.

[0068] - Fertilizer element emission factor (REF101) - Description: Greenhouse gas emission factor associated with the manufacture and transport of the element, expressed in kgCO2e / kg of element - Spreading emission factors (REF103) - Description: Greenhouse gas emission factors associated with the use of fertilizer, expressed in kgCO2e / kgN: • direct N2O emissions • indirect emissions of N2O via the volatilization process (expressed in kgCO2e / kg of product for organic fertilizers) • indirect emissions of N2O via the leaching process - Humification (REF109) - Description: Parameters for calculating the quantity of carbon humified following the application of organic fertilizer: • Carbon content of the fertilizer, expressed in kg / t • Humification coefficient - Average price of fertilizer type (REF065) - Description: Average price index of fertilizer type over the last 5 years, without unit. - Panel price (REF067) - Description: Panel price of the fertilizer over the last 5 campaigns, expressed in € / unit of product. - Persistence in the soil of the element DT50 field and DT50 lab (REF110) - Description: Time after which the quantity of element is reduced by half by natural degradation (measured in the field if DT50 field or in controlled conditions if DT50 lab) - Organic carbon - water partition coefficient Koc and Kfoc (REF111) - Description: Organic carbon / water partition coefficient, giving an indication of the element's ability to be adsorbed onto soil organic matter

[0069] REFERENCES ON CULTURES

[0070] - ETM content of the culture (REF011) - Description: Sum of the contents in Trace Metal Elements (TME) of the culture in g / g DM, namely Cd, Cu, Zn, Pb, Ni, Cr and Hg Cultural composition of the mixture (REFOI3) - Description: In the case of a cultural mixture, composition of the product in crops and percentage of these different crops. Crop group (REF047) - Description: Membership of the crop to a functional group, according to the characteristics and outlets of the species. E.g.: wheat, cereals, straw cereals, oilseeds, protein crops, legumes, monocotyledons, dicotyledons, etc. A crop can belong to several groups. Protein percentage (REF048) - Description: Average protein content of the grain, expressed as a %. Omega 6 and Omega 3 Contents (REF049) - Description: Average grain Omega 6 content and average grain Omega 3 content. Both data are expressed in g / 100 g. Average yield (REF050) - Description: Average yield of the crop, expressed in q / ha or t / ha. Average yields over the last 5 years (REF069) - Description: Average crop yields over the last 5 years, expressed in q / ha or t / ha. Average IFT (REF051) - Description: Average Treatment Frequency Index (TFI) of the crop Average gross margin (REF052) - Description: Average gross margin of the crop, expressed in € / ha. % national UAA (REF053) - Description: Useful Agricultural Area (UAA) sown with crops on French territory, as a % of the total UAA. Sowing window (REF054) - Description: Length in days of the period during which it is possible to sow the crop. Nitrogen requirement coefficients a and b (REF055) - Description: Fixed (coef a) and unit (coef b) nitrogen requirement coefficients of the crop. Coefficient b is reduced to a tonne equivalent, because yields are expressed in t / ha. Mineralization of residues from the previous Mr (REF056) - Description: Quantity of nitrogen supplied to the system by the mineralization of crop residues, expressed in kg / ha. Mineralization of intermediate crop residues MrCi (REF057) - Description: Quantity of nitrogen supplied to the system by the mineralization of intermediate crop residues, expressed in kg / ha. Annual nectar production of the crop (REF058) - Description: Potential nectar production of the crop, expressed in kg / ha / year Annual pollen production of the crop (REF071) - Description: Potential pollen production of the crop, expressed in kg / ha / year Flowering period of the crop (REF059) - Description: Flowering period of the crop, in two pieces of information: • Calendar month of start of flowering (month number) • Calendar month of end of flowering (month number) Crop for human consumption (REF070) - Description: Characterization of the crop's destination for human consumption: Yes / No. Rooted crop (REF078) - Description: Characterization of the crop, depending on whether it can be rooted (Yes) or not rooted (No). Crop Type (REF082) - Description: Characterization of the crop, depending on whether it is a main crop or an intermediate crop. The majority use will be retained for crops likely to belong to both classes. Average sowing density of the crop (REF083) - Description: Average sowing density of the crop, expressed in number of grains / ha. Crop Re-sowing Risk Rating (REFO88) - Description: Assessment of the risk of re-sowing the crop, taking into account the biotic and abiotic stresses inherent to sowing. Qualitative scale from 1 = very high risk to 5 = very low risk Type of crop outlets (REF098) - Description: Characterization of the type of crop outlets according to 4 classes: • Crops primarily for food production • Crops mainly for food but also having an energy outlet such as biofuel or methanization • Crops mainly for energy purposes but also having a food outlet • Crops mainly for energy purposes Crop Emission Factor (REF102) - Description: Greenhouse Gas Emission Factor associated with the manufacturing and transportation of the crop, expressed in kgCO2e / kg Organic Matter (OM) rate of the culture (REF104) - Description: Organic Matter (OM) rate of the culture, in % of the DM of the culture. Crop DM yield (REF105) - Description: Crop dry matter tonnage in tDM / ha. Methanogenic potential of the crop (REF106) - Description: Methanogenic potential of the crop in Nm3CH4 / tMO. Liquid Energy Conversion Efficiency (REF107) - Description: Liquid energy conversion efficiency of the produced methane. Biomass restitutions (REF108) - Description: Parameters for calculating the restitutions of aerial and root biomass of the crop: Harvest index Fraction of dry matter of the harvested crop ratio of underground residues / aboveground biomass Root correction coefficient of intermediate crops Average price (REF063) - Description: Average price index of culture over the last 5 years, without unit. Crop sensitivity to water and heat stress (REF112) - Description: Crop sensitivity to water and heat stress, assessed using a qualitative scale in 5 classes: Sensitive culture = 1 Fairly sensitive culture = 2 Medium sensitive culture = 3 Low sensitivity culture = 4 Very low sensitivity culture = 5 Possible exemption for AB (REF115) - Description: Crop with an exemption allowing the use of non-AB seeds in Organic Agriculture Yes / No Crop affected by a pathogenic risk (REFOI9) - Description: Crop affected by a pathogenic risk to human health Yes / No

[0071]

[0072] OTHER REFERENCES Input segment (REF061) - Description: Segment characterization to which the input belongs: Seeds / PPP / Ferti / Biostimulant Biostimulant Claim (REF062) - Description: Action claim associated with a Biostimulant type product: Soil activator / Biofertilizer / Other

[0073] Indicators

[0074] In a step (b), for a plurality of indicators each associated with a criterion from the set of evaluation criteria of said agricultural input mentioned above (the 6 criteria, but there could be more), at least one score of the indicator representative of an impact is calculated from said values ​​for the input of the descriptive parameters (when used in agricultural production) of said input on the criterion with which it is associated, and this in a rather original way.

[0075] More precisely, each criterion remains subjective and difficult to evaluate intrinsically. The indicators associated with each criterion are levers which can be seen as components of the criterion that are much simpler to quantify. More precisely, each indicator is formulated as an objective and for each indicator selected, a score representative of the impact of said input on the criterion with which it is associated can be calculated, corresponding to the achievement or not of said objective. This impact can be negative or positive. For example, contributing to the complete absence of residues of plant protection products due to a policy of substitution of risky molecules will have a strong positive impact on the "sanitary qualities" criterion, while being subjected to the possible presence of pathogens due to the chosen crop will have a strong negative impact.

[0076] At least one indicator is used per criterion, and said indicator score is at a value between a maximum score corresponding to a maximum positive impact observed in said learning base mentioned before (bases of real production of agricultural products) and a minimum score corresponding to a maximum negative impact observed in said learning base. In the middle, there is an intermediate score corresponding to a neutral impact. The score can be evaluated with a functional unit of surface (one hectare) to normalize the impacts.

[0077] For example, if the rating is reported on a scale of 0 to 100, we can define:

[0078] 0 (minimum value) = maximum negative impact

[0079] 50 (intermediate value) = neutral impact

[0080] 100 (maximum value) = maximum positive impact

[0081] Note that the maximum negative and positive impacts may be those “observed until now”, and therefore potentially be exceeded in the future, so that a margin can be provided, for example by arbitrarily defining that the minimum value is 10 and the maximum value is 90 (or any other value chosen by the person skilled in the art). Thus, if the learning base is subsequently enriched with a new example of real production of agricultural product in which the observed impact is even better, it will be possible, for example, to keep the scale and have a new maximum negative impact with a value of 95. Alternatively, in the event of enrichment of the database, the scale can be recalculated between the minimum and maximum values ​​(keeping the intermediate value corresponding to the neutral impact).

[0082] It is therefore understood that the present method is indeed based on learning corresponding to real productions using various inputs. In other words, we have a quantification of the impacts based on the average practices observed in the field (use of real data), and not only on a potential impact.

[0083] Each indicator is calculated based on some of said descriptive parameters (those which are relevant), and is defined by a calculation rule designed to respect the above principle (value between a maximum score corresponding to a maximum positive impact observed and a minimum score corresponding to a maximum negative impact observed). We will see examples later.

[0084] Preferably, the score of each indicator is divided into a plurality (in particular four) evaluation levels (rated from 1 to X, and defining X "NOTX" sub-scores) contributing advantageously in an equivalent share. These various levels typically correspond to various "scales" of impact of the input for the indicator (for example impact of the input segment vs. impact of the input itself compared to other inputs in the same segment) to facilitate calculations and respect the hierarchy between scales.

[0085] We will see later a strategy for combining the sub-scores into a single score.

[0086] In all cases, the calculation of a sub-score (or of the score directly if there is no sub-score) translates as explained a “rate” of impact observed in the learning base.

[0087] For some of the indicators below, the rating is based on a linear regression principle.

[0088] This consists of using a reference data or an intermediate data calculated for the needs of the indicator and transforming this data into a score between the minimum score and the maximum score in a linear manner. When the minimum and maximum scores are fixed, the equation allowing the transition from the data to the score is described directly in the calculation rules, but sometimes these limits are relative and depend on the values ​​taken by the data in the entire product database.

[0089] Preferably, there are four levels of evaluation which are:

[0090] 1. Impact of the input market: Seed / Plant protection product (PPP) / Fertilizer 2. Impact of the input segment: crop family (cereals, oilseeds, etc.) or Plant protection product segment (fungicides, herbicides, etc.) 3. Impact of the composition of the input: crop, active substance or substance of interest 4. Impact of the input itself: variety or plant protection product formula

[0091] Each indicator score is calculated as a percentage of the number of points at stake per level (in other words, the maximum score is divided between the levels). In the simple case where the contributions are identical per level (same number of points at stake, i.e. same fraction of the maximum score), we can simply take the average of the sub-scores having a value, i.e. a number of points, and not NA, i.e. “not applicable”. This means that the sub-score is not quantifiable (in general because the information is insufficient: to take a rough example, the “variety” segment alone of input does not allow us to take a position on the positive or negative impact with regard to the pathogen risk, because certain varieties will increase it and others will decrease it), which should not be confused with a score of 50% of the number of points at stake which corresponds to “neutral impact”, that is to say that the impact is quantifiable but it is neither positive nor negative.

[0092] In the general case, the indicator score can be seen as a weighted average of the sub-scores with a number of points at stake excluding the “non-applicable” sub-scores and the corresponding number of points at stake.

[0093] Let NOTX = sub-score of level X, with X from 1 to 4 (expressed in relation to said maximum score) and PTSX = number of points in play of level X in the calculation of the indicator score, and CONTRIBX the contribution per level corresponding to the value of NOTX in proportion to PTSX. NOTX (and therefore CONTRIBX) can be a value, i.e. the number of points of the score, or NA, i.e. “not applicable” as explained.

[0094] In the preferred case of an equal contribution, PSTX would be equal to 25 for all X.

[0095] For each level, if NOTX NA, then CONTRIBX = PTSX * NOTX / maximum score, and otherwise CONTRIBX = NA

[0096] The NA contributions must be adjusted (i.e., an attempt must be made to find a numerical value for them), and in practice, if possible, the contribution of at least one other higher-ranking level that is not NA is taken. As an exception, a level 1 NA contribution is not adjustable. Indeed, it is not possible to approximate a set of products by a product belonging to this set. However, it is possible to assign a value to a product based on the average of the set to which it belongs.

[0097] - If CONTRIB2 = NA: • If CONTRIB3 NA, then CONTRIB2 = CONTRIB3 • Otherwise if CONTRIB4 NA, then CONTRIB2 = CONTRIB4 • Otherwise, CONTRIB2 = NA If CONTRIB3 = NA: • If CONTRIB4 NA, then CONTRIB3 = CONTRIB4 • Otherwise, CONTRIB3 = NA If CONTRIB4 = NA: • If CONTRIB3 NA, then CONTRIB4 = CONTRIB3 • Otherwise, CONTRIB4 = NA

[0098] We can then calculate SOMCONTRIB the sum of the contributions that are not NA and SOMPTS the sum of the points in play of the contributions that are not NA. If all the contributions are values ​​there is no problem, but otherwise we ignore the NA contributions by not counting the associated points in play. We can use the following algorithm:

[0099] For X = 1 to 4:

[0100] If CONTRIBX NA, SOMCONTRIB = SOMCONTRIB + CONTRIBX

[0101] Otherwise SOMCONTRIB = SOMCONTRIB

[0102] If CONTRIBX NA, SOMPTS = SOMPTS + PTSX

[0103] Otherwise SOMPTS = SOMPTS

[0104] The indicator subscore is given by the formula NOTGI = SOMCONTRIB / SOMPTS * maximum score

[0105] Let us assume the following example:

[0106] - NOT1 = NA - PTS1 = 20 CONTRIB1 = NA (not adjustable) NOT2 = 30 - PTS2 = 30 CONTRIB2 = 9 NOT3 = NA - PTS2 = 10 CONTRIB3 = NA (adjustable if CONTRIB4 NA) NOT4 = 37.5 - PTS4 = 40 CONTRIB4 = 15 (CONTRIB3 can be adjusted to the same value =15)

[0107] Then SOMCONTRIB = 9 + 15 + 15 = 39 and SOMPTS = 30 + 10 + 40 = 80 (since CONTRIB1 = NA), and NOTGI = 39 / 80*100 = 48.75.

[0108] Here is a non-exhaustive list of possible indicators for each criterion, and the calculation rule for an indicator for each criterion will be described in detail. A person skilled in the art will be able to choose the indicators of his choice (at least one indicator per criterion), and construct for these indicators calculation rules of the type that will be presented starting from a base of production of reference agricultural products:

[0109] Sanitary qualities

[0110] - Produce without GMOs - Aim for no residue - Produce without pathogenic molecules that are toxic to health [YES] Nutritional qualities

[0112] - Produce more plant proteins - Produce more unsaturated fatty acids, especially Omega 3 - Produce flawless wines - Encourage diversity of productions - Encourage atypical productions

[0113] Carbon

[0114] - Reduce the carbon footprint by favoring inputs / services with low GHG emissions (manufacturing + use) - Reduce the carbon footprint by promoting inputs / services with higher nitrogen efficiency - Participate in carbon storage in the soil by favoring a significant return of biomass to the soil - Promote inputs / services with high energy recovery - Be resilient to water and thermal stress - Implement inputs / services to reduce the risk of erosion (carbon)

[0115] Biodiversity

[0116] - Limit the risk of toxicity to the environment - Avoid or reduce synthetic phytopharmaceutical treatments - Limit the risk to bees - Promote food supply for pollinators - Promote cultivated biodiversity - Reduce the risk of the presence of trace metal elements in soils - Prioritize inputs / services that limit the risk of soil contamination - Participate in the increase of organic matter by favoring a significant potential for returning biomass to the soil - Favor inputs / services that are least dangerous for earthworms

[0117] Fair and sustainable remuneration

[0118] - Make the economic investment of the input / service profitable - Access markets of specific technological quality - Access markets valued by the UAB mention - Access markets valued by compatibility with labels or notebooks charges - Favor low volatility of the purchase price - Sow crops with a stable selling price - Ensure reliable production despite hazards

[0119] Quality of life

[0120] - Limit the number of sprayer outputs - Limit the risk of re-sowing - Reduce mental load through good flexibility in input / service positioning - Limit the impact on the health of the applicator (IRSA, Dephyto) - Promote inputs / services with a positive image (UAB, biocontrol) - Reduce mental load through low regulatory constraints - Reduce mental load through good selectivity of input

[0121] Example of the “Pathogenic risk” indicator associated with the “Health qualities” criterion.

[0122] The consumer wants their food not to present a health risk, the objective of the indicator is therefore to identify products which make it possible to combat the presence in foodstuffs of a pathogen toxic to consumer health (datura, mycotoxins, ergot).

[0123] The descriptive parameters involved in its calculation are:

[0124] - Input segment (REF061) - PPP segment (REFOI6) - Seed cultivation (REF073) - Culture for human consumption (REF070) - Culture affected by a pathogenic risk (REFOI9) - Pathogenic risk (REF091) Use of PPP (REF094) - Culture group (REF047) - Fusarium wilt resistance rating (REF092) - Ergot resistance rating (REF093) - Direct pathogenic efficacy (REF096) - Indirect pathogenic efficacy (REF097)

[0125] We can calculate an additional internal parameter:

[0126] Pathogenic efficacy of PPP = Max(Direct pathogenic efficacy (REF096); Indirect_pathogenic_eff)

[0127] With:

[0128] - If Indirect Pathogenic Efficacy (REF097) = Yes: Eff_path_indirecte = 67 - Otherwise: Eff_path_indirecte = 50

[0129] First level of calculation (NOT1): Does the segment have an impact on the pathogenic risk?

[0130] - If seed (REF061): NOT1 = NA If PPP (REF061): NOT 1 = NA If Fertilizer (REF061): NOT 1 = 50

[0131] Second level of calculation (NOT2) - Crop Type / PPP Categories (organic, mineral, fungicides, herbicides, etc.): Does the crop type / use have an impact on pathogen risk?

[0132] - If Seed (REF061): • If the culture (REF073) is intended for human consumption (REF070): NOT2 = 33 • Otherwise: NOT2 = 100 - If PPP (REF061), according to its segment (REF016): • If Molluscicide, Acaricide or Adjuvant: NOT2 = 50 • Otherwise: NOT2 = 100 If Ferti (REF061): NOT2 = NA

[0133] Third level of calculation (NOT3) - Crop / Active substance or substance of interest / Adjuvant / Input composition (NPK): Do the intrinsic components have an impact on the pathogenic risk?

[0134] - If Seed (REF061): • If the culture (REF073) is affected by a pathogenic risk (REF019): N0T3 = 33 • Otherwise: N0T3 = 100 If PPP (REF061): • If the PPP is a fungicide (REFOI6) with Botrytis use (REF094): NOT3 = 100 • Otherwise if the PPP is a fungicide (REFOI6) with a use for Vine powdery mildew (REF094) or an insecticide (REFOI6) with a use for Grape berry moth (REF094): NOT3 = 75 • Otherwise: NOT3 = Eff_path If Ferti (REF061): NOT3 = NA

[0135] Fourth level of calculation: Variety / formulated input (NOT4): Does the variety / input have an impact on the pathogen risk?

[0136] - If Seed (REF061): • If the crop (REF073) belongs to the Wheat group (REF047): • If the variety's resistance score to fusarium wilt (REF092) is > 5: NOT4 = 100 • Otherwise: NOT4 = 0 • Otherwise if the crop (REF073) belongs to the Cereals group (REF04) • If the ergot resistance score (REF093) of the variety is > 5: NOT4 = 100 • Otherwise: NOT4 = 0 • Otherwise: NOT4 = NA SiPPP(REF061): • If the PPP has a use Ochratoxin a-producing mushrooms (REF094): NOT4 = 100 • Otherwise if at least one of the uses (REF094) of the PPP is affected by a pathogenic risk (REF091): NOT4 = 100 • Otherwise: NOT4 = 50 If Fertilizer (REF061): NOT4 = NA

[0137] “Fatty acids” indicator of the “Nutritional quality” criterion

[0138] It is recommended that consumers consume less saturated fatty acids. The objective of the indicator is therefore to encourage agricultural production that allows the ratio between omega 6 and 3 to be rebalanced to a target of 4 / 1, i.e. to consume a maximum of 4 times more omega 6 than omega 3.

[0139] The descriptive parameters involved in its calculation are:

[0140] - Input segment (REF061) - Seed cultivation (REF073) - Crop group (REF047) - Omega 6 content of the culture (REF049) - Omega 3 content of the culture (REF049) - Omega 6 content of the variety (REF006) - Omega 3 content of the variety (REF006) - Authorized crops of the PPP (REF022) - Culture for human consumption (REF070)

[0141] Two additional internal parameters can be calculated:

[0142] - Ratio 6 / 3 culture = Omega 6 content culture (REF049) / Omega 3 content culture (REF049) - Ratio 6 / 3 variety = Omega 6 content variety (REF006) / Omega 3 content variety (REF006)

[0143] If Omega 6 content of the variety or Omega 3 content of the variety is not provided, Ratio 6 / 3 variety = NA

[0144] First level of calculation (NOT1): Does the segment have an influence on the production of unsaturated fatty acids?

[0145] - If PPP (REF061): NOT1 = 50 If Ferti (REF061): NOT1 = 50 If Seed (REF061): NOT1 = NA

[0146] Second level of calculation (NOT2) - Crop type / Input categories (organic, mineral, fungicides, herbicides, etc.)

[0147] - If Seed (REF061): • If the culture (REF073) is intended for human consumption (REF070): • The crop does not belong to the oilseed group (REF047): NOT2 = 50 • The crop belongs to the oilseed group (REF047): NOT2 = 67 • Otherwise: NOT2 = 50 If Ferti (REF061): NOT2 = NA If PPP (REF061): NOT2 = NA

[0148] Third calculation level (NOT3) - Culture / Active substance or of interest / Adjuvant / Input composition (NPK): Does the crop or the input influence the unsaturated fatty acid content?

[0149] - If Seed (REF061): • If the culture (REF073) is intended for human consumption (REF070): • If the crop belongs to the oilseed group (REF047): • If Ratio 6 / 3 culture > 20: NOT3 = 0 • If Ratio 6 / 3 culture < 20: NOT3 = [-2.5316*(ratio 6 / 3 culture) + 100.63]

[0150] Limit NOT3 between 50 and 100.

[0151] • Other crops: NOT3 = 50 • Otherwise: NOT3 = 50 • If Ferti (REF061): NOT3 = NA • If PPP (REF061): • If none of the authorized crops of the product belong to the oilseed group (REF047): NOT3 = 50 • If at least one of the authorized crops of the product belongs to the oilseed group (REF047): calculate the NOT3 Seeds for each of these authorized oilseed crops and apply the best of these notes to the PPP.

[0152] Fourth level of calculation (NOT4) - Variety / Formulated input: Does the variety or the active ingredients influence the fatty acid content?

[0153] - If Seed (REF061): • If the culture (REF073) is intended for human consumption (REF070): • If the seed crop belongs to the oilseed group (REF047): • If Ratio 6 / 3 variety > 20: NOT4 = 0 • If Ratio 6 / 3 variety < 20: NOT4 = [-2.5316*(ratio 6 / 3) + 100.63]

[0154] Limit NOT4 between 50 and 100.

[0155] • If Ratio 6 / 3 variety = NA: NOT4 = NA. • Other crops: NOT4 = 50 • Otherwise: NOT4 = 50 • If Ferti (REF061): NOT4 = NA • If PPP (REF061): NOT4 = NA

[0156] In all cases the seed score is preferably the linear regression on the 6 / 3 crop ratio with 20 (neutral ratio) = 50 and 0.25 (minimal ratio corresponding to oilseed flax) = 100.

[0157] “UAB Mention” indicator of the “Fair and Sustainable Remuneration” criterion

[0158] Consumers want quality, environmentally friendly products that support the farmers who produce them. The objective of the indicator is to distinguish between products that can be used in organic farming and those that cannot, in order to promote inputs. AB (AB being understood as a way of accessing a specific outlet allowing for better value for a production)

[0159] The descriptive parameters involved in its calculation are:

[0160] - Input segment (REF061) - Seed cultivation (REF073) - UAB status of the fertilizer (Yes / No) (REF046) - Seed available in AB (Yes / No) (REF001) UAB Status of PPP (Yes / No) (REF021) - Possible exemption for AB (Yes / No) (REF115)

[0161] First calculation level (NOT1):

[0162] - If PPP (REF061): NOT1 = NA If Ferti (REF061): NOT 1 = NA If Seed (REF061): NOT 1 = NA

[0163] Second level of calculation (NOT2) - Crop type / Product categories (organic, mineral, fungicides, herbicides, etc.)

[0164] - If PPP (REF061): NOT2 = NA If Ferti (REF061): NOT2 = NA If Seed (REF061): NOT2 = NA

[0165] Third calculation level (NOT3): Culture / Active substance or of interest / Adjuvant / Product composition (NPK)

[0166] - If PPP (REF061): NOT3 = NA If Fertilizer (REF061): NOT3 = NA If Seed (REF061): NOT3 = NA

[0167] Fourth level of calculation (NOT4) - Variety / Formulated product

[0168] - If PPP (REF061): • If the UAB status of the PPP (REF021) is Yes: NOT4 = 100 • Otherwise: NOT4 = 50 - If Fertilizer (REF061): • If the UAB status of the fertilizer (REF046) is Yes: NOT4 = 100 • Otherwise: NOT4 = 50 - If Seed (REF061): • If the seed is available in AB (REF001): NOT4 = 100 • Otherwise if the culture (REF073) has a possible exemption for AB (REF115): NOT4 = 100 • Otherwise: NOT4 = 50

[0169] “Regulatory constraints” indicator of the “Quality of life” criterion

[0170] The consumer wants to limit the mental burden on the farmer. The objective of the indicator is to reflect the regulatory complexity linked to the use of product and the stress it can cause.

[0171] The descriptive parameters involved in its calculation are:

[0172] - Input segment (REF061) Fertilizer Type (Ferti) (REF040) Type of organic fertilizer (Ferti) (REF041) Composition of the fertilizer (Ferti) (REF043) ZNT and riparian ZNT (PPP) (REF036) Precautionary phrase SPe8 (PPP) (REF028) Hazard statements (PPP) (REF030) DRE (PPP) (REF090)

[0173] First calculation level (NOT1) - is the use of the segment a regulatory issue?

[0174] If Seed (REF061): NOT1 = 50 If Ferti (REF061): NOT1 = 33 If PPP (REF061): NOT1 = 0

[0175] Second calculation level (NOT2) - Crop type / Product categories (organic,

[0176] mineral, fungicides, herbicides, etc.) If Seed (REF061): NOT2 = NA If PPP (REF061): NOT2 = NA If Fertilizer (REF061): • If the Fertilizer is organic (REF040): • If the organic fertilizer (REF041) is type I (C / N > 8): NOT2 = 16.5 • If the organic fertilizer (REF041) is type II (C / N < 8): NOT2 = 33 • If the Fertilizer is mineral or organo-mineral (REF040): NOT2 = 25

[0177] Third calculation level (NOT3) - Crop / Active or interesting substance / Adjuvant / Product composition (NPK): is the use of the segment a regulatory issue?

[0178] If Seed (REF061): NOT3 = NA If PPP (REF061): NOT3 = NA If Ferti (REF061), depending on its type and composition: • If Fertilizer not containing Nitrogen (REF043): NOT3 = 50 • Otherwise : If mineral type fertilizer (REF040): NOT3 = 0 If organic or organo-mineral type fertilizer (REF040): • If Type II Fertilizer (REF041): NOT3 = 20 • Otherwise: NOT3 = 40

[0179] Fourth calculation level (NOT4): Variety / Formulated product

[0180] - If Seed (REF061): NOT4 = NA If Ferti (REF061): NOT4 = NA If PPP (REF061): • NOT4 = 50 if none of the following cases is true: • DRE (REF090) > 24 h • ZNT (REF036) > 20 m • Riverside ZNT (REF036) > 10m • Presence of the cautionary phrase SPe8 (REF028) • Presence of at least one of the hazard statements (REF030) listed below (restrictions on mixtures):

[0181] List of hazard statements with restrictions on mixtures

[0182] H300 Fatal if swallowed

[0183] H301 Toxic if swallowed

[0184] H310 Fatal in contact with skin

[0185] H311 Toxic in contact with skin

[0186] H330 Fatal if inhaled

[0187] H331 Toxic if inhaled

[0188] H340 May cause genetic defects (state route of exposure if known) (It has been proven that no other route of exposure leads to the same danger)

[0189] H341 Suspected of causing genetic defects (state route of exposure) if it is formally proven that no other route of exposure leads to the same danger)

[0190] H350 May cause cancer (state route of exposure if formally proven that no other route of exposure leads to the same danger)

[0191] H350i May cause cancer if inhaled.

[0192] H351 Suspected of causing cancer (state route of exposure if known) (It has been proven that no other route of exposure leads to the same danger)

[0193] H360D May harm the unborn child.

[0194] H360Df May harm the unborn child. Suspected of damaging fertility.

[0195] H360F May impair fertility.

[0196] H360Fd May damage fertility. Suspected of damaging the unborn child.

[0197] H360FD May damage fertility. May harm the unborn child.

[0198] H361d Suspected of damaging the unborn child.

[0199] H361f Suspected of damaging fertility.

[0200] H361fd Suspected of damaging fertility. Suspected of damaging the unborn child.

[0201] H362 May be harmful to breast-fed babies

[0202] H370 Causes damage to organs (or state all organs) affected, if known) (indicate the route of exposure if it is formally proven that no other route of exposure leads to the same hazard)

[0203] H371 May cause damage to organs (or state all organs) affected, if known) (indicate the route of exposure if it is formally proven that no other route of exposure leads to the same hazard)

[0204] H372 Causes damage to organs (list all organs) affected, if known) following repeated or prolonged exposure (state route of exposure if it is conclusively proven that no other route of exposure causes the same hazard)

[0205] H373 May cause damage to organs (list all organs) affected, if known) following repeated or prolonged exposure (state route of exposure if it is conclusively proven that no other route of exposure causes the same hazard)

[0206] • If at least 2 of the previous cases are true: NOT4 = 0 • Otherwise if 1 of the previous cases is true: NOT4 = 12.5

[0207] Indicator “Avoid or reduce phytosanitary treatments” of the “Biodiversity” criterion

[0208] The consumer wants the farmer to have practices that avoid or reduce the impact on non-target organisms, the objective of the indicator is to evaluate the interest of the products to avoid phytosanitary treatments (by resistance of varieties to certain bio aggressors or abiotic factors, by stimulators of plant defense, by mixtures of varieties, early varieties of rapeseed to avoid insecticides, adjuvants to reduce doses...)

[0209] The descriptive parameters involved in its calculation are:

[0210] - Input segment (REF061) - PPP segment (REF016) - PPP component type (REF086) - Seed cultivation (REF073) - Average IFT of culture (REF051) CEPP note of the PPP (REF037) - Average dose of PPP (REF017) - CEPP note of the variety (REF012) - Average sowing rate of the variety (REF077) - Starter Fertilizer Status Yes / No (Fertilizer) (REF042)

[0211] First calculation level (NOT1): Does the product belong to a segment which potentially makes it possible to avoid phytopharmaceutical treatments?

[0212] - If Seed (REF061): NOT1 = 67 If PPP (REF061): NOT1 = NA If Ferti (REF061): NOT1 = 50 If Biostimulant (REF061): NOT1 = 67

[0213] Second level of calculation (NOT2) - Crop type / Product categories (organic, mineral, fungicides, herbicides, etc.)

[0214] - If Seed (REF061): NOT2 = NA SiPPP(REF061): • If at least one of the product components is of the Macroorganism type (REF086): NOT2 = 100 • Otherwise, depending on its segment: • Adjuvant (REF016): NOT2 = 50 • Other segment (REF016): NOT2 = 0 If Ferti (REF061): • If the product is a Starter Fertilizer (REF042): NOT2 = 67 • Otherwise NOT2 = 50

[0215] Third level of calculation - Culture / Active substance or of interest / Adjuvant / Product composition (NPK): What is the level of use of PPPs targeted by the product?

[0216] - If Seed (REF061): NOT3 = [50 - Average IFT of the crop (REF051) / 15.3 * 50] If PPP (REF061): NOT3 = NA If Ferti (REF061): NOT3 = NA

[0217] For the “Seed” segment, the value of 15.3 corresponds to the potato IFT, i.e. the highest 1TFT (maximum score for IFT = 0).

[0218] Fourth level of calculation - Variety / Formulated product: What is the potential number of treatments or doses avoided by the characteristics of the product (resistant variety, etc.)?

[0219] - If Ferti (REF061): NOT4 = NA - If Seed (REF061): NOT4 = [CEPP note (REF012) * average sowing dose of the variety (REF077) * 100] If PPP (REF061): NOT4 = [CEPP note (REF037) * average dose of PPP (REF017) * 100]

[0220] For the “Seed” segment and in the case of a mixture of varieties, NOT4 should be calculated by weighting the unit CEPP score according to the proportion of each variety in the mixture.

[0221] Example of the “Nitrogen efficiency” indicator associated with the “carbon” criterion

[0222] The objective of the indicator is to evaluate the effect of the input (seed for example) on the nitrogen efficiency of the system in order to provide the least amount of external nitrogen to the plot, in particular mineral nitrogen, a significant contributor to the greenhouse gas balance of agricultural plant production.

[0223] The descriptive parameters involved in its calculation are:

[0224] - Input segment (REF061) - Seed cultivation (REF073) - Crop group (REF047) - Status Mixture for seed cover (REF002) - Type of fertilizer (Fertilizer) (REF040) - Composition of the fertilizer (Fertilizer) (REF043) - Form of mineral nitrogen fertilizer (Fertilizer) (REF045) - Average crop yield (Seeds) (REF050) - Nitrogen requirement coefficients a and b of the crop (Seeds) (REF055) - Unit nitrogen requirement coefficient b of the wheat variety (Seeds) (REFOI 5) - Mineralization of residues from the previous Mr (Seeds) (REF056) - Mineralization of residues from the MrCi intermediate crop (Seeds) (REF057)

[0225] We can calculate an additional internal parameter:

[0226] Nitrogen balance provided by the crop: SoldN = (Mr (REF056) + MrCi (REF057)) -(coef b (REF055) * Average yield (REF050) + coef a (REF055))

[0227] First calculation level (NOT1):

[0228] - If PPP (REF061): NOT1 = 50 If Ferti (REF061): NOT1 = NA If Seed (REF061): NOT 1 = NA

[0229] Second level of calculation - Crop Type / Product Categories (organic, mineral, fungicides, herbicides, etc.): What types of crops can improve the nitrogen efficiency of the system?

[0230] - If PPP (REF061): NOT2 = NA If Ferti (REF061): NOT2 = NA - If Seed (REF061): • If the crop belongs to the Legumes group (REF047): NOT2 = 100 • Otherwise: NOT2 = 50

[0231] Third calculation level (NOT3) - Crop / Active or interesting substance / Adjuvant / Product composition (NPK): Which crops can improve the nitrogen efficiency of the system?

[0232] - If PPP (REF061): NOT3 = NA If Ferti (REF061): • If the product contains Nitrogen (REF043): N0T3 = 67 • Otherwise: N0T3 = 50 - If Seed (REF061): • Score by linear regression on the SoldN indicator of culture, with • If SoldN = SoldN Min: NOT3 = 50 • If SoldN = SoldN_Max: NOT3 = 100

[0233] Fourth level of calculation (NOT4) - Variety / Formulated product: Which varieties or products make it possible to improve the nitrogen efficiency of the system?

[0234] - If PPP (REF061): NOT4 = NA - If Ferti (REF061), depending on the type (REF040), composition (REF043) and form of mineral nitrogen (REF045) of the product: • If the product does not contain Nitrogen (REF040): NOT4 = 50 • Otherwise if the product is of the Organic (REF043) or Organo-mineral (REF043) type: NOT4 = 67 • Otherwise, depending on the form of mineral nitrogen (REF045): • If Urea: NOT4 = 50 • If Urea with urease inhibitor: NOT4 = 62.5 • If Solution: NOT4 = 87.5 • If Ammonitrate: NOT4 = 100 • Otherwise: NOT4 = 67 - If Seed (REF061): • If the crop belongs to the Wheat group (REF047): NOT4 = [(- 50 / 1.3) * coef b of the variety (REF015) + (50 / 1.3) * 2.8 + 100] • Otherwise: NOT4 = NA

[0235] For example, we can take Coef b max = 4.1 (BAF or BD) and Coef b min = 2.8

[0236] In a step (c), said scores associated with each indicator are aggregated into a score overall.

[0237] This aggregation can include several sub-steps. Starting from the scores associated with the indicators, they can be aggregated into scores associated with the criteria, then possibly into scores associated with the three expectations, before arriving at the overall score.

[0238] Each aggregation is typically a weighted average (either with equivalent shares or with predetermined coefficients), or the maximum. Those skilled in the art will know how to find the best aggregation strategy, in particular again by taking into account said base of production of agricultural products for learning and the expectations of consumers.

[0239] Finally, in a step (d), preferably implemented at the level of client 2, we can use the overall score resulting from the evaluation in relation to the input, for example example by marking the packaging of the input with this score, intended for farmers, and / or by displaying it (on the interface 23) and communicating it generally. For example, a farmer purchasing inputs on his terminal 2 can request the display of the overall score of several inputs between which he is hesitating so that he can make an informed choice.

[0240] Alternatively, this score may be used in a certification process, as the present method can be configured so that reaching a certain threshold is equivalent to directly satisfying a list of criteria required in the certification. The process is thus greatly simplified.

[0241] Evaluation of agricultural production

[0242] According to a second aspect, the invention relates to agricultural production involving the use of a set of agricultural inputs.

[0243] This method thus comprises a step (A) of implementing for each input of said set of the method according to the first aspect of evaluating the input (in isolation) so as to obtain an overall score of said input, then a step (B) of aggregating said overall scores of each input of said set into a total score. Again, the average can be taken, the minimum score taken, etc.

[0244] The idea is to allow an aggregation of several global scores into a total score at the scale of several inputs, or even a route, a farm, etc., so as to allow a comparison at a higher level. The notion of "agricultural production" will again be understood in the broad sense.

[0245] For example, one may wish to simply evaluate a "combination" of inputs, but preferably, for a given production, said set of inputs includes the seed(s) and each plant protection product and each plant nutrition product used on said seed during said production.

[0246] In a similar manner to step (d), the method according to the second aspect may comprise a step (C) where the total score resulting from the evaluation may be used in connection with the production, for example by marking the packaging of the agricultural product obtained at the end of the production with this score, intended for consumers, and / or by displaying it (on the interface 23) and communicating it in a general manner.

[0247] Computer program product

[0248] According to a third and a fourth aspect, the invention relates to a computer program product comprising code instructions for the execution (in particular on the data processing means 11, 21 of the server 1 and / or the client 2) of a method for evaluating an agricultural input, as well as storage means readable by computer equipment (a memory 12, 22 of the server 1 and / or the client 2) on which this computer program product is found. 35

Claims

Claims

1. Method for evaluating an agricultural input, the method being characterized in that it comprises the implementation by processing means (11) of a server (1) of steps of: a. Obtaining the values ​​for said agricultural input of a set of descriptive parameters, said values ​​being measured directly, entered by a farmer or recovered from a base of observed values ​​of said parameters; b.For a plurality of indicators each associated with a criterion of a predefined set of evaluation criteria for said agricultural input, calculation, based on said descriptive parameters, of at least one score of the indicator representative of an impact of said agricultural input on the criterion with which it is associated, said score having a value between a maximum score corresponding to a maximum positive impact observed in a base of productions of reference agricultural products and a minimum score corresponding to a maximum negative impact observed in said base of productions of reference agricultural products; c. Aggregation of said scores of each indicator into an overall score; d. Marking of a package of said input with said overall score and / or display of said overall score on an interface.

2. Method according to claim 1, in which said indicator score has a predefined intermediate value corresponding to a neutral impact observed in said base of productions of reference agricultural products

3. A method according to either of claims 1 and 2, wherein said input is selected from a seed, a plant protection product, a plant nutrition product and an agricultural service.

4. Method according to one of claims 1 to 3, in which said predefined set of criteria for evaluating said agricultural input comprises the following criteria: - Health qualities - Nutritional qualities - Fair and sustainable remuneration - Quality of life - Carbon - Biodiversity

5. Method according to claim 4, in which: The health qualities criterion is associated with the indicators: - Produce without GMOs - Aim for the absence of residues - Produce without pathogenic molecules toxic to health The nutritional qualities criterion is associated with the indicators: - Produce more vegetable proteins - Produce more unsaturated fatty acids, in particular Omega 3 - Produce wines without defects - Encourage the diversity of productions - Encourage atypical productions The carbon criterion is associated with the indicators: - Reduce the carbon footprint by favoring inputs / services with a low GHG emissions balance - Reduce the carbon footprint by promoting inputs / services with higher nitrogen efficiency - Participate in carbon storage in the soil by favoring a significant return of biomass to the soil - Promote inputs / services with highenergy recovery - Be resilient to water and thermal stress - Implement inputs / services to reduce the risk of erosion The biodiversity criterion is associated with the indicators: - Limit the risk of toxicity to the environment - Avoid or reduce synthetic phytopharmaceutical treatments - Limit the risk for bees - Promote the food supply for pollinators - Promote cultivated biodiversity - Reduce the risk of the presence of trace metal elements in soils - Favor inputs / services that limit the danger of soil contamination - Participate in the increase of organic matter by favoring a significant potential for returning biomass to the soil - Favor inputs / services that are the least dangerous for earthworms The fair and sustainable remuneration criterion is associated with the indicators: - Make the economic investment of the input / service profitable - Access markets of specific technological quality - Access markets valued by the UAB label - Access markets valued by compatibility with labels or specifications - Favor low volatility in the purchase price - Sow crops with a stable selling price - Make production reliable despite hazards The quality of life criterion is associated with theindicators: - Limit the number of sprayer outings - Limit the risk of re-sowing - Reduce the mental load through good flexibility in input / service positioning - Limit the impact on the health of the applicator - Promote inputs / services with a positive image - Reduce the mental load through low regulatory constraints - Reduce the mental load through good selectivity of the input.

6. Method according to one of claims 1 to 5, in which there is at least one indicator per evaluation criterion of said agricultural input of the predefined set, step (c) comprising the calculation of a score of each evaluation criterion from said scores of each indicator associated with said criterion, then the calculation of said overall score from the scores of each evaluation criterion.

7. Method according to one of claims 1 to 6, in which step (b) comprises the calculation of a plurality of sub-scores of the indicator each representative of an impact at a given level of said input on the criterion with which it is associated, the sub-scores of the indicator being aggregated into the score of the indicator.

8. Method according to claim 7, in which there are four sub-scores of the indicator respectively representative of an impact: - of the market of the input, - of the segment of the input, - of the composition of the input, - of the input itself.

9. Method according to one of claims 7 and 8, in which each sub-score of the indicator either has a value or is "not applicable", the score of the indicator being calculated as an average of the sub-scores having a value weighted with a number of points of the level.

10. Method for evaluating an agricultural production involving the use of a set of agricultural inputs, the method being characterized in that it comprises the implementation by processing means (11) of a server (1) of steps of: A. For each input of said set, implementation of the method according to one of claims 1 to 9 so as to obtain an overall score of said input. B. Aggregation of said overall scores of each input of said set into a total score.

11. Computer program product comprising code instructions for executing a method according to one of claims 1 to 10 for evaluating an agricultural input or agricultural production, when said program is executed on a computer.

12. Storage medium readable by computer equipment on which a computer program product comprises code instructions for executing a method according to one of claims 1 to 10 evaluation of an agricultural input or agricultural production.

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