Modular agricultural treatment system and method for operating modular agricultural treatment system

Abstract

The invention relates to a method for operating a modular agricultural treatment system (1) comprising a base station (2) and at least one field device (3; 12). The base station (2) has at least three base containers (4) filled with a base product (5). Each field device (3; 12) 5 comprises at least two field containers (9) filled with a field product (10). According to the method, base product data (20) and field data (21) are provided. Based on the base product data (20) and the field data (21), a base product (5) and / or a mixture of base products (5) to be used as a field product (10) is determined. The base product (5) is correspondingly filled into the field device (3; 12) in the field container (9). Further, for each of a plurality of zones 10 of the farmland, a product composition (25) consisting of the farmland products (10) is determined. According to the determined product composition (25), by means of the field device (3; 12) applying the field product (10) to these zones of the farmland. The invention further relates to a corresponding modular agricultural treatment system (1). 15 (Figure 1)

Description

Technical Field

[0001] The present invention relates to digital agriculture. In particular, the present invention relates to a method for operating a modular agricultural treatment system that can be used to treat harmful organisms and / or plant health defects in agricultural fields. The present invention further relates to a modular agricultural treatment system. Background Art

[0002] Farmers often lack sufficient labor to carry out planting-related activities at the best moment of a season. Only when these activities are performed by autonomously functioning intelligent systems, decisions triggered by digital systems based on forecasts (e.g. weather), monitoring (e.g. monitoring of pests or diseases) and agronomic knowledge systems can reduce the workload of farmers. Such systems improve the timeliness and spatial accuracy of product application. By defining treated and untreated areas within the field and adjusting the selection and ratio of (multiple) products, the ideal effect on the target can be achieved and the input of (multiple) products can be saved. Due to the autonomy of the application system, the number of spraying is no longer a bottleneck for farmers. However, the number of potential product choices is limited and does not fully reflect the changing field conditions, such as the biological target situation or application conditions, such as humidity, temperature or wind speed. Summary of the invention

[0003] It is therefore an object of the present invention to provide a method for operating a modular agricultural processing system to improve product selection and application. It is another object of the present invention to provide a related modular agricultural processing system.

[0004] The objects of the invention are achieved by the subject-matter of the independent claims, wherein further embodiments are contained in the dependent claims.

[0005] According to one aspect of the present invention, a method for operating a modular agricultural treatment system is provided that can be used to treat harmful organisms and / or plant health defects in an agricultural field.

[0006] At least a portion of the method may be implemented on a computer. In this context, "computer" may refer to any computing device, such as a smartphone, a tablet computer, a personal computer, a supercomputer, or the computer portion of a farm management program on a device. In particular, the method may be performed on multiple processors, thereby parallelizing and thus speeding up the performance of the method. Furthermore, the method may be split across more than one computer, wherein the computers are interconnected via wireless and / or wired connections.

[0007] "Harmful organisms" are understood to be any organisms that have a negative impact on the growth or health of agricultural crop plants. In addition, "plant health defects" are any other conditions that are detrimental to plant health, such as lack of water, lack of nutrients, lack of minerals or lack of growth regulators.

[0008] The term "farmland" is understood to be any area where an organism (particularly a crop plant) is produced, grown, sown and / or is planned to be produced, grown or sown. The term "farmland" also includes horticultural fields and afforestation fields. The farmland can have open field conditions, or can be in a protected area, such as a greenhouse. The preferred crops produced, grown and / or sown in the farmland are onion (Alliumcepa), pineapple (Ananas comosus), peanut (Arachis hypogaea), asparagus officinalis (Asparagus officinalis), oats (Avena sativa), beet (Beta vulgaris spec.altissima), beet (Beta vulgaris spec.rapa), European rape (Brassica napus var. napus), turnip (Brassica napus var. napobrassica), turnip (Brassica rapa var.silvestris), kale (Brassica oleracea), black mustard (Brassica nigra), big leaf tea (Camellia sinensis), safflower (Carthamus tinctorius), American pecan (Caryaillinoinensis), lemon (Citrus limon), sweet orange (Citrus sinensis), small fruit coffee (Coffea arabica) (Coffea canephora, Coffea liberica), cucumber (Cucumissativus), dog tooth root (Cynodon dactylon), carrot (Daucus carota), oil palm (Elaeisguineensis), European strawberry (Fragaria vesca), soybean (Glycine max), upland cotton (Gossypiumhirsutum), (tree cotton (Gossypium arboreum), grass cotton (Gossypium herbaceum), Gossypiumvitifolium), sunflower (Helianthus annuus), rubber tree (Hevea brasiliensis), barley (Hordeum vulgare), hops (Humulus lupulus), sweet potato (Ipomoea batatas), walnuts (Juglans regia), lettuce (Latcuca sativa), lentils (Lens culinaris), flax (Linum usitatissimum), tomato (Lycopersicon lycopersicum), apple (Malus) species, cassava (Manihot esculenta), alfalfa (Medicago sativa), Musa (Musa) species, tobacco (Nicotiana tabacum) (N.rustica), olive (Olea europaea), rice (Oryza sativa), golden bean (Phaseolus lunatus), bean (Phaseolus vulgaris), European spruce (Picea abies), pine (Pinus) species, pistachio (Pistacia vera), pea (Pisum sativum), European sweet cherry (Prunus avium), peach (Prunus persica), pear (Pyrus communis), apricot (Prunus armeniaca), European sour cherry (Prunus cerasus), almond (Prunus dulcis) and European plum (Prunus domestica), radish (Raphanus sativus), currant (Ribes sylvestre), castor (Ricinus communis), sugarcane (Saccharum officinarum), rye (Secale cereale), mustard (Sinapis alba), potato (Solanum tuberosum), sorghum (Sorghum bicolor) (sorghum (s. vulgare)), theobroma cacao, red clover (Trifolium pratense), common wheat (Triticum aestivum), triticale (Triticale), durum wheat (Triticum durum), broad bean (Vicia faba), grape (Vitis vinifera), and maize (Zea mays). The most preferred crops are groundnut, sugar beet, rapeseed, kale, lemon, orange, coffee (Coffee cane, coffee macro), bermudagrass, soybean, cotton, (Gossypium vitifolium), sunflower, barley, walnut, lentil, flax, tomato, apple species, alfalfa, tobacco (Nicotiana tabacum), olive, rice, golden bean, bean, pistachio, pea, almond, sugarcane, rye, potato, sorghum, triticale, common wheat, durum wheat, broad bean, grape and maize. Particularly preferred crops are cereal crops, corn, soybean, rice, rapeseed, cotton, potato, peanut or perennial crops.

[0009] The modular agricultural processing system is particularly an autonomous system that requires little or no input from a user (e.g., a farmer). The modular agricultural processing system includes a base station and at least one field device. The base station can be located or placed near the farmland so that (multiple) field devices do not have to travel unnecessary distances. The base station includes at least three basic containers, wherein each basic container is filled with a basic product. Specifically, the basic products in different basic containers are different from each other. More specifically, the first basic product in the first basic container, the second basic product in the second basic container, and the third basic product in the third basic container are different from each other. Preferably, the modular agricultural processing system includes a plurality of field devices so that the farmland can be processed in a timely manner. Each field device includes at least two field containers. Specifically, the number of field containers of each field device may be less than the number of basic containers. Each field container is adapted to be filled with a field product, and the field device is adapted to apply the field product to the farmland. Specifically, the field device can spray the field product onto the farmland.

[0010] According to the method, basic product data related to the basic product is provided. For example, the basic product can be marked with a product identifier. The basic product data may include active ingredient information, agricultural performance information, dosage form, viscosity, surface tension, turbidity, phase separation risk, loading, physical compatibility data, chemical data, crop registration, health defect registration and / or mixture registration. Active ingredient information can be considered when the necessity of a specific active ingredient has been determined (for example, by detecting a certain harmful organism that needs to be treated with the specific active ingredient). Agricultural performance information is related to active ingredient information: it includes information that the product has a certain agricultural performance, such as control of a certain harmful organism. The dosage form can be, for example, a solution, a suspension, an emulsion or a solid product. Loading includes information on how the product can be loaded onto a processing system, for example, whether the storage tank needs to meet certain safety requirements. Crop registration includes information on whether the product is registered for a certain crop, which may depend on the date or the growth stage of the crop. Health defect registration includes information on whether the product is registered for treating a certain health defect. Crop registration and / or health defect registration can also include information about the maximum amount of products registered for a certain crop and / or treating a certain health defect. The mixture registration includes information on whether the product is registered as mixed with other products.

[0011] Further, field data related to the field conditions of the farmland are also provided. Then, the base product and / or mixture of base products to be used as the field product is determined based on the base product data and the field data. The determination of the base product and / or mixture of base products allows the production of a field product mixture that is optimal for the farmland (e.g., to treat harmful organisms and / or plant health defects). The base product and / or mixture of base products to be used as the field product can be further determined so that the expected mixture of the field product meets regulatory and / or legal requirements, and relevant agronomic and / or regulatory practice thresholds can be taken into account.

[0012] Then, the base product is filled into the field container of the field equipment so that the field product in the field container is the determined field product. If it is determined that the field product is a pure (ie, unmixed) base product, the corresponding base product is filled into the field container. On the other hand, if the field product is a mixture of base products, the base products can be mixed in the base station, and then the mixture of base products can be filled into the corresponding field container. The mixing in the base station can be performed by using one or more mixing chambers and adjusting the flow of these base products to (multiple) mixing chambers accordingly. Alternatively or in addition, these base products can be mixed by adding them to a dedicated mixing tank, in which these base products can also be stirred. Alternatively or in addition, these base products can be filled into the field container separately, wherein the amount of each base product filled into the field container is selected according to the determined base product mixture. The field container may include a device for stirring these base products, or these base products can be fully mixed by filling these base products into the field container and / or shaking the field container (e.g., due to the movement of the field equipment). As yet another alternative, the two options described above can be combined so that some base products are mixed in the base station and then filled into the field container, while other base products are added directly to the field container. Of course, it is also possible that some field products are pure base products, while other field products are mixtures of base products.

[0013] The base station can send an alarm or notification to a user (e.g., a farmer) when one or more base containers need to be refilled with base products and / or when such refilling is expected to be required within a predetermined time span. The user can then refill before the base product runs out. Alternatively or in addition, the base station can be connected to a reloading unit and / or an automatic command system, and the base station can transmit a refill command when one or more base containers need to be refilled with base products and / or when such refilling is expected to be required within a predetermined time span. The need for refilling can be determined by measuring a meter of the remaining base product in each base container, wherein the need for refilling is indicated when the remaining amount is below a predetermined value. Alternatively or in addition, the need for refilling can be determined based on recorded base product usage and / or predicted demand for base products used to treat farmland.

[0014] Further, for each of the multiple zones of the farmland, a product composition consisting of field products to be applied to the zone of the farmland is determined. The determination is based on basic product data and field data. In particular, it is to make the product composition optimal for the zone of the farmland (e.g., to treat harmful organisms and / or plant health defects). The determination can further make the product composition meet regulatory and / or legal requirements, and relevant agronomic and / or regulatory practice thresholds can be considered. In this context, the term "zone" should be understood as a sub-field area or a part of the farmland, that is, the farmland can be spatially divided into more than one zone, wherein each zone can have different properties. Further, a "product composition" can be a mixture of field products, but it can also be just one of the field products. In addition to the product composition, the ratio of the product composition to be applied to these zones of the farmland can also be determined, for example, the volume of the product composition to be applied per unit area is given.

[0015] Finally, the field product is applied to these areas of the farmland by the field equipment according to the determined product composition. The application of the field product can be carried out by a direct spray system. Different droplet sizes can be achieved, for example, by using different nozzles, different spray pressures and / or flexible use of droplet size adjustment products. In addition, different application rates can be achieved, for example, by changing the speed of the field equipment, by using different nozzles and / or by using different spray pressures.

[0016] Thus, the optimal mixture of base products is applied to these zones of the field, where "optimal" can be the overall response to all relevant conditions of the field. This ensures the best input-output ratio, where input refers specifically to the base products used, and output refers to the agricultural effect, increased profitability, and avoiding overuse of products, without the need to (re)formulate existing products under changing conditions.

[0017] According to an embodiment, the base product is at least one of the group or a mixture of at least two of the group, the group consisting of: chemical products, biological products, fertilizers, nutrients, biostimulants, pheromones, water, tank mix adjuvants, detergents, bulking agents, defoamers, water quality regulators and pH regulators. The chemical products and biological products may be crop protection compounds. Water or other suitable liquids may be used as solvents, i.e. as carriers for the other base products.

[0018] Specifically, the base product can be a single product, can be a premix of a product, or can be an integrated combination of several products. Specifically, the base product can be provided as a liquid or as a solid. The chemical product can be a fungicide, a herbicide, an insecticide, a miticide, a molluscicide, a nematicide, a birdicide, a piscicide, a rodenticide, an insect repellent, a pheromone, a bactericide, a biocide, a safener, a plant growth regulator, a urease inhibitor, a nitrification inhibitor or a denitrification inhibitor. The biological product can be a microorganism used as a fungicide (biofungicide), a herbicide (bioherbicide), an insecticide (bioinsecticide), a miticide (biomiticide), a molluscicide (biomolluscicide), a nematicide (bionematicide), a birdicide, a piscicide, a rodenticide, an insect repellent, a pheromone, a bactericide, a biocide, a safener, a plant growth regulator, a urease inhibitor, a nitrification inhibitor or a denitrification inhibitor. Tank mix adjuvants can be products that, in addition to other functions (such as increasing the biological performance of the product), also act as compatibilizers, which prevent phase separation in the tank or facilitate mixing compatibility of other products and are used especially when the product is a mixture. Compatibilizers can be used in mixtures or alone and aid in the mixing of other products or modify the mixing of other products so that the mixture achieves certain properties, such as sprayability, reduced surface tension or adjusted droplet size distribution.

[0019] In a preferred embodiment of the invention, at least one of these products is a herbicide from at least one of the following classes: acetamides, amides, aryloxyphenoxypropionates, benzamides, benzofurans, benzoic acids, benzothiadiazinones, bipyridyliums, carbamates, chloroacetamides, chlorocarboxylic acids, cyclohexanediones, dinitroanilines, dinitrophenols, diphenyl ethers, glycine, imidazolinones, isoxazoles, isoxazolidinones, nitriles, N-phenylphthalimides, oxadiazoles, oxazolidinediones, oxyacetamides, phenoxy phenylcarbamate, phenylpyrazole, phenylpyrazoline, phenylpyridazine, phosphinic acid, phosphoramidate, phosphorodithioate, o-carbamoylbenzoate, pyrazole, pyridazinone, pyridine, pyridinecarboxylic acid, pyridinecarboxamide, pyrimidinedione, pyrimidinyl(thio)benzoate, quinolinecarboxylic acid, semicarbazone, sulfonylaminocarbonyltriazolinone, sulfonylurea, tetrazolinone, thiadiazole, thiocarbamate, triazine, triazone, triazole, triazolinone, triazolocarboxamide, triazolopyrimidine, triketone, uracil, urea.

[0020] In another preferred embodiment of the invention, at least one of these products is a herbicide selected from the herbicides of classes b1) to b15):

[0021] b1) lipid biosynthesis inhibitors;

[0022] b2) acetolactate synthase inhibitors (ALS inhibitors);

[0023] b3) photosynthesis inhibitors;

[0024] b4) protoporphyrinogen-IX oxidase inhibitors,

[0025] b5) bleaching agent herbicides;

[0026] b6) Enolpyruvylshikimate 3-phosphate synthase inhibitors (EPSP inhibitors);

[0027] b7) glutamine synthetase inhibitors;

[0028] b8) 7,8-dihydropteroate synthase inhibitors (DHP inhibitors);

[0029] b9) mitotic inhibitors;

[0030] b10) Very long chain fatty acid synthesis inhibitors (VLCFA inhibitors);

[0031] b11) cellulose biosynthesis inhibitors;

[0032] b12) decoupler herbicide;

[0033] b13) auxin herbicides;

[0034] b14) auxin transport inhibitors; and

[0035] b15) Other herbicides selected from the group consisting of: brombutyric acid chlorpyrifos, chlorpyrifos methyl, cyproconazole, cumyluron, dalapon, dazomethan, dimethoate, dimethoate-methyl sulfate, thiamethoxam, DSMA, dymron, endothal and its salts, ethoxybencarb, flamprop, flamprop-isopropyl, flamprop-methyl, flamprop-M- isopropyl), flamprop-M-methyl, flurenol, flurenol-butyl, flurprimidol, cypermethrin, cypermethrin ammonium, indole, indole-3-nitropropane, maleic hydrazide, flusulfuron, metamidine, isothiocyanate, methyl azide, methyl bromide, methyl-cypermethrin, methyl iodide, MSMA, oleic acid, oxazithromycin, nonanoic acid, barnyardgrass, anabolic acid, tetflupyrolimet, triazine fluazifop, and cypermethrin; including agriculturally acceptable salts, amides, esters or thioesters thereof.

[0036] In a preferred embodiment of the invention, at least one of these products is one of the following herbicides or herbicide mixtures: as an example, the product providing the inhibition of acetyl-CoA carboxylase is cyclohexanedione (DIM), aryloxyphenoxy-propionate (FOP) and / or phenylpyrazoline, the product providing the inhibition of acetolactate synthase is pyrimidinylbenzoate, sulfonanilide, triazolopyrimidine, sulfonylurea, imidazolinone and / or triazolinone, the product providing the inhibition of photosynthesis at the PS11-serine 264 binder is triazine, triazolinone, triazone, uracil, phenylcarbamate, pyridazinone, urea and / or amide, the product providing the inhibition of photosynthesis at the PS11-histidine 215 binder is nitrile, phenyl-pyridazine and / or benzothiadiazinon, the product providing the inhibition of PS11-histidine 215 binder is The product of I electron transfer is pyridinium, the product providing protoporphyrinogen oxidase inhibition is diphenyl ether, phenylpyrazole, N-phenyl-oxadiazolinone, N-phenyl-triazolinone and / or N-phenyl-imide, the product providing phytoene unsaturase inhibition is phenyl ether, N-phenyl heterocycle and / or diphenyl heterocycle, the product providing hydroxyphenylpyruvate dioxygenase inhibition is triketone, pyrazole and / or isoxazole, the product providing homogentisate solanyl transferase inhibition is phenoxypyridazine, the product providing deoxy-D-xylulose phosphate synthase inhibition is isoxazolidinone, the product providing enolpyruvylshikimate phosphate synthase inhibition is glycine, the product providing glutamine synthase inhibition is phosphinate, the product providing dihydropteroate synthase inhibition is carbamate, the product providing microtubule assembly inhibition is dinitroaniline, pyridine, phosphoramidate, benzoic acid and / or benzamide, the product providing microtubule assembly inhibition is The product provided for inhibiting cellulose synthesis is a carbamate, the product provided for inhibiting cellulose synthesis is a triazole carboxamide, a benzamide, an alkyl oxadiene and / or a nitrile, the product used as an uncoupler is a dinitrophenol, the product provided for inhibiting the synthesis of very long chain fatty acids is a pyrrolyl-carboxamide, α-thioacetamide, isoxazoline, ethylene oxide, α-chloroacetamide, α-oxyacetamide, thiocarbamate and / or benzofuran, the product used as an auxin mimetic is a pyridine carboxylate, pyridyloxycarboxylate, phenoxycarboxylate, benzoate, quinoline carboxylate, pyrimidine carboxylate and / or phenyl carboxylate, the product used as an auxin transport inhibitor is an aryl carboxylate, the product provided for inhibiting fatty acid thioesterase is a benzyl ether, the product provided for inhibiting solanesyl diphosphate synthase is a diphenyl ether, the product provided for inhibiting dihydroorotate dehydrogenase is an arylpyrrolidone aniline, and the product provided for inhibiting lycopene cyclase is a triazole.

[0037] Examples of active ingredients in the products are 2.4-D (choline, DMA, ester), BAPMA, DGA, Na, K), Florasulam, Acetochlor, Atrazine, Bentazone, Bicyclopyrone, Carfentrazone-E, Chlorimuron-E, Clethodim, Clomazone, Clopyralid, Cloransula m), DFFP, Diflufenican, Dimethenamid-P, Diquat, Flufenacet, Flumetsulam, Flumiclorac, Flumioxazin, Fluroxypyr, Fluthiacet, Fomesafen, Glufosinate-Ammonium, Glyphosate (K, IPA), Glyphosate-Potassium (Gl yphosate-Potassium-Salt), Halauxifen, Halosulfuron, Haloxyfop-PM, Imazamox, Imazethapyr, Isoxaflutole, Lactofen, Mesotrione, Metribuzin, Nicosulfuron, Paraquat, Pendimethalin, Pendimethalin Pyroxasulfone, Quizalofop, Rimsulfuron, Saflufenacil, S-Metolachlor, Sulfentrazone, Tembotrione, Thifensulfuron, Tolpyralate, Topramezone, Tribenuron, Trifludimoxazin, Metazachlor,Quizalofop-PE, Fenoxaprop, Chlortoluron, Glyphosate, Imazamox, Flurochloridone, MCPA, Flufenacet, Pinoxaden, Tribenuron-M, Diflufenican, Clomazone, Aclonifen, Fluroxypyr, Propaquizafop, Clethodim, Diquat and Florasulam. Examples of mixtures of active ingredients are L-glufosinate and DMTA-P; dimethoate-P and benpyrazone; fluazifop-p-butyl and pyraclostrobin; L-glufosinate ammonium and benpyrazone; glyphosate and metolachlor; L-glufosinate ammonium and mesotrione; atrazine, mesotrione and S-metolachlor; glyphosate and pyrimidine oxime; atrazine and S-metolachlor; fluazifop-p-butyl and pyraclostrobin; L-glufosinate ammonium and cypermethrin; S-metolachlor and Terbuthylazine; Dimethoate-P and pyrimidine oxime; Benthiocarb, Mesotrione and S-isopropylamine; Acetochlor and Fomesulfuron; GLY and GFA; L-Glufosinate-ammonium and Acetochlor; Atrazine and Mesotrione; L-Glufosinate-ammonium, Trifluoperazine and pyrimidine oxime; Fomesulfuron and glyphosate; 2.4-D-choline and glyphosate; Cyprosulfuron, Foramsulfuron, Iodosulfuron-M-Na and Thiencarbazone-M; dicamba, nicosulfuron and sulfasulfuron; acetochlor, clopyralid and mesotrione; dicamba and diflupyrone; cyprosulfonamide, flufenacet, foramsulfuron, terbuthylazine and thiocarbazone-M; cyprosulfonamide, isoxathiapiprolin and thiocarbazone-M; imazethapyr, sulfasulfuron and pyrimidinesulfuron; atrazine, bicyclopyrone, mesotrione and S-isopropylamine; GLY and dicamba; dicamba- Diglycolamine salt and S-isopropylamine; glyphosate and mesotrione; mesotrione, S-isopropylamine and terbuthion; cypermethrin and thiocarb; imazethapyr and mesotrione; isoxathiocarb and thiocarb; glyphosate, mesotrione and S-isopropylamine; metolachlor and S-isopropylamine; acetochlor and atrazine; acetochlor, clopyralid and sulfamethoxam; S-isopropylamine and mesotrione; L-glufosinate ammonium and pyrimidine oxime; bicyclic pyrone,Mesotrione and S-isopropylamine; Imazethapyr and pyrimidine oxime; L-glufosinate ammonium and trifluoxetine; Mesotrione and terbuthion; Mesotrione and nicosulfuron; Bapma salt of dicamba and L-glufosinate ammonium; L-glufosinate ammonium and bicyclic pyrone; Fomesulfuron and S-isopropylamine; Acetochlor and Mesotrione; 2,4-D choline and L-glufosinate ammonium; Glyphosate, pyrimidine oxime and trifluoxetine; Glyphosate isopropylamine and glyphosate potassium salt; Clofenac and sulfentrazone; Isoxadifen-E and cypermethrin; Flufenacet, isoxadifen Azoles-ethyl, cypermethrin and terbuthylazine; dimethoate-P and terbuthylazine; dicamba and trifloxysulfuron; glufosinate, pyraclostrobin and imazamox; fluazifop-butyl and trifloxysulfuron; glufosinate ammonium and acetochlor; glufosinate ammonium and S-isopropylamine; glufosinate ammonium and DMTA-P; glufosinate ammonium and pyraclostrobin; glufosinate ammonium, trifloxysulfuron and pyraclostrobin; 2,4-D choline and glufosinate ammonium; GA and pyraclostrobin; GA, pyraclostrobin and imazamox; L-GA and DMTA-P; pyraclostrobin and pyraclostrobin; pyraclostrobin and fluazifop-butyl; pyraclostrobin and dimethoate amine; sulfone pyraclostrobin and imazethapyr; sulfone pyraclostrobin, pyrimidine oxime and mesotrione; dicamba, DFFP and Pyrox; dicamba, Pyrox and imazethapyr; pyrimidine oxime, trifluoperazine, sulfone pyraclostrobin and imazethapyr; sulfone pyraclostrobin and imazethapyr; dicamba and DFFP; dimethoate-P, pyraclostrobin and clomeclorac; quincloquin-mexyl, bispyribac and foramsulfuron; pyraclostrobin and clomeclorac; flufenacet and pendimethalin; imazamox and methotrexate; flufenacet, flufenacet and flutolanil; bispyribac and foramsulfuron; aminopyralid and pendimethalin; mesotrione Metsulfuron-M and Tribenuron-M; 2.4-D and bispyribac; flufenacet and flufenacet; bispyribac and trifloxysulfuron; flufenacet, bispyribac and penoxsulam; chlorotoluron and flufenacet; iodosulfuron-methyl-Na and mesosulfuron-methyl-M; iodosulfuron-methyl-Na, pyrazol-diethyl and mesosulfuron-methyl; aminopyralid, clopyralid and picloram; and thifensulfuron-methyl and bensulfuron-methyl-M.

[0038] In a preferred embodiment of the invention, at least one of these products is at least one insecticide selected from the group consisting of: triazemate, aldicarb, alanycarb, benfuracarb, carbaryl, carbofuran, carbosulfan, methiocarb, methomyl, oxamyl, primicarb, propoxur, Thiodicarb, acephate, azinphos-ethyl, azinphos-methyl, chlorfenvinphos, chlorpyrifos, chlorpyrifos-methyl, demeton-S-methyl, diazinon, dichlorvos / DDVP, dicrotophos, dimethoate te), disulfoton, ethion, fenitrothion, fenthion, isoxathion, malathion, methamidaphos, methidathion, mevinphos, monocrotophos, oxymethoate, oxydemeton-methyl, parathion, parathion-methyl, phenthoate, phorate, phosalone, phosmet, phosphamidon, pirimiphos-methyl, quinalphos, terbufos, tetrachlorvinphos, triazophos, trichlorfon, cyclodiene or-ganochlorineendosulfan), N-ethyl-2,2-dimethylpropionamide-2-(2,6-dichloro-α.α.α-trichloro-p-tolyl)hydrazone, N-ethyl-2,2-dichloro-1-methylcyclopropane-carboxamide-2-(2,6-dichloro-aaa-trifluoro-p-tolyl)hydrazone, acetoprole, ethiprole, fipronil, pyrafluprole, pyriprole, vaniliprole, allethrin, bifenthrin in), cyfluthrin, lambda-cyhalothrin, cypermethrin, alpha-cypermethrin, beta-cypermethrin, zeta-cypermethrin, deltamethrin, esfenvalerate, etofenprox, fenpropathrin, fenvalerate, flucythrinate, tau-fluvalinatev, permethrin permethrin, silafluofen, tralomethrin, nicotine, cartap, hydrochloride, thiocyclam, sulfoxaflor, acetamiprid, clothianidin, dinotefuran, imidacloprid, nitenpyram, thiacloprid , thiamethoxam, AKD-1022, spinosad, spinetoram, abamectin, emamectin, benzoate esters, lepimectin, milbemectin, hydroprene, kinoprene, fenoxycarb, pyriproxyfen, diafenthiuron, fenbutatinoxide), propargite, chlorfenapyr, buprofezin, bistrifluron, diflubenzuron, flufenoxuron, hexaflumuron, lufenuron, novaluron, teflubenzuron, cyromazine, methoxyfenozide, tebufenozide, azadirachtin, pyridaben, tolfenpyrad, flufenerim, indoxacarb, metaflumizone, tefluthrin, gamma-cyfluthrin, flupyradifurone furone), triflumezopyrim, afidopyropen, pymetrozine, flonicamid, spiraletramat, spidoxamat, dicloromezotiaz, chlorantraniliprole, cyantraniliprole, cyclaniliprole, tetraniliprole, flubendiamide, broflanilide, fluxametamide, dimpropyridaz, oxazosulfyl, fenmezoditiaz, isocycloseram.

[0039] In a preferred embodiment of the invention, at least one of these products is at least one fungicide selected from the group consisting of:

[0040] -Mode of action group A (nucleic acid metabolism): phenylamides, hydroxy-(2-amino-)pyrimidines, heteroaromatic compounds, carboxylic acids

[0041] - Mode of action group B (cytoskeleton and motor proteins): methylbenzimidazole carbamate, N-phenyl carbamate, benzamide (toluamide), thiazole carboxamide, phenyl urea, benzamide (pyridylmethylbenzamide), cyanoacrylate, aryl-phenyl ketone

[0042] - Mode of action group C (respiratory): pyrimidine amines, pyrazole-MET1, quinazolines, succinate dehydrogenase inhibitors, QoI (quinone external inhibitor) fungicides, QiI (quinone internal inhibitor) fungicides, dinitrophenyl crotonate, 2,6-dinitro-aniline, organotin compounds, thiophene-carboxamides, QoSI fungicides (quinone external inhibitor, schizolyl bromide-bound)

[0043] -Mode of action group D (protein synthesis): anilino-pyrimidines, enopyranuronic acid antibiotics, hexopyranosyl antibiotics, glucopyranosyl antibiotics, tetracycline antibiotics

[0044] -Mode of Action Group E (Signal Transduction): Naphthalene azathionines, phenylpyrroles, dicarboximides

[0045] - Mode of Action Group F (lipid synthesis or transport / membrane integrity or function): phosphothiol salts, dithiolanes, aromatic hydrocarbons, 1,2,4-thiadiazoles, carbamates, polyenes, piperidinyl-thiazole-isoxazolines

[0046] - Mode of action group G (sterol biosynthesis in membranes): demethylation inhibitors (SBI: class I), morpholines (SBI: class II), ketoreductase inhibitors (SBI: class III), thiocarbamates (SBI class IV), allylamines (SBI class IV),

[0047] -Mode of action Group H: Cell wall biosynthesis: polyoxins, carboxylic acid amides

[0048] - Mode of action group I (melanin synthesis in the cell wall): melanin biosynthesis inhibitors - reductase, melanin biosynthesis inhibitors - dehydratases, melanin biosynthesis inhibitors - polyketide synthases,

[0049] - Mode of action group P (host plant defense induction): benzothiadiazole (BTH), benzisothiazole, thiadiazole carboxamide, polysaccharides, plant extracts, phosphonates, isothiazoles

[0050] - Mode of action Group U (unknown mode of action): cyanoacetamide oxime, o-aminobenzoic acid, benzotriazine, benzenesulfonamide, pyridazinone, phenylacetamide, guanidine, thiazolidine, pyrimidone-hydrazone, 4-quinolyl-acetate, tetrazolyl oxime, pyranosyl glucopyranosyl antibiotics

[0051] - Mode of action group M (chemicals with multi-site activity): inorganic electrophiles, dithiocarbamates and related substances (electrophiles), phthalimides (electrophiles), chloronitriles (phthalonitriles), sulfonamides (electrophiles), biguanides (membrane disruptors, detergents), triazines, quinones (anthraquinones) (electrophiles), quinoxalines (electrophiles), maleimides (electrophiles), thiocarbamates (electrophiles).

[0052] In a preferred embodiment of the invention, at least one of these products is at least one fungicide selected from the group consisting of: Initium; Azoxystrobin; Boscalid; Carbendazim; Chlorothalonil; Copper; Copper; Cymoxanil; Difenoconazole; Dimethomorph; Dimethomorph; Dithianon; Morpholin-acetate; Epoxiconazole; Fenmorph; Fludioxonil; Fluquinconazole; Xemium; Folpet; Fungicide =Dan; Fosetyl-aluminum; Iprodione; KHP (potassium hydrogen phosphonate); Kresoxim-methyl; Mancozeb; Metalaxyl; Metconazole; Metconazole; Metiram / other EBDC (= Mancozeb, Maneb); Metraconazole; Tetracycline; Oxystrobin; Prochloraz; Propiconazole; Prothioconazole; Pyraclostrobin; Pyrimidine; Revysol, Cyclofosporin; Sithiopyrad; Sulfur; Thiophanate-methyl; Thiophanate-methyl; Tricyclazole; Tridemorph; Trichlorfonazole.

[0053] According to an embodiment, the base station remains stationary when the field equipment applies the field product to the farmland. That is, the base station can be stationary during at least most of the time, and in particular all of the time, when the field product is applied to the farmland. In this context, "at least most of" can mean at least 75%, at least 90%, or at least 95%. The base station can be movable, for example, so as to move it to a position where the base container can be refilled, to a different farmland, or to a more convenient position in or near the farmland. However, as described above, the base station will be stationary during most of the time when the field product is applied to the farmland. Alternatively, the base station can be completely stationary.

[0054] According to an embodiment, the base station further performs powering the field equipment. If the field equipment is electrically powered, this may include charging or recharging a battery. If the field equipment is fuel powered, this may include adding a suitable fuel, such as natural gas or hydrogen, to the field equipment.

[0055] Additionally or alternatively, the base station can further clean the field equipment. This can be performed as needed, or each time the field equipment is located at the base station to fill the field container.

[0056] According to an embodiment, the field equipment is an agricultural robot. This may be a robot with wheels, with chain drive and / or with legs.

[0057] Alternatively, the field equipment is an unmanned aerial spraying system (UASS), i.e. a drone adapted to apply field products to agricultural fields. This has the advantage of not causing damage to crops.

[0058] According to another embodiment, the field equipment can be heterogeneous, that is, the modular agricultural processing system can include different field equipment, such as agricultural robots and UASS. For example, the agricultural robot can apply field products to large connected areas of the farmland, while the UASS can apply field products to hard-to-reach parts of the farmland.

[0059] According to an embodiment, field data comprises at least one item in a group, and this group is made up of general field conditions, crop type, crop growth stage, crop disease, disease prediction, pest pressure, pest prediction, weed pressure, weed prediction, crop infection risk, abiotic stress, temperature, humidity, precipitation, weather conditions, weather forecast, soil characteristics, application time, previously applied product and / or product requirement.Described field data can be provided for each district in these districts of farmland.Before sowing, general field conditions such as soil, geography, microclimate or soil moisture can be mapped.Crop type can be given by crop identifier.Crop growth stage can be one of germination, shoot, bud development, leaf development, lateral branch formation, tillering, stem elongation or rosette growth, branch development, the growth of harvestable nutrient plant part, bolting, inflorescence appearance, heading, flowering, fruit development, ripening or ripening of fruit and seed, senescence and beginning dormancy, and can be provided by BBCH scale.Further weather conditions can be for example wind speed and wind direction. Soil properties may include the content of minerals and / or nutrients in the soil. The time of application may be important, in particular whether the application is carried out during the day (i.e. when there may be sunlight) or at night. Field data related to previously applied products may have been recorded throughout the season, even including data from past seasons, and can be used to prevent violations of product approval and regulatory requirements (e.g. regarding buffer zones in sensitive areas, or intervals before re-entry and harvest), promote sustainability aspects and perform (anti-)resistance management.

[0060] According to an embodiment, at least some of the field data is acquired in short intervals, which are one week or less, preferably one day or less. Alternatively or additionally, the field data is acquired in a short time span before applying the field product, which short time span is six hours or less, preferably two hours or less. This is particularly suitable for rapidly changing field data, such as crop growth stage, crop disease, pest pressure and / or weed pressure. The field data can be obtained by drones, robots, aircraft, satellites and / or field sensors.

[0061] According to an embodiment, determining the base product and / or mixture of base products to be used as field products and / or determining the product composition to be applied to these areas of the farmland is performed by an intelligent algorithm and / or an artificial intelligence system. The intelligent algorithm can use, for example, a knowledge system based on big data. The artificial intelligence system can also be referred to as an artificial intelligence decision support system. Specifically, these systems can be self-learning systems that can learn from previously taken actions and corresponding results. Specifically, the determination of the base product and / or mixture of base products to be used as field products and the determination of the product composition to be applied to these areas of the farmland can be performed together to take into account their mutual relationship. The intelligent algorithm and / or artificial intelligence system can also determine whether it is necessary to refill the base container with the base product based on the recorded base product usage and / or the predicted base product demand for processing the farmland.

[0062] According to an embodiment, determining the product composition to be applied to the zones of the farmland includes generating an application map, and applying the field product to the zones of the farmland according to the determined product composition includes reading the determined product composition at the current position of the field equipment from the application map. In addition to the product composition to be applied to the zones of the farmland, the application map may also include information about the application rate of the product composition.

[0063] According to an embodiment, the field equipment obtains current field data during the application of the field product, and determines the product composition to be applied to these areas of the farmland based on the current field data. Further, the application rate of the product composition can also be determined based on the current field data. Therefore, the application of the field product is customized for the current situation of the farmland. The field equipment can use at least one sensor (e.g., a camera) to collect current field data.

[0064] According to an embodiment, the determined product composition is achieved by mixing the field products, in particular using a direct injection system on board the field equipment. The mixing can be performed in one or several mixing chambers.

[0065] Alternatively or additionally, the determined product composition is achieved by applying the field products individually at a ratio corresponding to the determined product composition. That is, each field product can be sprayed by a separate nozzle.

[0066] A combination of the two options described above can also be performed, ie some field products can be mixed in the field equipment, while other products can be applied through separate nozzles.

[0067] According to an embodiment, the method further includes obtaining a desired effect as a user input, and determining the base product and / or mixture of base products to be used as a field product and / or determining the product composition to be applied to these zones of the farmland is further based on the desired effect. The user may be, for example, a farmer or another operator of a modular agricultural processing system. The user input may be performed directly at the base station of the modular agricultural processing system (e.g., via a user interface), or may be performed remotely (e.g., using an intelligent device and / or computer). The desired effect may be, for example, a measure of the level of investment and / or intensity to achieve the desired result. Alternatively or in addition, the desired effect may include a measure of crop quality, for example, whether they should be used as animal feed, high-end cuisine, seed production, and / or ethanol production. Alternatively or in addition, the desired effect may include an indication of a planned crop rotation so that the next season's crop has been taken into account when processing the farmland. In the case where the desired effect is the only user input, the farmer may not directly affect the modular agricultural processing system, but the modular agricultural processing system may operate only based on the desired effect and other rules (such as agreed field management practices and / or regulatory requirements) input by the user.

[0068] According to an embodiment, the method further includes determining an application time and applying the field product to the farmland at the determined application time. The application time may, for example, depend on changes in temperature, wind, humidity and / or crop sensitivity within a day, etc. The application time can be freely selected to achieve on-demand application of the farmland. The best time for application can also ensure that the best effect on the target is achieved (for example, related to diseases, pests and / or weeds). Further, due to the use of a modular agricultural processing system, the optimal application time is not limited by the availability of labor. In addition, the application of the product can be divided into two or more application instances, wherein the optimal application time is determined for each instance. Further, different application times can be selected for different zones of the farmland based on field data associated with the different zones.

[0069] According to an embodiment, when field equipment is arranged to process a specific portion of a farmland, a special base product and / or a mixture of base products to be used as a field product is determined for the specific portion of the farmland, and these base products are filled into field containers of the corresponding field equipment, so that the field products in these field containers are special base products and / or mixtures of base products determined for the specific portion of the farmland. The specific portion of the farmland may include one or more zones of the farmland. A specific portion of the farmland may be selected as the next portion of multiple consecutive portions of the farmland. Alternatively, a specific portion may be selected so that each specific portion includes a farmland zone with similar field data. In this case, a mixture may be determined so that it better matches the requirements of the farmland zone.

[0070] According to another aspect of the invention, a modular agricultural processing system is provided. The modular agricultural processing system comprises a base station, at least one field equipment and a computing unit. The base station has at least three basic containers, wherein each basic container is adapted to be filled with a basic product. Each field equipment comprises at least two field containers adapted to be filled with field products, and the field equipment is adapted to apply the field products to the farmland. The computing unit is adapted to determine the base products and / or mixtures of base products to be used as these field products and the product compositions consisting of these field products to be applied to the zones of the farmland based on the basic product data and the field data. The modular agricultural processing system is adapted to perform the method according to the above description. Advantages and further embodiments of the modular agricultural processing system correspond to those mentioned in the above description. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] These and other aspects of the invention will become apparent and be further elucidated with reference to the embodiments described by way of example in the following description and with reference to the accompanying drawings, in which:

[0072] Figure 1 shows a schematic side view of an embodiment of a modular agricultural processing system;

[0073] Figure 2 A schematic side view showing another embodiment of a modular agricultural processing system; and

[0074] Figure 3 A flow chart of a method for operating a modular agricultural processing system is shown.

[0075] It should be noted that these drawings are schematic only and are not drawn to scale. In the drawings, elements corresponding to elements already described may have the same reference numerals. Examples, embodiments or optional features, whether or not indicated as non-limiting, should not be construed as limiting the invention as claimed. DETAILED DESCRIPTION

[0076] Figure 1 A schematic side view of an embodiment of a modular agricultural processing system 1 is shown. The modular agricultural processing system 1 comprises a base station 2 and a plurality of unmanned aerial spraying systems (UASS) 3, i.e. drones, as an example of field equipment. Of course, the modular agricultural processing system 1 may also comprise more than one base station 2, and the number of UASS 3 may be greater than 1. Figure 1 Three UASS 3 are shown.

[0077] The base station 2 comprises at least three (four in this example) base containers 4, each of which is filled with a base product 5. The base product 5 may be a chemical product, a biological product, a fertilizer, a nutrient, a biostimulant, a pheromone, water, a tank mix aid, a detergent, a bulking agent, a defoamer, a water quality regulator and / or a pH regulator, or a mixture thereof. Figure 1 The four base containers 4 shown in the figure are of the same size, but different sizes may be used, in particular in relation to the estimated demand for the respective base products 5, for example, a base container 4 containing water (e.g. used as a carrier for other base products 5) may be larger than a base container 4 containing a specific pheromone. The base station 2 further comprises a computing unit 6 adapted to determine the base product 5 and / or a mixture of base products 5 to be used as a field product, and for each of a plurality of zones of the farmland, to determine a product composition consisting of the field products to be applied to that zone of the farmland. A pipe 7 is connected to each base container 4 and converges in a filling pipe 8, i.e., the base products 5 from the base containers 4 can flow together in the filling pipe 8. Valves and / or pumps that control the flow of the base product 5 based on the base product 5 and / or the mixture of base products 5 to be used as a field product determined by the computing unit 6 are not shown in the figure to avoid confusion.

[0078] Each UASS 3 comprises two field containers 9 adapted to be filled with field products 10, wherein the field products 10 are base products 5 or mixtures of base products 5. The UASS 3 may comprise more than two field containers 9, but the number of field containers 9 per UASS 3 should be less than the number of base containers 4 in the base station 2. The UASS 3 further comprises nozzles 11 so that they can apply the field products 10 to the farmland. In this embodiment, the nozzles 11 can be operated individually so that the product composition of the field products 10 that has been determined by the calculation unit 6 is applied to the farmland.

[0079] Figure 2A schematic side view of another embodiment of a modular agricultural processing system 1 is shown. According to this embodiment, each base container 4 is equipped with a filling pipe 8, so that the base product 5 can be filled individually into the field container 9 of the field equipment. Likewise, the base product 5 and / or the mixture of base products 5 to be used as the field product 10 is determined by a computing unit 6, which in this case is a remote computing unit 6. The computing unit 6 wirelessly transmits the determined base product 5 and / or the mixture of base products 5 to be used as the field product 10 and the determined product composition consisting of the field products 10 to be applied to these areas of the agricultural field. The control unit (not shown) of the base station 2 receives the determined base product 5 and the mixture of base products 5 to be used as the field product 10 and controls the filling of the base product 5 into the field container 9 accordingly. The determined product composition can be received by the base station 2 and then forwarded to the field equipment, or can be received directly by the field equipment.

[0080] In this embodiment, the field equipment is an agricultural robot 12. These agricultural robots also include a field container 9 and a nozzle 11 to apply field products 10 to the farmland. In this embodiment, the field products 10 are mixed in a mixing chamber according to the determined product composition and then applied through a nozzle 11.

[0081] The base station 2 can remain stationary while the field equipment 3 or 12 applies the field product 10 to the farmland. In addition, the base station 2 can further power the field equipment 3 or 12 and / or can be adapted to clean the field equipment 3 or 12. In addition, the base station 2 can include a user interface, or can be connected to a user interface, so as to allow a user (e.g., a farmer) to input a desired effect. The desired effect can include an expected crop rotation, previous crops and potentially related input factors, and / or an investment level / intensity to achieve a desired result.

[0082] Figure 3 A flow chart of a method for operating a modular agricultural processing system 1 is shown. According to the method, base product data 20 associated with a base product 5 and field data 21 associated with field conditions of an agricultural field are provided. The base product data 20 may include active ingredient information, agricultural performance information, formulation, viscosity, surface tension, turbidity, phase separation risk, loading, physical compatibility data, chemical data, crop registration, health defect registration, and / or mixture registration. The field data 21 may include general field conditions, crop type, crop growth stage, crop disease, disease prediction, pest pressure, pest prediction, weed pressure, weed prediction, crop infection risk, abiotic stress, temperature, humidity, precipitation, weather conditions, weather forecast, soil properties, application time, previously applied products, and / or product requirements.

[0083] Based on the base product data 20 and the field data 21, a base product 5 and / or a mixture of base products 5 to be used as field product 10 is determined 22. Said determination 22 may be performed by calculation 6 using intelligent algorithms and / or artificial intelligence systems.

[0084] Based on the determined 22 base product 5 and / or mixture of base products 5 , the base product 5 is filled 23 into the field container 9 of the field equipment 3 or 12 so that the field product 10 in the field container 9 is the determined base product 5 and / or mixture of base products 5 .

[0085] Furthermore, based on the basic product data 20 and the field data 21, for each of the plurality of zones of the farmland, a product composition 25 consisting of the field products 10 to be applied to the zone of the farmland is determined 24. The determination 24 can also be performed by the computing unit 6 using an intelligent algorithm and / or an artificial intelligence system. In particular, the determination 24 can be performed together with the determination 22.

[0086] Finally, these field products 10 are applied 26 to the agricultural field according to the determined product composition 25 .

[0087] When the above method is used together with the modular agricultural treatment system 1, the optimal product composition 25 of the base product 5 is applied to the farmland, where "optimal" can be an overall response to all relevant conditions of the farmland. This can ensure the best input-output ratio, where the input refers specifically to the base product 5 used, and the output refers to the agricultural effect, the increase of profitability and the avoidance of overuse of products, without the need to (re)formulate existing products under changing conditions.

[0088] As a specific example, the control of potato Phytophthora (late blight) is discussed. The control of late blight usually requires multiple applications throughout the season. In addition to tolerant varieties, farmers use protectant and systemic products to prevent infection. Late blight not only damages the green leaves of the plants, but also causes latent infection in newly formed tubers. Such tubers not only cause storage problems, but can also serve as the starting point for new epidemics in the field. The effective development of the disease in the field mainly requires the combination of two factors: favorable climatic conditions (mainly sufficient moisture) and inoculum, which can come from infected tubers or neighboring fields.

[0089] To optimize control strategies, autonomous application systems can play an important role in several ways: remotely sensing areas of the field where infected plants or diseases are beginning to spread; mapping field climate conditions to identify high-risk areas that are more prone to disease, such as areas with higher humidity; and applying the optimal mixture of base products5 at different growth and disease stages, at the optimal time and dosage, and at spray intervals dictated by field conditions, without being limited by labor availability.

[0090] According to the above method, "target performance" is optimized by applying a product combination consisting of at least two field products 10 as needed, depending on the disease situation, crop health status, and especially the field conditions at the time of application. The required dosage can be adjusted within the field or within a sub-area of ​​the field.

[0091] Specifically, the following steps can be performed: before sowing, field conditions such as soil, geography, microclimate and / or soil moisture can be mapped. Intelligent algorithms can be used to define risk zones within the field according to the development needs of crops and late blight. Growth and disease development can be monitored physically or remotely in short intervals, such as using drones, aircraft or satellite images or field sensors. The captured data can be processed and linked to historical information, risk zone mapping and farmers' expectations. Intelligent algorithms can be used to determine the base product 5 and / or mixture of base products 5 delivered to the farmland by field equipment 3 or 12, allowing the use of an onboard direct injection system to generate the best product mixture given by the product composition 25. The amount and spatial distribution of the combined active ingredients that have been applied and may be applied can be taken into account to prevent violations of product approval and regulatory requirements (e.g., buffer zones in sensitive areas, re-entry and pre-harvest intervals), promote sustainability, resistance management and meet farmers' expectations. The field container 9 can be filled autonomously by the base station 2. The field product 10 can then be used to generate the best mixture. If necessary, multiple flights of the UASS 3 can be initiated to complete the mission. Quality assessment can be performed by measuring the impact on disease and crop development through physical inspection or remote sensing (e.g. using drones, aircraft or satellite imagery). If a shortage of base product 5 is expected, the base station 2 can provide automatic feedback. The base product 5 can be refilled or an empty base container 4 can be replaced. All activities can be recorded and the relevant information can be transferred directly to the farm documentation system.

[0092] It must be noted that embodiments of the present invention are described with reference to different subject matters. In particular, some embodiments are described with reference to method type claims, while other embodiments are described with reference to device type claims. However, those skilled in the art will appreciate from the above and following descriptions that, unless otherwise notified, any combination of features relating to different subject matters, in addition to any combination of features belonging to one type of subject matter, is also considered to be disclosed with the present application. However, all features may be combined to provide synergistic effects, rather than simply the addition of these features.

[0093] Although the present invention has been shown and described in detail in the drawings and the foregoing description, such showing and description should be considered illustrative or exemplary rather than restrictive. The present invention is not limited to the disclosed embodiments. Through the study of the drawings, the present disclosure and the appended claims, those skilled in the art can understand and implement other variations of the disclosed embodiments when practicing the claimed invention. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article one / a ("a" or "an") does not exclude multiple. A single processor or other unit can perform the functions of several items stated in the claims. The fact that certain measures are stated in different dependent claims does not mean that a combination of these measures cannot be used to advantage. Any figure marks in the claims should not be interpreted as limiting the scope.

Claims

1. A method for operating a modular agricultural treatment system (1) for treating harmful organisms and / or plant health defects in agricultural fields, wherein: The modular agricultural processing system (1) comprises: A base station (2) having at least three base containers (4), wherein each base container (4) is filled with a base product (5); and at least one field equipment (3; 12), each field equipment (3; 12) comprising at least two field containers (9), wherein each field container (9) is adapted to be filled with field products (10), and wherein the field equipment (3; 12) is adapted to apply the field products (10) to the farmland; And the method comprises: providing basic product data (20) related to these basic products (5); Providing field data related to the field condition of the farmland (21); Based on the base product data (20) and the field data (21), determining a base product (5) and / or a mixture of base products (5) to be used as the field product (10); Filling the base products (5) into the field containers (9) of the field equipment (3; 12) so that the field products (10) in the field containers (9) are the determined field products (10); Based on the base product data (20) and the field data (21), for each of a plurality of zones of the farmland, determining a product composition (25) consisting of the field products (10) to be applied to the zone of the farmland; and The field products (10) are applied to the zones of the agricultural field by means of the field equipment (3; 12) according to the determined product composition (25).

2. The method according to claim 1, wherein: The base products (5) are at least one of a group consisting of chemical products, biological products, fertilizers, nutrients, biostimulants, pheromones, water, tank mix adjuvants, detergents, extenders, defoamers, water quality regulators and pH regulators, or a mixture of at least two of the group.

3. The method according to claim 1 or 2, wherein: The base station (2) further performs power supply to the field equipment (3; 12) and / or cleaning of the field equipment (3; 12).

4. The method according to any one of claims 1 to 3, wherein: The field equipment (3; 12) is an agricultural robot (12) and / or an unmanned aerial spraying system (3).

5. The method according to any one of claims 1 to 4, wherein: The field data (21) includes at least one item from a group consisting of general field conditions, crop type, crop growth stage, crop diseases, disease forecasts, pest pressure, pest forecasts, weed pressure, weed forecasts, crop infection risk, abiotic stress, temperature, humidity, precipitation, weather conditions, weather forecasts, soil properties, application time, previously applied products and / or product requirements.

6. The method according to any one of claims 1 to 5, wherein: At least some of the field data (21) is acquired within short intervals of a week or less, preferably a day or less, and / or within a short time span of six hours or less, preferably two hours or less, prior to application of the field products (10).

7. The method according to any one of claims 1 to 6, wherein: Determining the base product (5) and / or mixture of base products (5) to be used as these field products (10) and / or determining the product composition (25) to be applied to these areas of the farmland is performed by intelligent algorithms and / or artificial intelligence systems.

8. The method according to any one of claims 1 to 7, wherein: Determining the product composition to be applied to the zones of the agricultural field (25) includes generating an application map; and Applying the field products (10) to the zones of the agricultural field according to the determined product composition (25) includes reading the determined product composition (25) at the current position of the field equipment (3; 12) from the application map.

9. The method according to any one of claims 1 to 8, wherein: Determining the product composition (25) to be applied to the zones of the agricultural field is further based on current field data (21) obtained by the field equipment (3; 12) during application of the field product (10).

10. The method according to any one of claims 1 to 9, wherein: The determined product composition (25) is achieved by mixing the field products (10) using a direct injection system, in particular on-board the field equipment (3; 12).

11. The method according to any one of claims 1 to 10, wherein: The determined product composition (25) is achieved by applying the field products (10) individually at a ratio corresponding to the determined product composition (25).

12. The method according to any one of claims 1 to 11, wherein: The method further includes obtaining a desired effect as a user input; and The determination of the base product (5) and / or mixture of base products (5) to be used as the field products (10) and / or the determination of the product composition (25) to be applied to the areas of the farmland is further based on the desired effect.

13. The method according to any one of claims 1 to 12, wherein: The method further comprises determining a time of administration; and The field products (10) are applied to the farmland at the determined application time.

14. The method according to any one of claims 1 to 13, wherein: When the field equipment (3; 12) is arranged to process a specific part of the field, determining for said specific portion of the farmland a specific base product (5) and / or a mixture of base products (5) to be used as the field product (10); and The base products (5) are filled into field containers (9) of the corresponding field equipment (3; 12) so that the field products (10) in these field containers (9) are specialized base products (5) and / or mixtures of base products (5) determined for a specific part of the farmland.

15. A modular agricultural processing system (1), comprising A base station (2) having at least three basic containers (4), wherein: Each base container (4) is adapted to be filled with a base product (5); At least one field equipment (3; 12), wherein each field equipment (3; 12) comprises at least two field containers (9), wherein each field container (9) is adapted to be filled with field products (10) and the field equipment (3; 12) is adapted to apply the field products (10) to the farmland; and a calculation unit (6) adapted to determine, based on the base product data (20) and the field data (21), base products (5) and / or mixtures of base products (5) to be used as the field products (10) and product compositions (25) consisting of the field products (10) to be applied to the zones of the agricultural field; Wherein, the modular agricultural processing system (1) is adapted to perform the method according to any one of claims 1 to 14.

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