Modular agricultural treatment system and method for operating the same

Abstract

The invention relates to a method for operating a modular agricultural treatment system (1) that can be used to treat harmful organism and / or plant health defects in a field of farmland. A modular agricultural processing system (1) comprises a base station (2) and at least one field device (3; 12). The base station (2) has at least two base containers (4), each base container (4) being filled with a base product (5). Each field device (3; 12) comprises a field container (9). According to the method, basic product data (20) relating to a basic product (5) and field data (21) relating to a field situation of the field are provided. Based on the base product data (20) and the field data (21), a mixture (23) of the base product (5) to be used as the field product (10) is determined. Filling a base product (5) into the field device (3; 12), such that the field product (10) in the field container (9) is the determined mixture (23) of these base products (5), and by means of the field device (3; 12) applying the field product (10) to the field. The invention further relates to a corresponding modular agricultural treatment system (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 comprises a base station and at least one field equipment. The base station can be located or placed near the farmland so that (multiple) field equipment does not have to travel unnecessary distances. The base station comprises at least two base containers, wherein each base container is filled with a base product. Specifically, the base products in different base containers are different from each other. More specifically, the first base product in the first base container may be different from the second base product in the second base container. Preferably, the modular agricultural processing system comprises a plurality of field equipment so that the farmland can be processed in a timely manner. Each field equipment comprises a field container. Specifically, the field container is adapted to be filled with a field product, and the field equipment is adapted to apply the field product to the farmland. More specifically, the field equipment 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, a mixture of base products to be used as field products is determined based on the base product data and the field data. In this context, a "mixture" includes the case where only one base product is used, that is, the content of one base product in the mixture is 100% and the content of (multiple) other base products is 0%. This determination is to make the mixture optimal for the farmland (for example, to treat harmful organisms and / or plant health defects). The mixture can be determined so that the resulting mixture 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 mixture of the base product. In other words, the field product is obtained by mixing the base product. Finally, the field product is applied to the farmland by the field equipment. The application of the field product can be carried out by a direct injection system.

[0013] Thus, the optimal mixture of base products is applied to 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.

[0014] 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.

[0015] 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.

[0016] 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.

[0017] 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):

[0018] b1) lipid biosynthesis inhibitors;

[0019] b2) acetolactate synthase inhibitors (ALS inhibitors);

[0020] b3) photosynthesis inhibitors;

[0021] b4) protoporphyrinogen-IX oxidase inhibitors,

[0022] b5) bleaching agent herbicides;

[0023] b6) Enolpyruvylshikimate 3-phosphate synthase inhibitors (EPSP inhibitors);

[0024] b7) glutamine synthetase inhibitors;

[0025] b8) 7,8-dihydropteroate synthase inhibitors (DHP inhibitors);

[0026] b9) mitotic inhibitors;

[0027] b10) Very long chain fatty acid synthesis inhibitors (VLCFA inhibitors);

[0028] b11) cellulose biosynthesis inhibitors;

[0029] b12) decoupler herbicide;

[0030] b13) auxin herbicides;

[0031] b14) auxin transport inhibitors; and

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] In a preferred embodiment of the invention, at least one of these products is at least one fungicide selected from the group consisting of:

[0037] -Mode of action group A (nucleic acid metabolism): phenylamides, hydroxy-(2-amino-)pyrimidines, heteroaromatic compounds, carboxylic acids

[0038] - 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

[0039] - 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)

[0040] -Mode of action group D (protein synthesis): anilino-pyrimidines, enopyranuronic acid antibiotics, hexopyranosyl antibiotics, glucopyranosyl antibiotics, tetracycline antibiotics

[0041] -Mode of Action Group E (Signal Transduction): Naphthalene azathionines, phenylpyrroles, dicarboximides

[0042] - 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

[0043] - 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),

[0044] -Mode of action Group H: Cell wall biosynthesis: polyoxins, carboxylic acid amides

[0045] - Mode of action group I (melanin synthesis in the cell wall): melanin biosynthesis inhibitors - reductase, melanin biosynthesis inhibitors - dehydratases, melanin biosynthesis inhibitors - polyketide synthases,

[0046] - Mode of action group P (host plant defense induction): benzothiadiazole (BTH), benzisothiazole, thiadiazole carboxamide, polysaccharides, plant extracts, phosphonates, isothiazoles

[0047] - 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

[0048] - 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).

[0049] 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.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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.

[0054] 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.

[0055] 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.

[0056] According to an embodiment, the field data includes at least one item in a group, the group consisting of general field conditions, crop types, crop growth stages, crop diseases, disease predictions, pest pressure, pest predictions, weed pressure, weed predictions, crop infection risk, abiotic stress, temperature, humidity, precipitation, weather conditions, weather forecasts, soil properties, application time, previously applied products and / or product requirements. The field data can be provided for multiple zones in the farmland. In this context, the term "zone" should be understood as a sub-field area or part of a farmland, that is, the farmland can be spatially divided into more than one zone, wherein each zone can have different attributes. Before sowing, general field conditions such as soil, geography, microclimate or soil moisture can be mapped. The crop type can be given by a crop identifier. The 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 development of harvestable vegetative plant parts, bolting, inflorescence emergence, heading, flowering, fruit development, ripening or maturation of fruit and seed, senescence and beginning dormancy, and can be provided by the BBCH scale. Further weather conditions can be, for example, wind speed and wind direction. Soil properties can include the content of mineral matter and / or nutrients in the soil. Application time may be very important, especially application is during the day (that is, when there may be sunlight) or at night. The field data related to the product previously applied may have been recorded throughout the season, and can even include the data of past seasons, and can be used to prevent violation of product approval and regulatory requirements (for example, about the buffer zone of sensitive areas or the interval before re-entry and harvest), promote sustainability and carry out (anti-) resistance management.

[0057] According to an embodiment, at least some of the field data is acquired in short intervals, which are one week or shorter, preferably one day or shorter. This is particularly applicable to 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.

[0058] According to an embodiment, an intelligent algorithm and / or an artificial intelligence system is used to determine the mixture of the base products. The intelligent algorithm may use, for example, a knowledge system based on big data. The artificial intelligence system may also be referred to as an artificial intelligence decision support system. Specifically, these systems may be self-learning systems that can learn from previously taken actions and corresponding results.

[0059] According to an embodiment, the base products are mixed in a base station and then the mixture of the base products is filled into the field container. The mixing in the base station can be performed by using one or more mixing chambers and adjusting the flow of the base products to the mixing chamber(s) accordingly. Alternatively or additionally, the mixing can be performed by adding the base products to a dedicated mixing tank, where the base products can also be stirred.

[0060] Alternatively or additionally, the base products may 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 mixture. The field container may include means for stirring the base products, or the base products may be thoroughly mixed by filling the field container with the base products and / or shaking the field container (e.g. due to movement of field equipment).

[0061] As a further alternative, the two above options 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.

[0062] 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 a meter measuring 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 by an intelligent algorithm and / or an artificial intelligence system based on the recorded usage of the base product and / or the predicted demand for the base product used to treat the farmland.

[0063] According to an embodiment, the method further includes obtaining a desired effect as a user input, and further determining a mixture of base products to be used as field products 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 a base station of the modular agricultural processing system (e.g., via a user interface), or may be performed remotely (e.g., using a smart device and / or computer). The desired effect may be, for example, a measure of the level and / or intensity of investment to achieve a 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 is already taken into account when processing 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.

[0064] 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.

[0065] According to an embodiment, an application map is generated, and field products are applied at a certain rate according to the application map. Specifically, the farmland may include multiple zones, and field products may be applied at different rates for each of these zones. The changing rate may be achieved, for example, by changing the moving speed of the field equipment, changing the nozzle used, and / or changing the spraying pressure. In the latter two cases, the droplet size may also change - therefore, a combination of two of the options may change both the rate and the droplet size.

[0066] According to an embodiment, the field equipment obtains current field data just before and / or during the application of the field product, and applies the field product at a rate that depends on the current field data obtained. Therefore, the application of the field product is customized to the current situation of the farmland. In this context, "just before..." may mean that the current field data is obtained at most one day, preferably at most one hour before the application of the field product. In addition, the field equipment itself can collect some field data, such as using a camera. Then, the application rate can depend on the currently collected field data.

[0067] According to an embodiment, when field equipment is arranged to process a specific portion of a farmland, a special mixture is determined for the specific portion of the farmland, and the base product is filled into the field container of the corresponding field equipment according to the special mixture determined for the specific portion of the farmland. The specific portion of the farmland may include one or more zones of the farmland. The specific portion of the farmland may be selected as the next portion of multiple consecutive portions of the farmland. Alternatively, the specific portions may be selected so that each specific portion includes a farmland zone with similar field data. In this case, the mixture may be determined so that it better matches the requirements of the farmland zone.

[0068] 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 two base containers, wherein each base container is adapted to be filled with a base product. Each field equipment comprises a field container adapted to be filled with a field product, and the field equipment is adapted to apply the field product to the farmland. The computing unit is adapted to determine a mixture of these base products to be used as field products based on base product data and 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

[0069] 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:

[0070] Figure 1 shows a schematic side view of an embodiment of a modular agricultural processing system;

[0071] Figure 2 A schematic side view of another embodiment of a modular agricultural processing system is shown; and

[0072] Figure 3 A flow chart of a method for operating a modular agricultural processing system is shown.

[0073] 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

[0074] 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.

[0075] The base station 2 comprises at least two (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 calculation unit 6, which is adapted to determine the mixture of the base products 5. 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 products 5 based on the mixture determined by the calculation unit 6 are not shown in the figure to avoid confusion.

[0076] Each UASS 3 comprises a field container 9 adapted to be filled with a field product 10, wherein the field product 10 is a mixture of the base product 5. The UASS 3 further comprise nozzles 11 so that they can apply the field product 10 to the agricultural field.

[0077] Figure 2 A 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. Again, the mixture of the base products 5 is determined by the computing unit 6, which in this case is a remote computing unit 6. The computing unit 6 transmits the determined mixture wirelessly. The control unit (not shown) of the base station 2 receives the determined mixture and controls the filling of the base products 5 into the field container 9 accordingly.

[0078] 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 field.

[0079] 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.

[0080] 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.

[0081] Based on the base product data 20 and the field data 21 a mixture 23 of the base product 5 to be used as a field product 10 is determined 22. Said determination 22 of the mixture 23 may be performed by calculation 6 using intelligent algorithms and / or artificial intelligence systems.

[0082] Then, the base product 5 is filled 24 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 mixture 23 of the base product 5. Finally, the field product 10 is applied 25 to the agricultural field.

[0083] When the above method is used together with the modular agricultural treatment system 1, the optimal mixture 23 of the base products 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 products 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.

[0084] 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.

[0085] 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 best time and dosage, and at spray intervals dictated by field conditions, without being limited by labor availability.

[0086] For mixtures 23, a single base product 5 or a combination of base products (including one or more adjuvants) is used to optimize the "target performance" 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.

[0087] 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 based on the development needs of the crop and late blight. Growth and disease development can be monitored physically or remotely at 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 best mixture 23 and its spatial distribution within the field and the optimal dosage rate. This mixture 23 produced on demand may change during the day as weather conditions (e.g., temperature, wind, humidity, crop sensitivity) change. Similarly, this mixture 23 produced on demand will also change as crops and diseases continue to develop to ensure the best protection for yield and quality with minimal impact on nature. 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 aspects, resistance management and meet farmers' expectations. The field containers 9 can be filled autonomously by the base station 2. If necessary, multiple UASS flights can be launched to complete the mission. Quality assessment can be done by measuring the impact on disease and crop development through physical inspection or remote sensing (e.g. using drones, aircraft or satellite imagery). If shortages of base product 5 are 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.

[0088] 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.

[0089] 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 two base containers (4) and at least one field equipment (3; 12), wherein each base container (4) is filled with a base product (5), wherein each field equipment (3; 12) comprises a field container (9), and wherein 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 mixture (23) of the base products (5) to be used as the field product (10); Filling the base products (5) into the field container (9) of the field equipment (3; 12) so that the field product (10) in the field container (9) is a determined mixture (23) of the base products (5); and The field product (10) is applied to the farmland by means of the field equipment (3; 12).

2. The method according to claim 1, wherein: The base station (2) remains stationary while the field equipment (3; 12) applies the field product (10) to the farmland.

3. The method according to claim 1 or 2, 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.

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

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

6. The method according to any one of claims 1 to 5, 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.

7. The method according to any one of claims 1 to 6, wherein: At least some of the field data (21) are acquired in short intervals, which are one week or shorter, preferably one day or shorter.

8. The method according to any one of claims 1 to 7, wherein: Determining the mixture (23) of these base products (5) is performed by intelligent algorithms and / or artificial intelligence systems.

9. The method according to any one of claims 1 to 8, wherein: mixing the base products (5) in the base station (2) and filling the mixture (23) of the base products (5) into the field container (9); and / or The base products (5) are respectively filled into the field container (9), and the amount of each base product (5) filled into the field container (9) is selected according to the determined mixture (23).

10. The method according to any one of claims 1 to 9, wherein: The method further includes obtaining a desired effect as a user input; and Determining the mixture (23) of the base products (5) to be used as the field product (10) is further based on the desired effect.

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

12. The method according to any one of claims 1 to 11, wherein: generating an application map; and The field product (10) is applied at a certain rate according to the application map.

13. The method according to any one of claims 1 to 12, wherein: The field equipment (3; 12) obtains current field data (21) just before and / or during application of the field product (10); and The field product (10) is applied at a rate dependent upon the current field data (21) obtained.

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 a specific mixture (23) for the specific portion of the farmland; and The base products (5) are filled into the field containers (9) of the respective field equipment (3; 12) according to the special mixture (23) determined for the specific section of the field.

15. A modular agricultural processing system (1), comprising A base station (2) having at least two 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 a field container (9) adapted to be filled with a field product (10), and the field equipment (3; 12) is adapted to apply the field product (10) to the farmland; and a calculation unit (6) adapted to determine a mixture (23) of the base products (5) to be used as the field product (10) based on the base product data (20) and the field data (21); 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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