31:T334b,function* createCropTabComponent(cropData) { const container = html`

`; const style = html` `; const el = htl.html`

`; container.appendChild(style); container.appendChild(el); container.value = cropData; yield container; Vue.createApp({ data() { return { activeCrop: cropData[0].name, originalData: JSON.parse(JSON.stringify(cropData)), cropData: cropData, charts: {} }; }, mounted() { this.cropData.forEach((crop) => this.createChart(crop)); }, methods: { resetCrop(crop) { // Finde die ursprünglichen Daten für diese Kultur const original = this.originalData.find((c) => c.name === crop.name); if (!original) return; // Werte zurücksetzen crop.price = original.price; crop.avgYield = original.avgYield; crop.costs = original.costs; crop.nPrice = original.nPrice; crop.yieldSteps = [...original.yieldSteps]; // Chart und Container-Value aktualisieren this.updateChart(crop); }, updateAvgYield(crop) { const oldAvgYield = crop.yieldSteps[3]; const newAvgYield = crop.avgYield; const scalingFactor = newAvgYield / oldAvgYield; crop.yieldSteps = crop.yieldSteps.map((value) => value * scalingFactor); this.updateChart(crop); }, updateChart(crop) { const chart = this.charts[crop.name]; chart.data.datasets[0].data = crop.nSteps.map((step, i) => ({ x: step, y: this.createGM( crop, crop.yieldSteps[i], step ) })); const methods = [ "Mittelwert", "Minimum", "Q1", "Q2", "Q3", "Q4", "Maximum" ]; methods.forEach((m, idx) => { chart.data.datasets[idx + 1].data = this.createHelperDataset(crop, m); }); chart.update(); container.value = this.cropData; }, switchTab(cropName) { this.activeCrop = cropName; }, createGM(crop, cropYield, nAmount) { return crop.price * cropYield - crop.nPrice * nAmount - crop.costs; }, createHelperDataset(crop, method) { return crop.nSteps.map((step, i) => { //const absoluteN = (step / 100) * crop.duevNValue; // console.log(absoluteN) return { x: step, y: this.createGM( crop, table_data.find( (r) => r.Kultur === crop.name && r.Methode === method )[step + "% N-DüV"], step ) }; }); }, createChart(crop) { const canvas = document.getElementById(`${crop.name}_chart`); const ctx = canvas.getContext("2d"); const options = { type: "scatter", data: { datasets: [ { label: `Deckungsbeitrag ${_.capitalize(crop.name)} (€/ha)`, borderColor: crop.color, backgroundColor: "#fff", pointRadius: 7, pointBorderWidth: 4, showLine: true, data: crop.nSteps.map((step, i) => ({ x: step, y: this.createGM( crop, crop.yieldSteps[i], step ) })) }, { label: "Mittelwert", borderDash: [10], pointRadius: 0, showLine: true, data: this.createHelperDataset(crop, "Mittelwert") }, { label: "Min.", pointRadius: 0, showLine: true, borderWidth: 0, data: this.createHelperDataset(crop, "Minimum") }, { label: "Q1", pointRadius: 0, showLine: true, borderWidth: 0, fill: "-1", backgroundColor: "rgba(0,0,0,0.05)", data: this.createHelperDataset(crop, "Q1") }, { label: "Q2", pointRadius: 0, showLine: true, borderWidth: 0, fill: "-1", backgroundColor: "rgba(0,0,0,0.1)", data: this.createHelperDataset(crop, "Q2") }, { label: "Q3", pointRadius: 0, showLine: true, borderWidth: 0, fill: "-1", backgroundColor: "rgba(0,0,0,0.2)", data: this.createHelperDataset(crop, "Q3") }, { label: "Q4", pointRadius: 0, showLine: true, borderWidth: 0, fill: "-1", backgroundColor: "rgba(0,0,0,0.1)", data: this.createHelperDataset(crop, "Q4") }, { label: "Spanne", pointRadius: 0, showLine: true, borderWidth: 0, fill: "-1", backgroundColor: "rgba(0,0,0,0.05)", data: this.createHelperDataset(crop, "Maximum") } ] }, options: { scales: { x: { title: { display: true, text: "Stickstoff gedüngt (kg N/ha) →", align: "end" }, type: "linear", min: 0, max: crop.nMax, offset: true }, y: { title: { display: true, text: "Deckungsbeitrag (€/ha) →", align: "end" } } }, responsive: false, plugins: { tooltip: { filter: (item) => item.datasetIndex === 0, callbacks: { title: (context) => `${context[0].parsed.x.toFixed(1)} kg N-gedüngt / ha`, label: (context) => [ `Deckungsbeitrag: ${context.parsed.y.toFixed(0)} €/ha`, `${Math.round(crop.yieldSteps[context.dataIndex])} ${crop.yieldType}` ], } }, legend: { labels: { filter: (item) => !["Min.", "Q1", "Q2", "Q3", "Q4"].includes(item.text) } }, dragData: { round: 1, onDragEnd: (e, datasetIndex, index, value) => { crop.yieldSteps[index] = (value.y + Number(crop.costs) + crop.nPrice * value.x) / Number(crop.price); container.value = this.cropData; container.dispatchEvent(new Event("input")); } } } } }; this.charts[crop.name] = Vue.shallowRef(new Chart(ctx, options)); } } }).mount(el); }32:T24bf,cropDataDEPRECATED = [ { name: "Winterweizen", color: "#4e79a7", avgYield: 80, maxYield: 150, price: 25, costs: 612, nPrice: 0.9, nSteps: [ 0, 100, 140, 180, 230 ], nMax: 230, yieldSteps: [ 50.28, 69.58, 75.23, 79.06, 80 ], yieldStepsMedian: [ 50.3491, 68.5069, 74.4503, 78.0496, 80.4115 ], yieldStepsMittelwert: [ 50.2842, 69.579, 75.2346, 79.0567, 80 ], yieldStepsQ1: [ 28.5018, 50.4358, 56.4533, 57.3545, 55.5377 ], yieldStepsQ2: [ 38.2916, 62.3976, 69.8988, 73.6621, 73.8108 ], yieldStepsQ3: [ 60.7067, 77.7996, 82.8707, 87.4014, 89.973 ], yieldStepsQ4: [ 77.3756, 87.9199, 93.5355, 96.5055, 97.605 ], yieldStepsMinimum: [ 21.1799, 37.7614, 43.3946, 48.5022, 47.3794 ], yieldStepsMaximum: [ 92.5716, 93.9966, 96.6818, 101.1808, 103.4432 ] }, { name: "Wintergerste", color: "#f28e2c", avgYield: 70, maxYield: 150, price: 16, costs: 533, nPrice: 0.9, nMax: 190, nSteps: [ 0, 90, 120, 160, 190 ], yieldSteps: [ 46.41, 63.16, 68.11, 70.63, 70 ], yieldStepsMedian: [ 46.698, 64.6582, 70.1782, 69.8771, 70.3652 ], yieldStepsMittelwert: [ 46.4054, 63.1553, 68.1064, 70.6337, 70 ], yieldStepsQ1: [ 23.8565, 44.6911, 49.7977, 53.3806, 55.0721 ], yieldStepsQ2: [ 34.5449, 57.6507, 63.2934, 63.5433, 61.7717 ], yieldStepsQ3: [ 56.0544, 70.0039, 74.0273, 78.5312, 77.8014 ], yieldStepsQ4: [ 70.95, 82.4127, 84.7867, 88.0608, 85.8212 ], yieldStepsMinimum: [ 20.8986, 34.757, 39.3764, 40.7295, 39.8901 ], yieldStepsMaximum: [ 77.546, 85.6642, 87.649, 90.1277, 90.6562 ] }, { name: "Winterraps", color: "#e15759", avgYield: 40, maxYield: 200, price: 50, costs: 612, nPrice: 0.9, nSteps: [ 0, 110, 140, 170, 200 ], yieldSteps: [ 29.63, 36.62, 38.39, 39.64, 40 ], yieldStepsMedian: [ 31.4882, 37.3774, 38.1086, 39.1557, 39.2074 ], yieldStepsMittelwert: [ 29.6337, 36.6168, 38.3918, 39.6369, 40 ], yieldStepsQ1: [ 16.7588, 27.197, 29.1689, 29.4657, 29.8858 ], yieldStepsQ2: [ 23.5421, 33.1125, 36.1201, 36.3921, 37.4396 ], yieldStepsQ3: [ 35.1273, 40.6663, 42.6812, 43.2969, 44.2005 ], yieldStepsQ4: [ 38.7841, 46.2699, 48.5351, 49.6552, 48.4862 ], yieldStepsMinimum: [ 15.1588, 24.6433, 27.23, 28.4384, 29.8716 ], yieldStepsMaximum: [ 42.6212, 46.4911, 49.0374, 50.0583, 50.3118 ] }, { name: "Silomais", color: "#76b7b2", avgYield: 450, maxYield: 600, price: 4.2, costs: 612, nPrice: 0.9, nMax: 200, nSteps: [ 0, 60, 100, 150, 200 ], yieldSteps: [ 393.4, 436.15, 442.01, 447.66, 450 ], yieldStepsMedian: [ 384.7882, 428.5884, 423.6462, 441.711, 438.9793 ], yieldStepsMittelwert: [ 393.4006, 436.1526, 442.01, 447.6559, 450 ], yieldStepsQ1: [ 320.3375, 388.4808, 415.9247, 416.3037, 409.9504 ], yieldStepsQ2: [ 371.1559, 424.9036, 421.4113, 419.1603, 423.6866 ], yieldStepsQ3: [ 422.1946, 448.4883, 461.2014, 470.0728, 475.7918 ], yieldStepsQ4: [ 460.4331, 494.0061, 500.686, 496.6161, 508.5058 ], yieldStepsMinimum: [ 308.0917, 386.3514, 409.7484, 412.4558, 409.0979 ], yieldStepsMaximum: [ 474.7674, 504.9498, 512.9765, 510.193, 512.0605 ] }, { name: "Winterrogen", color: "#edc949", avgYield: 70, maxYield: 14, price: 14, costs: 495, nPrice: 0.9, nMax: 170, nSteps: [ 0, 80, 110, 140, 170 ], yieldSteps: [ 52.31, 63.95, 67.21, 68.55, 70 ], yieldStepsMedian: [ 53.1141, 65.9718, 67.4702, 70.9456, 68.9017 ], yieldStepsMittelwert: [ 52.3101, 63.9463, 67.2073, 68.5474, 70 ], yieldStepsQ1: [ 32.6541, 44.1918, 48.9135, 51.1503, 53.4477 ], yieldStepsQ2: [ 48.6034, 57.4128, 63.7743, 60.9838, 63.5788 ], yieldStepsQ3: [ 61.6967, 72.6224, 76.4508, 75.7202, 77.9059 ], yieldStepsQ4: [ 68.131, 77.1733, 81.6489, 83.5976, 84.3769 ], yieldStepsMinimum: [ 23.0197, 42.4261, 47.7284, 48.8736, 49.1865 ], yieldStepsMaximum: [ 68.7382, 77.914, 83.3694, 87.7775, 88.5493 ] }, { name: "Zuckerrübe", color: "#B9C497", avgYield: 740, maxYield: 600, price: 3.8, costs: 1078, nPrice: 0.9, nMax: 170, nSteps: [ 0, 50, 90, 130, 170 ], yieldSteps: [ 612.13, 682.29, 719.73, 733.19, 740 ], yieldStepsMedian: [ 599.4923, 702.9366, 725.5138, 741.6222, 755.8281 ], yieldStepsMittelwert: [ 612.1316, 682.2883, 719.7329, 733.1911, 740 ], yieldStepsQ1: [ 390.712, 441.7845, 468.7555, 512.0707, 502.7415 ], yieldStepsQ2: [ 469.8082, 600.7685, 634.3806, 650.5525, 671.7979 ], yieldStepsQ3: [ 729.3189, 759.2527, 796.3528, 808.5927, 814.8712 ], yieldStepsQ4: [ 854.6857, 914.5722, 922.9351, 921.9894, 941.8624 ], yieldStepsMinimum: [ 338.9113, 415.2679, 450.6979, 474.5623, 482.9994 ], yieldStepsMaximum: [ 988.3223, 976.6532, 1022.3149, 1038.2965, 1027.6421 ] } ] 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2f:{"title":"Optimierung der N-Düngung","cells":[{"id":0,"value":"# Optimierung der N-Düngung","pinned":false,"hidden":false,"mode":"md"},{"id":1064,"value":"In der Grafik sind Deckungsbeiträge auf Basis von *ortswechselnden* Versuchsergebnissen der Landwirtschaftskammer NRW abgebildet. Erzeugerpreise und Kosten lassen sich über die Regler auf der rechten Seite anpassen, wodurch ein Deckungsbeitrag je Düngermenge berechnen lässt. \nDie optimale N-Düngermenge lässt sich dann von der Grafik ablesen. \n\n**WICHTIG**: Die Düngebedarfs Ermittlung nach DüV ist hier **nicht** abgebildet, gilt aber nach wie vor als einzuhaltende Obergrenze.","pinned":false,"hidden":false,"mode":"md"},{"id":855,"value":"viewof cropTabs = createCropTabComponent(cropData)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1053,"value":"Der Verlauf der Kurve kann je nach Standort unterschiedlich steil sein, die Variabilität der verwendeten Versuche wird durch die schattierten Bereiche in der Grafik dargestellt: Von dunkel nach hell umspannen diese 50, 90 und 100 % der Versuchsdaten. Generell ist bei stark nachliefernden Standorten ein flacherer Kurvenverlauf zu erwarten, bei schwach nachliefernden Standorten kann eher die steilere Schattierungsgrenze zur Orientierung dienen.","pinned":false,"hidden":false,"mode":"md"},{"id":1202,"value":"\n\nBei Fragen wenden Sie sich gerne an: duengung\n that \n @\n that \n LWK.\n NRW.DE \n","pinned":false,"hidden":false,"mode":"html"},{"id":1074,"value":"**HINWEIS**: Diese Webanwendung ist lediglich ein Prototyp für didaktische Zwecke. Sie wird ohne Gewähr und ohne Haftungsübernahme bereitgestellt. Die Betreiber behalten sich vor, den Dienst jederzeit ganz oder teilweise einzustellen. \n**Der Fachbereich 13 bietet keinerlei Support!**","pinned":false,"hidden":false,"mode":"md"},{"id":932,"value":"### Daten & Funktionen","pinned":false,"hidden":false,"mode":"md"},{"id":275,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1198,"value":"cropData = FileAttachment(\"cropData_observable@11.JSON\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":113,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":869,"value":"table_data = {\n const table_data = createTableData(cropData);\n const sm = table_data.filter((d) => d.Kultur === \"Silomais\");\n sm.forEach((s) => {\n s[\"80% N-DüV\"] = 0;\n });\n\n return table_data;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1163,"value":"function createTableData(data) {\n const methodMap = {\n Median: \"yieldStepsMedian\",\n Mittelwert: \"yieldStepsMittelwert\",\n Q1: \"yieldStepsQ1\",\n Q2: \"yieldStepsQ2\",\n Q3: \"yieldStepsQ3\",\n Q4: \"yieldStepsQ4\",\n Minimum: \"yieldStepsMinimum\",\n Maximum: \"yieldStepsMaximum\"\n };\n return data.flatMap(crop => {\n \n // Dynamically build labels like \"0% N-DüV\"\n const nduevLabels = crop.nSteps.map(step => `${step}% N-DüV`);\n\n return Object.entries(methodMap).map(([methode, key]) => {\n const arr = crop[key];\n \n // Build object dynamically\n const result = {\n Kultur: crop.name,\n Methode: methode\n };\n \n nduevLabels.forEach((label, index) => {\n result[label] = arr[index];\n });\n return result;\n });\n });\n}\n\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":10,"value":"height = 570","pinned":false,"hidden":false,"mode":"ojs"},{"id":29,"value":"Chart = {\n const Chart = await require(\"chart.js\");\n const dragdata = await require(\"chartjs-plugin-dragdata@2.2.4\");\n\n Chart.register(dragdata);\n return Chart;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"Vue = import(\"https://unpkg.com/vue@3/dist/vue.esm-browser.js\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}