Crop Rotation Planning Method for Yield Optimization
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Solution Overview
Problem
Current crop rotation planning methods fail to maximize yield while adhering to agronomic principles and sustainability regulations, as they do not effectively account for the dynamic yield impact of previous crops and often result in soil fertility depletion and increased environmental damage.
Innovation Solution
A method that determines a set of permissible crop sequences for each plot over a planning horizon, considering the yield impact of previous crops, with the total yield calculated as the sum of seasonal yields based on the current and preceding crops, allowing for dynamic yield determination and compliance with agronomic and sustainability constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If monoculture schemes are used to simplify land management, then operational simplicity is improved, but soil fertility is depleted and yield decreases
Solution Approach 1:
The patent divides the farmland into multiple plots and implements different crop sequences on each plot. Instead of uniform monoculture, each plot is segmented with specific rotation patterns (e.g., Plot 1: Corn-Wheat-Legume, Plot 2: Soybean-Oats-Rye). This segmentation allows simplified management of individual plots while achieving overall sustainability and high yield across the entire farm.
2Productivity
If crop rotation is implemented to maintain soil fertility, then productivity is improved, but planning complexity increases
Solution Approach 1:
The patent employs dynamic optimization to determine crop sequences based on current soil conditions, weather forecasts, and market prices. The system adapts rotation plans in real-time rather than following fixed static patterns. For example, if soil moisture is high in a particular plot, the system may dynamically adjust to plant crops that benefit from moisture, thereby maintaining high yield while simplifying the planning process through automated adaptive decision-making.
3Productivity
If previous crops are considered in yield calculation to maximize productivity, then crop yield is improved, but computational complexity increases
Solution Approach 1:
The patent pre-calculates and stores yield coefficients for different crop-combination sequences before the planting season. Historical data on how previous crops affect current yields is analyzed in advance to create lookup tables of yield modifiers. During the planning phase, the system simply retrieves these pre-computed values rather than performing complex simulations, thereby achieving accurate yield predictions while keeping computational requirements low.
4Object-affected harmful factors
If sustainability regulations are complied with to reduce environmental impact, then harmful factors are reduced, but operational flexibility decreases
Solution Approach 1:
The system continuously monitors soil health indicators, crop performance, and environmental metrics, then uses this feedback to adjust crop sequences and management practices. For example, if soil nitrogen levels are low, the system automatically increases legume planting in subsequent seasons to naturally replenish nitrogen. This closed-loop feedback mechanism ensures compliance with sustainability regulations while maintaining operational flexibility, as the system adapts to actual conditions rather than following rigid predetermined rules.
Data Source
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AI summary
A method for planning crop rotations in at least one plot (hi, i=1...n) of land within a predetermined planning horizon or time (T), to implement a cropping method, includes the steps of: for said or each plot (h), determination of a set (C) of acceptable crops (c) based on the soil nature of the plot(s) (h), an availability of irrigation, exposure, and geographic coordinates; for said or each plot (h), definition of a succession of planting periods (t) until the planning horizon (T) is completed; specification of a plurality of desired crops (ci ) among the acceptable crops; choice of a σ sequence of k crops, where k≥2, among the desired crops (ci , i=1...k); definition of a plurality of eligible sequences σ of the desired crops ci to be assigned to plot h, according to respective predetermined time orders, subject to agronomic constraints including on each plot, uniqueness of the crop c to be assigned in each planting period t, and minimum and maximum area assigned to each crop c in each planting period t; determination, for each of the eligible sequences σ, and for all p sowing periods t of planning time T, of a total yield πh for said or each plot h, obtained as the sum of seasonal yields Yh in sowing periods t, in which each of the seasonal yields in a sowing period t is calculated based on a maximum number of crops k comprising the assigned crop in sowing period t, and the k-1 assigned crops, according to each of the sequences, in a corresponding k-1 number of consecutively preceding earlier sowing periods preceding said sowing period (Figure 1).