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Optimal trap cropping investments to maximize agricultural yield Matthew H Holden School of Mathematics and Physics, The University of Queensland, St Lucia, 4072, Australia Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, 4072, Australia Abstract Trap cropping is a pest manageme... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
Intermediate attractiveness warrants the greatest investment in trap cropping. Our framework offers a transparent and tractable approach for exploring trade-offs in pest management and can be extended to incorporate more complex pest behaviors, crop spatial configurations, and economic considerations. Keywords: ecologi... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
and pollinators , and environmental contamination . These concerns have motivated a growing interest in ecologically based pest management approaches that reduce reliance on chemical controls while maintaining productivity . Among these, trap cropping has emerged as a promising, environmentally friendly tactic for mani... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
of trap cropping and related ecological interventions such as intercropping and companion planting. Early models focused on insect pest dispersal and behavioral responses to attractants or traps embedded within cropping systems . Since then, a range of modeling approaches have been used to explore how pest movement, cr... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
demonstrate the potential of spatially targeted interventions, they do not offer general analytic solutions for the optimal proportion of land to devote to trap cropping. Our work aims to fill this gap by proposing a stylized but tractable framework that captures key trade-offs and yields explicit recommendations for g... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
behavior and damage functions . To illustrate the utility of the framework, we analyze a simplified scenario in which pests move freely across the field and select plants purely based on relative attractiveness. This assumption corresponds to highly mobile pests, such as adult moths that lay their eggs in batches over ... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
extended to incorporate more complex dynamics such as pest reproduction, spatial heterogeneity, and economic costs. 2 2 Framework In this work, we consider a scenario with N pests in a field damaging the main crop harvested by the grower. To reduce this damage, the grower may plant a trap crop to divert pests, potentia... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
all cash and trap plants are otherwise equal, the total yield across the whole field is given by: Y (nc) = y (ρ(nc)) · nc (1) This equation says that total yield is just the average yield of a cash plant, given the average pest density on cash plants, multiplied by the number of cash plants. As the grower increases the... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
(1) and (2) hold (see section 7). Equation (3) implies that at the optimal number of cash plants, the yield per plant equals the marginal loss in yield caused by adding another cash plant, summed over all plants. Roughly, if you added a cash plant, the yield of that cash plant should equal the reduced yield summed over... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
common properties. First, there is some assumed maximum yield per plant in the absence 3 0 2 4 6 8 10 0 20 40 60 80 100 Pest density per plant Yield per plant Linear Reciprocal Exponential Figure 1: Yield curves, y(ρ), as a function of pest density per plant ρ, with N = 1,000, β = 0.8, k = 100, and n = 10. of pests, ca... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
with pest density from a maximum yield of k to (1 −β)k when pest density is N/n, we obtain the yield function, y(ρ) = k 1 −βn N ρ . (4) Reciprocal yield Assuming yield declines reciprocally with pest density, i.e., y(ρ) = α/(1 + γρ), and parameterizing such that y(0) = k and y(N/n) = (1 −β)k, we obtain: y(ρ) = k(1 ... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
optimal allocation of land to cash and trap plants. Consider the case where pests leave plants at each time step with probability l. Pests that leave a cash plant settle on another cash plant with probability s, while those leaving a trap plant settle on a cash plant with probability σ. Under these assumptions, the pro... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
related to pest density. So far, our model is simple. We have assumed very little about the spatial structure of the field. The only critical assumption is that all trap plants are treated as identical, and all cash plants are treated identically as well. This assumption implies that pests leaving any trap plant have t... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
to x∗= s, providing a simple formula relating the proportion of pests on the cash crop directly to the number of cash crops, nC. Substituting our expression for x∗for x(nC) then allows us to proceed using the framework to determine the optimal number of cash plants (and hence trap plants) to allocate to the landscape. ... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
number of trap plants, n −n∗ C, makes up a high proportion of the landscape. For example, if a trap plant were four times as attractive as a cash plant, the grower would have to devote a third of the landscape to trap plants to maximize yield. Even if the trap crop is 100 times more attractive than the cash crop, the g... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
n∗ C = " a(1 −β) + β − p β2 + βa(1 −β) (1 −β)(a −1) # n, (12) if the quantity is in [0, n], or n otherwise. For exponential yield, the optimal number of cash plants is n∗ C = " 2a −ln(1 −β) − p ln(1 −β)(ln(1 −β) −4a) 2(a −1) # n. (13) These expressions are more complex than for the linear yield relationship. However, n... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
in agricultural landscapes . We will use these two parameter values as an illustrative baseline, but will also explore the whole parameter space. If a = 49 and β = 0.4, we find that roughly 91.5 – 92.9 percent of a grower’s greenhouse or field should be allocated to cash plants to maximise yield (Figure 2). The nonline... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
relationship, assuming the trap plant is 49 times more attractive than the cash plant (a = 49). Note that when there are no trap plants, the grower loses 40% of their yield (right endpoint), with steep gains from adding only a few trap plants (moving left). The optimal proportion of the field to devote to trap plants i... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
an optimal cash plant proportion of 91.5–92.9 percent. At approximately 95 percent of the landscape devoted to cash plants, each additional cash plant severely reduces yield compared to an equivalent investment in trap plants due to pest damage (see the rapid drop off in the right of Figure 2). However, a = 49 represen... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
plant that is only twice as attractive as a cash plant, trap cropping is ineffective, and the grower should plant only cash plants, accepting the yield loss caused by pests. For more attractive trap plants, 5 and 25 times more attractive, approximately 7–10% of the field should be allocated to trap plants. As attractiv... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
can increase the optimal number of trap crops or decrease it compared to the linear pest-density model, depending on the attractiveness parameter (the order of the colored circles, representing optimal yield, changes when comparing Figure 3b and to Figure 3c). These reversals reflect that, at intermediate attractivenes... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
12.5, respectively. After achieving the minimum, for larger attractiveness values, the optimal proportion of the landscape devoted to cash plants gradually rises again. This is because, as trap crops become highly effective, less land allocation is required to achieve adequate pest control. For even nearly perfect attr... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
their efficacy is high enough that a smaller proportion of the landscape can achieve the necessary reduction in pest densities to maximize yield. Optimal trap cropping is even more sensitive to the maximum yield at risk due to pests, β, than the attraction parameter. We plotted the optimal proportion of cash plants in ... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
to achieve optimal yield. The exponential is an intermediate case between this severely nonlinear yield–pest relationship and the more gradual, linear, pest–yield relationship. However, even in the linear case, if 100 percent of the yield is at risk, still 88 percent of the field needs to be devoted to cash plants to m... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
majority of the parameter space corresponds to the case when 8095 percent of the landscape should be dedicated to the cash crop to maximize agricultural yield. Low optimal cash plant proportions of less than five percent only occur when less than 30 percent of the grower’s yield is at risk (left second darkest region).... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
attraction warrants the greatest trap cropping investment, compared to highly attractive and unattractive trap crops, is general across parameterizations. That is for all yield-pest dentistry relationships (all panels) and parameter values for yields at risk (horizontal axis), as long as the trap crop is attractive eno... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
(3), that maximizes total yield, Y (nC), if the following three properties hold: 1. The function x is positive, continuously differentiable, and strictly increasing on (0, n). 2. The function E, defined by E(nC) = nC x(nC) dx dnC −1, (14) is positive and strictly increasing with respect to nC on nC ∈(0, n). 12 3. The f... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
For example, if the elasticity in equation (15) is two, then, approximately, a one percent increase in cash plants will cause a two percent increase in the proportion of pests on a cash plant. Therefore, condition 2 says that the elasticity of pest density on a single plant with respect to the number of cash plants pre... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
additional individual pest added to a plant decreases yield more than the one before, or each pest decreases yield less than the one before, but it never switches back and forth depending on how many pests are on the plant. Theorem 1 means that for many mathematical models of pest movement and yield-pest relationships,... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
to the cash crop (a). When trap crops are only marginally more attractive than the cash crop (e.g., a = 2), trap cropping fails to improve yield, even under extreme pest pressure. In contrast, when trap crops are highly attractive (e.g., a = 49), yield gains can be substantial even with relatively small land allocation... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
is severe. This finding is particularly important for organic and low-input systems, where pesticides are avoided and trap cropping is one of few viable pest management options . Second, the analysis emphasizes that blanket recommendations about trap crop allocation are unlikely to be effective. Instead, effective impl... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
attractiveness, without considering pest arrestment, retention, or mortality on trap plants. In systems where trap plants kill or immobilize pests (e.g., through glandular trichomes or nectar-feeding traps), trap cropping will likely be more effective, and our model’s recommendations may not hold. Nonetheless, our fram... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
variable pest dispersal patterns or plant preferences. Further, while our framework was designed for trap cropping, other systems where the grower sacrifices space via companion planting to increase yield in the rest of the field may also work for our framework. For example, a modified version of the model could be use... | {
"Authors": "Matthew H Holden",
"Published": "2025-08-07",
"Summary": "Trap cropping is a pest management strategy where a grower plants an\nattractive \"trap crop\" alongside the primary crop to divert pests away from it.\nWe propose a simple framework for optimizing the proportion of a grower's field\nor green... |
GPT-4 AS EVALUATOR: EVALUATING LARGE LANGUAGE MODELS ON PEST MANAGEMENT IN AGRICULTURE Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang* ABSTRACT In the rapidly evolving field of artificial intelligence (AI), the application of large language models (LLMs) in agriculture, particularly in pest m... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
the use of instruction-based prompting containing domain-specific knowledge proved the feasibility of LLMs as an effective tool in agriculture, with an accuracy rate of 72%, demonstrating LLMs’ effectiveness in providing pest management suggestions. Index Terms— Large Language Model, Prompt Engineering, Large Language ... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
pre-trained language models (PLMs) like BERT (Bidirectional Encoder Representations from Transformers) and GPT have significantly altered the NLP landscape, delivering state-of-the-art results across various tasks [7]. Traditional NLP methods require handcrafted features and task-specific training, whereas PLMs use a g... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
Followed by small fine-tuning, LLMs are adapted to task-specific datasets to particular applications of interest [9]. Consequently, identifying appropriate evaluation metrics for LLMs across diverse domains has emerged as a novel and significant research theme. Due to the efficiency in understanding and generating huma... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
Our research uncovers subtle differences between GPT-3.5 and GPT-4 in decision-making on pest management, emphasizing the importance of model selection in agricultural contexts. 2. RELATED WORK 2.1. Application of LLMs “FinBERT” is a LM tailored in financial domain, a variant of the BERT model where lies in the special... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
achieve scores at or near the passing threshold for all three components of the United States Medical Licensing Exam without specific training or reinforcement, underscoring the potential of LLMs to support medical education and possibly influence clinical decision-making processes. Similarly, Thirunavukarasu et al. [1... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
agricultural environments [16]. Besides, Silva et al. [17] evaluate the capability of LLMs, including GPT-4, GPT-3.5, and Llama2, in responding to agriculturally-related queries. The queries were sourced from agricultural examinations and datasets from the United States, Brazil, and India. The study assessed the accura... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
information [18]. 2.2. Prompt & Prompt Engineering Prompts are a mechanism for interaction with large language models (LLMs) to accomplish specific tasks [19]. Prompts act as essentially instructions directed towards LLMs, comprise the input provided by users and guide the model to generate answers for the response [20... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
in the “Prompt Engineering Guide [28]”, constructing an effective prompt can involve integrating four elements or a combination: Instruction, Context, Input Data and Output Indicator. Instruction refers to a specific task or directive to guide the model to perform a designated operation. Context encompasses providing s... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
and refinement continues until the desired outcome is achieved. 3. EXPERIMENT DESIGN 3.1. Experiment Models This section provides an overview of the two LLMs evaluated in the experiment: Section 3.1.1 covers the GPT series from OpenAI, specifically GPT-3.5 and GPT-4, while Section 3.1.2 describes the FLAN-T5 model deve... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
API. However, it remains applicable to non-chat tasks. The GPT-4 model, as a large multi-modal model, exhibits a broader comprehension of general knowledge and reasoning capabilities, enabling it to solve complex problems with greater accuracy compared to GPT-3.5 and its predecessors [35]. 3.1.2. FLAN-T5 The T5 model s... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
model, FLAN models require downloading the checkpoints locally to generate the response. Given the considerations for computational speed and memory constraints, the FLAN-T5XL variant is selected as a more practical option for experimental use containing 3 billion parameters. The pre-trained model 3 “google/flan-t5-xl”... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
four datasets extracted from the AHDB’s Encyclopaedia of Pests and Natural Enemies in Field Crops [38]. These datasets include two in structured data ‘JSON’ format: ‘pest to affected crop.json’ and ‘pest to threshold.json’ and two in ‘XLSX’ format ‘thresholds database.xlsx’ and ‘pest to management.xlsx’. • File ‘pest t... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
sticky trap’, and ‘per gram of soil’. • File ‘pest to management.xlsx’ has two columns, the first listing the names of pests and the second detailing management suggestions for Non-chemical control solutions that meet the criteria for affected plants and thresholds achieved. Notably, the Expert System is designed to ou... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
pests of the same species, 25 types of pests, along with their affected crops, thresholds and Non-chemical control solutions, have been extracted. The ‘generate densities’ function provides a mechanism for determining ‘true’ and ‘false’ density values. By iterating through a list of density-related columns in file ‘thr... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
symbol if the original value was expressed as a percentage. 4 Data Extraction and Indexing thresholds_database.xlsx Generate True (exceeding threshold) and False (below threshold) density values by manipulating the original density values with random integers. Density Values Generation thresholds_database.xlsx pest_to_... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
Crops + True Densities False Crops + False Densities Positive Sample Pest Name: … Crop: … Density: … Temperature: … Location: … Label: 1 Negative Sample Pest: … Crop: … Density: … Temperature: … Location: … Label: 0 Generate True (crops affected by the pest) and False (crops unaffected by the pest) crops by classifying... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
are augmented with randomly generated temperature and latitude location parameters to diversify the dataset further. Considering computational resources and experimental costs, also ensuring an even distribution of positive and negative samples, one positive sample (labelled as ‘1’) and one negative sample (labelled as... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
LLMs without needing prior examples or contextual information. Zero-shot prompting necessitates the ability of the model to comprehend and respond to tasks or queries not directly encountered before [39]. The model relies on the extensive knowledge and understanding acquired during the training phase for zero-shot prom... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
by the demonstrations are crucial for performance, irrespective of the accuracy of individual labels. Additionally, the format of the demonstrations, including random labels, significantly influences effectiveness, which is better than not using any labels. The core of the few-shot learning approach is encapsulated wit... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
2}, with a density of {Density 2}. The temperature was {Temperature 2}, and the location was at {Location 2}. Could you please provide some control and management suggestions? Answer: {Non-chemical control solutions for Pest 2} Question: I discovered {Pest 3} in my {Crop 3}, with a density of {Density 3}. The temperatu... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
comprehensive and sustainable pest management suggestions based on the given crop, pest type and density, and environmental conditions, including temperature and location. Context: Pest management in agriculture requires balancing control measures with environmental sustainability. Different crops and pests respond to ... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
to specific scenarios. The structured example 6 systematically introduces the input data, incorporating placeholders for designated variables. Precisely, the {Pest} variable corresponds to the pest identified in the inquiry, while the {Affected Crops} are derived from the ‘pest to affected crop.json’ file. Similarly, t... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
Response 3: {Response 3 from instruction-based prompting} Create a summary response that combines the best elements of question: I discovered {Pest} in my {Crop}, with a density of {Density}. The temperature was {Temperature}, and the location was at {Location}. Could you please provide some control and management sugg... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
action is required. The prompt followed with the ‘Evaluation Criteria’ to inform the GPT that this is a binary evaluation to assign ‘1’ or ‘0’. Through the Evaluation Steps, the GPT is guided with the CoT sequence, asked to decide whether the information presented within a response indicates that an action is required ... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
Assign a score based on the evaluation criteria: 0 means no action is needed, 1 means the suggestion requires action. 4. If the response suggests the action is optional, needs further observation or continuous monitoring, leaves room for doubt, lacks clearly direction, contains not be necessary or not immediate control... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
ranging from 1 to 10 for each of the six dimensions. 4. RESULTS Model & Prompting Coherence Consistency Fluency Relevance Comprehensibility Exhaustiveness FLAN zero-shot 2.52 2.52 3.30 2.36 2.76 2.96 FLAN few-shot 2.68 3.00 3.42 2.44 3.32 3.46 FLAN instruction-based 3.70 3.92 4.84 5.06 5.04 4.36 FLAN self-consistency 2... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
1 0.72 0.65 0.96 0.77 79.86 GPT-3.5 self-consistency 25 0 25 0 0.50 0.50 1.00 0.67 70.08 GPT-4 zero-shot 24 4 21 1 0.56 0.53 0.96 0.69 78.40 GPT-4 few-shot 21 7 18 4 0.56 0.54 0.84 0.66 74.68 GPT-4 instruction-based 24 9 16 1 0.66 0.60 0.96 0.74 79.88 GPT-4 self-consistency 25 0 25 0 0.50 0.50 1.00 0.67 74.94 Table 2: ... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
and Exhaustiveness are each allocated 10%, while Accuracy is assigned a higher weight of 40%. In the computation of the Final Score, the metrics of Coherence, Consistency, Fluency, Relevance, Comprehensibility, and Exhaustiveness are evaluated on a scale from 1 to 10. In contrast, Accuracy is averaged, falling in a ran... | {
"Authors": "Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang",
"Published": "2024-03-18",
"Summary": "In the rapidly evolving field of artificial intelligence (AI), the\napplication of large language models (LLMs) in agriculture, particularly in\npest management, remains nascent. We aim... |
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