Volume 2, Issue 4 (In Progress)


In Progress
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Table of Contents

Open Access | Research Article | 10 November 2026
Reliability-Aware Active Crowdsourcing and Ontology-Constrained Multi-Evidence Clustering for Agricultural Multimedia Knowledge-Base Construction
Digital Intelligence in Agriculture | Volume 2, Issue 4: 214-229, 2026 | DOI: 10.62762/DIA.2026.512829
Abstract
Constructing agricultural multimedia knowledge bases is complicated by heterogeneous evidence, noisy crowdsourced annotations, variations in sample difficulty, and inadequate integration of multisource information. Using tomato disease and pest data, this study proposes a unified framework comprising Multi-evidence Reliability-Aware Active Crowdsourcing (MRAC) and Ontology-Constrained Multi-Evidence Clustering and Refinement (OMCR). MRAC jointly models annotator reliability, sample difficulty, content-evidence quality, and evidence availability. It selects sample-annotator pairs according to the expected information gain per unit cost and produces calibrated soft-label posteriors. OMCR integ... More >

Graphical Abstract
Reliability-Aware Active Crowdsourcing and Ontology-Constrained Multi-Evidence Clustering for Agricultural Multimedia Knowledge-Base Construction
Open Access | Research Article | 09 November 2026
Development of an Intelligent Fertigation Machine and Its Application Test in Soilless Cultivation of Mountain Blueberry
Digital Intelligence in Agriculture | Volume 2, Issue 4: 203-213, 2026 | DOI: 10.62762/DIA.2026.142287
Abstract
Conventional manual fertigation practices are generally limited by low control precision, considerable water and fertilizer waste, and poor adaptability to varied horticultural cultivation conditions. These limitations create particularly prominent challenges for high-value cash crops that are highly sensitive to root-zone substrate electrical conductivity (EC) and pH dynamics. To address these gaps, this study developed a digitally intelligent integrated fertigation system that integrates multi-sensor autonomous sensing, precise nutrient ratio regulation, and full-cycle operational monitoring modules. Systematic validation of both equipment performance and field production benefits was carr... More >

Graphical Abstract
Development of an Intelligent Fertigation Machine and Its Application Test in Soilless Cultivation of Mountain Blueberry
Open Access | Research Article | 08 November 2026
MaizeEviReason for Auditable Evidence Applicability and Conservative Release in Maize Disease Decision Support
Digital Intelligence in Agriculture | Volume 2, Issue 4: 191-202, 2026 | DOI: 10.62762/DIA.2026.954088
Abstract
Agricultural evidence can be topically relevant yet conflict with the conditions of a query, or lack the information needed to support an action. We present MaizeEviReason, an auditable interface that keeps source conditions, distinguishes applicable, inapplicable and undetermined states, and separates applicability assessment from deterministic release checks. The core evaluation measures how much information is lost when conditions are projected onto fixed fields and what coverage is given up when supplied contracts are enforced. Matched learning experiments evaluate applicability prediction, and a public-pipeline diagnostic examines whether the interface is activated. On 49 constructed as... More >

Graphical Abstract
MaizeEviReason for Auditable Evidence Applicability and Conservative Release in Maize Disease Decision Support