Dryland agriculture faces multiple challenges, particularly extreme environmental conditions and institutional constraints, which increase the vulnerability of farming households. Despite the availability of agricultural land, sustainable solutions are required to improve land productivity and farmer welfare. This study aims to analyze the effectiveness of compound cropping innovation in enhancing Farmers’ Terms of Trade (FTT) in calcareous drylands. A mixed-methods approach was employed, integrating qualitative and quantitative techniques through surveys, field observations, and participatory farmer empowerment using a demonstration plot. The study introduced a compound polyculture system combining maize (Zea mays) and jack bean (Canavalia ensiformis) as a low-input agroforestry innovation. The results indicate that major constraints in the Kendeng Mountains include pest attacks (particularly rats), drought-induced soil degradation, limited capital, and restricted access to agricultural inputs and markets. The introduction of the maize–jack bean system improved land productivity and increased FTT from 69.24 to 74.13. These findings demonstrate that jack bean-based compound cropping is agronomically suitable and economically beneficial in dryland conditions. The model also contributes to sustainable agriculture by improving soil fertility, reducing production risk, and enhancing farmer resilience. Therefore, this innovation has strong potential for wider adoption in the Kendeng region and similar dryland ecosystems.

A field experiment was conducted during the spring of 2024 to evaluate the effects of irrigation water salinity and organic fertilizer levels on the growth and yield of lettuce (Lactuca sativa L. ‘Parris Island Cos’). The experiment was arranged as a factorial within a split-plot design based on a randomized complete block design (RCBD) with three replications. Two irrigation water salinity levels were assigned to the main plots, namely fresh water (500 ppm) and saline water (4,500 ppm), while four levels of organic fertilizer (sheep manure), 0%, 1%, 2%, and 3%, were assigned to the subplots. The results showed that saline water irrigation generally produced higher numerical values for most growth and yield traits than fresh water under the conditions of this study. Among the tested fertilizer levels, the 1% organic fertilizer treatment gave the most favorable overall performance, particularly when combined with saline water. Under this treatment, plant height reached 19.1 cm, stem diameter 21.7 mm, leaf area 1.59 m², number of leaves per plant 75.8, plant weight 664.7 g, and total yield 53.2 t ha⁻¹. In conclusion, the findings suggest that a moderate rate of organic fertilizer may help maintain lettuce growth and productivity under saline irrigation conditions. These results also indicate that lettuce can be cultivated using saline water resources when supplemented with an appropriate level of organic fertilizer.

Adan rice farming is a traditional agricultural system uniquely practised in the border region of North Kalimantan, Indonesia. Cultivated organically using buffalo manure and crop residues, Adan rice contributes to local food sovereignty and shows cross-border market potential in Malaysia and Brunei Darussalam. However, its productivity remains low, and its sustainability status has not yet been clearly established. This study aimed to determine the land characteristics of Adan rice paddies, assess the sustainability status of Adan rice farming, and identify sensitive attributes influencing its sustainability. Data collection involved laboratory analysis of soil samples and a sustainability assessment using the Multidimensional Scaling (MDS) approach with Rapid Appraisal of the Status of Farming (Rap-FARM) software, supported by leverage (sensitivity) analysis, Monte Carlo simulation, stress-value testing, and the coefficient of determination (R²). The respondents consisted of 73 farmers in Krayan Sub-district. The results indicated that Adan rice paddies were dominated by clay loam, sandy clay loam, and sandy loam, with soil pH ranging from acidic to slightly acidic. Fertility indicators showed moderate to high organic carbon content, low to moderate nitrogen levels, low to moderate phosphorus levels, moderate potassium levels, and moderate to high cation exchange capacity (CEC). The novelty of this study lies in linking detailed land characteristics with a multidimensional sustainability framework for a rice cultivation system located in a strategically important border region. Unlike previous studies that focused primarily on high-yield commercial rice, this research highlights how local wisdom preserved in traditional rice cultivation can contribute to sustainable agricultural systems and food security in border areas.

The rapid growth of organic agriculture has created both opportunities and challenges for young agripreneurs, who should navigate certification standards (e.g., Thai Organic and the European Union Organic), compliance requirements, and market-specific documentation for domestic and international trade. This study aims to design and implement an ontology-driven decision support system (DSS) that leverages Semantic Web Rule Language (SWRL) to provide transparent and context-specific recommendations for organic farming. Having adopted a design-and-development approach, the research collected data from 50 agripreneurs and integrated these insights into an ontology framework enriched with rule-based reasoning. Five structured sets of recommendation rules were developed to link organic products, target markets, certification standards, certifying agencies, certification services, and required supporting documents while their performance was evaluated using standard information retrieval metrics. Evaluation based on case-based rule validation indicated that the system returned no false positives across the tested scenarios (100% precision), with an average recall of 93.03% and an overall F-measure of 96.39%, thus demonstrating strong logical correctness and practical applicability within the defined evaluation scope. The study concluded that embedding SWRL-based “IF–THEN” recommendation rules within ontological structures could effectively bridge fragmented regulatory and market knowledge and actionable decision making, in order to offer agripreneurs a scalable and explainable tool to manage certification and market access. The significance of this work lies in its dual contributions: theoretically, it demonstrates how semantic technologies could advance knowledge-to-decision processes in agriculture; practically, it provides structured guidance to support certification compliance and market participation in organic farming.

The organic rice supply chain in Indonesia, particularly in Banten Province, is characterized by high complexity and the involvement of multiple actors, which creates challenges related to transparency, traceability, and product authenticity. These issues reduce consumer trust and complicate regulatory supervision in organic farming systems. This study aims to design and evaluate a blockchain-based traceability model to enhance transparency, ensure product authenticity, and support food safety compliance in the organic rice supply chain. This research employs the Design Science Research Methodology (DSRM), encompassing problem identification, objective definition, artifact design and development, demonstration, and evaluation. Data were collected through interviews, field observations, and Focus Group Discussions (FGDs) involving organic rice supply chain actors, government regulators, and experts. The proposed model was empirically evaluated using Partial Least Squares–Structural Equation Modeling (PLS-SEM) based on responses from 220 participants. The resulting Organic Rice-Supply Chain Traceability (Organic Rice-SCT) model integrates farmers, farmer cooperatives, business actors, retailers, consumers, and government agencies within a blockchain-based system supported by quick response (QR) code technology. The findings indicate that operational excellence, cultural suitability, environmental conditions, quality assurance, and organizational resources significantly influence blockchain adoption. Conversely, data management, supply chain integration, technology maturity, and knowledge management show no significant effect. The model demonstrates its capability to improve supply chain visibility, reduce information asymmetry, strengthen regulatory oversight, and support compliance with Fresh Plant-Based Food (Pangan Segar Asal Tumbuhan, PSAT) certification. In conclusion, this study provides a validated blockchain-based traceability model that enhances transparency and trust in organic rice supply chains. Practically, the model supports stakeholders and regulators in ensuring food safety and product authenticity, while theoretically contributing to the literature on blockchain adoption in sustainable agricultural systems.