The current study aims to develop a simple model for estimating greenhouse gas emissions originating from paddy fields, utilizing backpropagation neural networks. The model integrated three input parameters: soil moisture, soil temperature, and soil electrical conductivity (EC), while generating estimations for two output parameters: methane (CH4) and nitrous oxide (N2O) emissions. The model was put into practice across three different irrigation systems, i.e., continuous flooded (FL), wet (WT), and dry (DR) regimes. For model training and validation, the input parameters were measured by a single 5-TE sensor. Concurrently, CH4 and N2O emissions were determined utilizing a closed chamber, and gas samples were subjected to laboratory analysis. Findings unveiled that the developed model accurately estimated CH4 and N2O emissions, demonstrating commendable coefficient of determination (R2) values ranging from 0.60 to 0.97 for validation process. Notably, the WT irrigation system exhibited the highest precision, boasting R2 values of 0.97 for CH4 and 0.73 for N2O estimation, respectively. Conversely, the FL irrigation system has the lowest accuracy with R2 values of 0.66 and 0.60. Despite variances in accuracy across irrigation systems, the overall performance remained deemed acceptable, warranting the model's applicability for estimating greenhouse gas emissions under diverse irrigation scenarios.

Context While the individual benefits of technologies like alternate wetting and drying (AWD), site-specific nutrient management (SSNM), mechanical transplanting, laser-guided land leveling (LLL), and herbicide application are well-documented, limited information exists on their combined effects on rice productivity and profitability. Objectives This study hypothesized that integrating resource-use efficient technologies could offer compounded benefits in yields and reduced production costs. The study aimed to assess the cost-effectiveness and grain yields of bundled technologies for rice, evaluating whether bundling could enhance yields, reduce production costs, and improve gross margin under farmers' field conditions. Methods On-farm participatory field trials were conducted over two dry seasons in the Philippines. Technology combinations were grouped as treatments (T) to reflect increasing bundling levels: T1 (farmers' practice (FP) with continuous flooding or CF), T2 (CF with mechanical transplanting, SSNM, and pre-emergence herbicide or PH), T3 (T2 with LLL), T4 (FP with AWD), T5 (AWD, mechanical transplanting, SSNM, and PH), and T6 (T5 with LLL). Results Bundles involving LLL (T3) significantly increased the unit cost of production (P < 0.05) but did not result in proportional yield or gross margin increases. The outcome was attributed to exposure to less fertile soil after cut-and-fill operations and the high rental fee of LLL. However, the AWD in T6 with LLL mitigated these effects, resulting in no significant impact on yield. T5 balanced production costs and yield, offering a more economically viable approach than T3. The variability in yields and gross margins across treatments suggests that the expected benefits of higher yields and reduced costs from bundling technologies were inconsistent, with some treatments showing no advantages over farmers’ practices. Conclusion The bundles combining AWD, SSNM, mechanical transplanting, and pre-emergence herbicide offered a balanced approach to cost-efficiency and productivity. Bundles involving LLL have increased production costs without corresponding yield or gross margin gains. Implications of the study The results underscore the complexity of bundled agricultural technologies, particularly in the context of smallholder systems. Benefits vary significantly depending on the technology combination, environmental conditions, and management practices, emphasizing the need for site-specific approaches when introducing new technologies. The findings provide valuable insights for bundling rice farming technologies with similar agroecosystems like the study site to enhance resource use management.

Water management plays a crucial role in paddy rice cultivation. Inappropriate use of irrigation water can hinder optimal plant growth and lead to wastage. Therefore, it is essential to optimize the irrigation water delivery system. This optimization can be achieved after developing a model that identifies the relationship between the irrigation system and plant growth. This research aims to develop a plant growth model influenced by the irrigation system. An artificial neural network model with a backpropagation algorithm is employed to predict plant growth under different irrigation treatments. The model development is based on a lab-scale rice cultivation experiment conducted over two growing seasons in 2021 and 2022, comparing a flooded system (CFI) and a more water-efficient intermittent irrigation system (IIS). The first growing season was used for model training, while the second season was for model validation. The developed model incorporates three inputs: soil moisture, plant height, and the number of tillers from the previous week. The outputs are the plant height and the number of tillers for the following week. The results of the model training indicate that the neural network model accurately predicts plant height and the number of tillers, with R 2 values of 0.99 and 0.93, respectively. For validation, the R 2 values are slightly lower, at 0.97 and 0.65. These results suggest that the model can effectively predict plant height and the number of tillers.

Water saving in rice cultivation has assumed paramount importance, especially in the context of climate change. The introduction of sheet-pipe technology in Indonesia heralded as an innovative subsurface irrigation and drainage system, is poised to revolutionize how to manage this vital resource. Our study was designed with two primary objectives: first, to investigate how rice plants respond when water levels are deliberately reduced using the sheet-pipe technology; and second, to comprehensively analyze water productivity and water use efficiency in comparison to conventional flooded rice cultivation systems. We conducted two distinct experiments: one employing sheet-pipe subsurface irrigation (SSI) and the other utilizing conventional flooded irrigation (CFI). In the SSI setup, the water level was maintained at a depth of 5-10 cm below the soil surface 20 days after transplanting to harvesting. With this setting, the soil moisture was maintained at around 85-95 degrees of saturation. On the other hand, the CFI approach involved water flowing directly over the soil surface, with the water level consistently maintained at a mere 2-3 cm above it. Interestingly, while the SSI method did lead to a reduction in yield, it has significant benefits. Our results showed that a reduction in yield was observed for the SSI 15.5-18.6 % lower compared to the conventional method (CFI). However, the SSI is environmentally benefit compared to the conventional method by reducing 37.5-50.5 % in water irrigation, increasing water use efficiency (WUE) up to 70.8 %, and improving 3.2-10.4 % in water productivity. Our findings reveal that optimizing water conservation may have a disadvantageous effect on rice yield, indicating the importance of optimal water level. Future research to find the optimal water level that balances yield production and environment is required, especially to adapt to dry and warming climate change in the future.

The demand for biomass energy production in the Philippines has led to substantial rice husk ash (RHA) generation. We combined alternate wetting and drying (AWD) and varying RHA rates (10, 20, and 30 t ha–1) to evaluate the yield, water productivity (WP), and greenhouse gas (GHG) emissions in paddy rice for four cropping seasons (CS). We compared these treatments with continuous flooding (CF) and no RHA as controls. The RHA decreased N2O emissions by 8–22

AbstractTo ensure sustainability and resilience in the areas damaged by the Great East Japan Earthquake, it is important to educate the next generation, who can discover and create solutions for the problems and challenges that constantly arise in the agricultural field. To this end, we propose and practice a field and project-based learning (FPBL) program, which combines a “field-based approach” with the project-based learning (PBL: a program in which students work on a question or hypothesis to be solved as a project). The FPBL aims to develop human resources who can realize the process of extracting issues from the practical field, through thinking, discussion, and working in a group of diverse and multidisciplinary people, and who finally reapply the meaningful results to the field. In our approach, we aim to evaluate not only knowledge transfer but also multifaceted indicators (such as attachment to the target area and improvement of self-efficacy). This chapter introduces the education program conducted in Iitate village, Fukushima, and discusses the results of the qualitative and quantitative research on the feedbacks from the program participants.

Irrigation and fertilization technologies need to be adapted to climate change and provided as effectively and efficiently as possible. The current study proposed pocket fertigation, an innovative new idea in providing irrigation water and fertilization by using a porous material in the form of a ring/disc inserted surrounding the plant's roots as an irrigation emitter equipped with a "pocket" /bag for storing fertilizer. The objective was to evaluate the functional design of pocket fertigation in the specific micro-climate inside the screenhouse with a combination of emitter designs and irrigation rates. The technology was implemented on an experimental field at a lab-scale melon (Cucumis melo L.) cultivation from 23 August to 25 October 2021 in one planting season. The technology was tested at six treatments of a combination of three emitter designs and two irrigation rates. The emitter design consisted of an emitter with textile coating (PT), without coating (PW), and without emitter as a control (PC). Irrigation rates were supplied at one times the evaporation rate (E) and 1.2 times the evaporation rate (1.2E). The pocket fertigation was well implemented in a combination of emitter designs and irrigation rates (PT-E, PW-E, PT-1.2E, and PW-1.2E). The proposed technology increased the averages of fruit weight and water productivity by 6.20 and 7.88%, respectively, compared to the control (PC-E and PC-1.2E). Meanwhile, the optimum emitter design of pocket fertigation was without coating (PW). It increased by 13.36% of fruit weight and 14.71% of water productivity. Thus, pocket fertigation has good prospects in the future. For further planning, the proposed technology should be implemented at the field scale.

The potential use of drip irrigation to reduce water use without yield penalty in aerobic rice cultivation has not been fully explored in the tropics due to high investment costs. One major way to lowering this cost is by optimizing the lateral spacing to serve more rows of rice plants per dripline. This study evaluates the effects of lateral dripline spacing on the grain yield, water productivity, and the economic return in aerobic rice production. Field experiments were conducted for the period of two years (2020-2021) using three lateral dripline spacings (40-cm, 60-cm, and 80-cm) as treatments and surface flooding as the control. Grain yields, water use, water productivity, and economic benefits were evaluated. The drip-irrigated aerobic rice did not show significant differences with surface flooding except for a lower yield at 80-cm in 2021 dry season due to its low percent filled grains. Among treatments, the 60-cm lateral spacing consistently obtained the highest irrigation water productivity by up to 1.03 kg m(-3) and 42% irrigation water savings relative to surface flooding. Increasing the spacing of the lateral dripline decreased the material costs (80 < 60 < 40 cm) by 10-36%. The 60-cm spacing produced the highest average net income by 41-75% among drip treatments and had comparative economic returns compared with surface flooding. The net present value and the benefit-cost ratio indicate that it is economically viable to invest in drip irrigation using a 60-cm lateral spacing. Thus, this study suggests that when there is insufficient water to grow surface flooding aerobic rice, drip irrigation using 60-cm lateral spacing is the best option for reducing irrigation water use and increasing water productivity; while having comparative yield and economic return as surface flooding method of aerobic rice cultivation.

Evapotranspirative irrigation is a simple idea in a watering field based on the actual evapotranspiration rate, by operating an automatic floating valve in the inlet without electric power to manage water levels. The current study introduces a model of evapotranspirative irrigation and its application under different water levels. The objectives were (1) to evaluate the performances of evapotranspirative irrigation under various irrigation regimes, and to (2) to observe crop and water productivities of the system of rice intensification (SRI) as affected by different types of irrigation. The experiment was performed during one rice planting season, starting from July to November 2020, with three irrigation regimes, i.e., continuous flooded (CFI), moderate flooded (MFI) and water-saving irrigation (WSI). Good performance of the system was achieved; low root mean square error (RMSE) was indicated between observed water level and the set point in all irrigation regimes. Developing a better drainage system can improve the system. Among the regimes, the WSI regime was most effective in water use. It was able to increase water productivity by up to 14.5% while maintaining the crop yield. In addition, it has the highest water-use efficiency index. The index was 34% and 52% higher than those of the MFI and CFI regimes, respectively. Accordingly, the evapotranspirative irrigation was effective in controlling various water levels, and we recommend the system implemented at the field levels.

Since the nuclear disaster in Fukushima, Japanese soil scientists have tackled soil contamination problems due to radioactive cesium. For the radiation education based on the research results and outreach activities, we published a comic book and developed a digital application using iOS Xcode for Apple iPhone and tablet devices. This allows students to quickly understand why clay soil absorbed cesium and how to remove contaminated soil using educational mini-games. Through radiation education seminars and a conference, our application was evaluated and revised by school teachers.

Escalating intensification and homogenization occurring throughout the supply chain poses serious challenges to the global food supply. Several approaches have been developed to shift the food systems to a more resilient path; however, the high unit costs of shipping impede its development. This paper proposes a shared logistic service supported by E-commerce as a solution to this problem. It analyzes the shared logistic system developed by Vegibus Ins. in Japan which has unique features, such as fixed routes. It argues that the logistic service has the ability to connect different scales while supporting flexible transactions leading to the construction of a resilient agri-food system. At the same time, the paper points out the need for subsidies from the governments to facilitate this kind of shared logistic service at the initial stage as one limitation to this approach.

Alternate Wetting and Drying (AWD) is a well-known low-cost water-saving and climate change adaptation and mitigation technique for irrigated rice. However, its adoption rate has been low despite the decade of dissemination in Asia, especially in the Philippines. Using cross-sectional farm-level survey data, this study empirically explored factors shaping AWD adoption in a gravity surface irrigation system. We used regression-based approaches to examine the factors influencing farmers’ adoption of AWD and its impact on yield. Results showed that the majority of the AWD adopters were farmers who practiced enforced rotational irrigation (RI) scheduling within their irrigators’ association (IA). With the current irrigation management system, the probability of AWD implementation increases when farmers do not interfere with the irrigation schedule (otherwise they opt to go with flooding). Interestingly, the awareness factor did not play a significant role in the farmers’ adoption due to the RI setup. However, the perception of water management as an effective weed control method was positively significant, suggesting that farmers are likely to adopt AWD if weeds are not a major issue in their field. Furthermore, the impact on grain yields did not differ with AWD. Thus, given the RI scheduling already in place within the IA, we recommend fine-tuning this setup following the recommended safe AWD at the IA scale.

The primary key to the modernization of irrigation is the effectiveness of agricultural water use that should be supported by good infrastructure, including information technology (IT). The objective was to evaluate the performance of IT infrastructure in collecting weather data for evaporative irrigation. The system was set up under a natural environment since 10 July 2020 in the Kinjiro Farm, Bogor. The system consisted of three parts, i.e., integrated sensors suite (ISS), console (data logger), and the server, including the dashboard system. The ISS involved several sensors, namely: Pyr solar radiation, rain gauge, air temperature, and humidity sensors, together with wind speed and direction. All data were collected through the console and data logger and then transferred into a local computer server to the dashboard system using an internet connection. The users can access all data from the dashboard system as numerical and graphical data. The system showed a reliable performance, as all data were well properly sent to the server every 30 minutes. The weather parameters, including rain events, were correctly monitored every 30 minutes. All observed data were found to directly affect the reference evapotranspiration, a parameter that will be used for further consideration in determining irrigation scheduling.

The smart evaporative irrigation is offered as an appropriate option in regulating irrigation water more effective. Smart means the system of irrigation is automatically controlled by a floating ball valve based on evaporation and evapotranspiration rate without electrical power. The objective was to evaluate the functional design of the evaporative irrigation on water demand aspect particularly for Mina-padi (paddy–fish farming). The system was evaluated based on the experimental field in the lab-scale since 10 July 2020. There were three irrigation regimes, i.e., continuous flooded (CR), wet (WR), and dry (LR) regimes. During the vegetative growth stage, the smart evaporative irrigation worked well. The irrigation was supplied by a floating ball valve automatically according to the evapotranspiration rate. The actual water levels were well kept and fitted to the setpoint as indicated by low mean absolute error (MAE). The CR regime needs more irrigation water and evaporated more water through the evapotranspiration process. Its rate was highest ranged between 5.81 – 6.6 mm/day. On the other hand, the LR regime has the lowest evapotranspiration rate in between 1.65 – 4.09 mm/day. The irrigation control system became crucial for control the evapotranspiration rate in which less irrigation water evaporate less water.

This paper presents an Internet of Thing system based on the LoRa wireless sensor network to monitor soil moisture to support agricultural cultivation in drought season. Our proposed system was developed using Ai Thinker Ra-02 LoRa module integrated with Arduino pro mini board, which is responsible for gathering soil moisture and transmitting data to a gateway for forwarding to a data server on the internet. So that, farmers and researchers can monitor the soil condition remotely. Two experiments were conducted, which are the sensor calibration test to calculate the volumetric water content from the sensor’s analog signal and the network coverage test to find the LoRa module capability. The system had been deployed to test in the real situation. It is expected to support the farmer to monitor the soil condition of plants due to the effects of drought and salinity phenomena.

Since the 2011 Tohoku earthquake in Japan, natural rainfall has helped to reduce the salinity levels in the root zone of agricultural fields. However, leaching resulting from natural rainfall alone was insufficient for crop management in tsunami-affected regions, where severe subsidence had occurred. In order to understand the desalinization process, a Field Monitoring System was installed with time domain transmission, a sensor network technology used to investigate high soil moisture and high salinity levels in a tsunami-affected field in Miyagi. Using the Field Monitoring System with time domain transmission, volumetric soil water content and bulk soil electrical conductivity was monitored in tsunami-damaged farmland before-and-after the application of two weeks of the flooded leaching method with the addition of a topsoil layer. Pore water electrical conductivity may be estimated based on volumetric soil water content and bulk soil electrical conductivity using the Rhoades model. During the flooded leaching period, in situ bulk soil electrical conductivity dropped above the deeper groundwater but did not decrease near the boundary between the added topsoil and the salt affected cracking subsoil. This indicates that preferential flow may have occurred, and flooded leaching was not enough to reduce the salinity level near the boundary. Pore water electrical conductivity was an excellent indicator of whether the field's salinity level was low enough to maintain moderately salinity sensitive crops such as rice and soybean through Field Monitoring System real time monitoring.

We performed consecutive field trials of rice cultivation to monitor radiocesium contamination in harvested rice from 2012, in the Iitate Village in Fukushima Prefecture, where people were forced to be evacuated due to high level of radioactive contamination caused by the disaster at the Fukushima Dai-ichi Nuclear Power Plant of Tokyo Electric Power. The early year results (2012–2013)1, 2) showed the radiocesium concentration in the brown rice was reduced depending on the decontaminated level of paddy soil and on the exchangeable K content of the soil. This report of later year results (2015–2019) showed further more than 80% reduction of 137Cs concentration in the brown rice and straw at KCl fertilized paddy soil, in spite of little reduction of 137Cs concentration of the soil. The transfer factor of 137Cs from soil to brown rice reduced from 0.0022 in 2015 to 0.0003 in 2019 and that to straw reduced from 0.0262 in 2015 to 0.0028 in 2019, respectively. Exchangeable positive ions of the soil were also analyzed. Multiple regression analyses of all data of transfer factor in 2015 to 2019 to year (ageing) and exchangeable K ion as variables shows that the main causal factor is year (ageing) with some supportive effect of increase of exchangeable K ion. This implicates that radiocesium in soil was gradually transformed to a form more difficult to be absorbed by rice, that is, 137Cs immobilization or fixation on clay minerals by ageing, not only in early years after the accident (2011–2015), but also in later years (2015–2019). This implication was supported by comparative analysis of exchangeable 137Cs of dry soil of 2017, 2018 and 2019.

Traceability is key to ensure food quality and safety from farm to fork, yet high implementation costs and the complexity of the food supply chain pose challenges to its operation. Here we propose a mobile-based bidirectional tracing system for food products that integrates graph data and peer-to-peer architecture. Our system allows data synchronization to happen seamlessly between all connected nodes, as data are gathered through market transactions and all related product information is concatenated by scanning 2D product barcodes. The system’s decentralized and flexible structure favours stakeholder involvement and is applicable to various and dynamic food networks. By promoting resource efficiency and transparency of origin, production and distribution, the system ensures mesh surveillance and sheds light on complex food networks, ultimately contributing to the advancement of food research.