Overview of Manually Operated Paddy Transplanter

Agriculture is the most important sector in the Indian economy. It is the most important source of employment for most of the country’s labor force. In 2012, about 49% of the labor force was engaged in agriculture. The highest proportion of these is in the rice sector. Rice is the country’s main stable food. The release of labor to sectors other than agriculture is important to the development of the country. The mechanization of rice fields has played an important role in liberating labor. Feeding a growing population is a huge challenge. The import of rice will cause the country’s economy to drain. The mechanization of the rice sector will lead to higher productivity and release labor to other sectors. The goal of the project is to design a rice transplanting mechanism for small farmers in the country to transplant rice seedlings.

Stopping Winter Flooding of Rice Fields to Control Invasive Snails Has no Effect on Waterbird Abundance at the Landscape Scale

The invasive apple snail (Pomacea maculata) appeared in 2010 in the Ebro Delta Natural Park, an important area for rice production and waterbird conservation in the eastern Mediterranean. To control crop damage, farmers stopped flooding their rice fields in winter, an agri-environmental scheme (AES) applied for more than 20 years in some European and American regions to favor flora and fauna from wetlands, including wintering waterbirds. Thus, apple snail control is controversial because of its potential side effects on international waterbird conservation efforts. Despite the fact that 10 years have passed since the first flooding limitations, and the alarms raised by the managers of the Natural Park, the side effects of apple snail management on waterbird conservation have not been evaluated. Here we fill this gap by analyzing a 35-year time series to assess whether abundance trends of 27 waterbird species, from five functional groups, decreased in the Ebro Delta after stopping winter flooding. We considered the effects of confounding local factors by also assessing trend changes in l’Albufera, a similar nearby not invaded wetland where flooding has not been interrupted. In addition, as a control of the positive effect of winter flooding, we also assessed whether abundance trends increased in both wetlands after applying this AES winter flooding. Our results showed complex and decoupled trend changes across species and geographical areas, without statistical evidences, in general or for any particular functional group, on the positive effect of winter flooding in both wetlands neither on the negative effect of its cessation in Ebro Delta. These results suggest the safety of this apple snail control in terms of waterbird abundance at a landscape scale. In addition, these results question, at least in two important wintering areas in Europe, the attractor role associated with the flooding agri-environmental scheme applied for decades.

Drought assessment in paddy rice fields using remote sensing technology towards achieving food security and SDG2

PurposeThis research aims to monitor vegetation indices to assess drought in paddy rice fields in Mazandaran, Iran, and propose the best index to predict rice yield.Design/methodology/approachA three-step methodology is applied. First, the paddy rice fields are mapped by using three satellite-based datasets, namely SRTM DEM, Landsat8 TOA and MYD11A2. Second, the maps of indices are extracted using MODIS. And finally, the trend of indices over rice-growing seasons is extracted and compared with the rice yield data.FindingsRice paddies maps and vegetation indices maps are provided. Vegetation Health Index (VHI) combining average Temperature Condition Index (TCI) and minimum Vegetation Condition Index (VCI), and also VHI combining TCImin and VCImin are found to be the most proper indices to predict rice yield.Practical implicationsThe results serve as a guideline for policy-makers and practitioners in the agro-food industry to (1) support sustainable agriculture and food safety in terms of rice production; (2) help balance the supply and demand sides of the rice market and move towards SDG2; (3) use yield prediction in the rice supply chain management, pricing and trade flows management; and (4) assess drought risk in index-based insurances.Originality/valueThis study, as one of the first research assessing and mapping vegetation indices for rice paddies in northern Iran, particularly contributes to (1) extracting the map of paddy rice fields in Mazandaran Province by using satellite-based data on cloud-computing technology in the Google Earth Engine platform; (2) providing the map of VCI and TCI for the period 2010–2019 based on MODIS data and (3) specifying the best index to describe rice yield through proposing different calculation methods for VHI.

Reducing impacts of rice fields nitrate contamination on the river ecosystem by a coupled SWAT reservoir operation optimization model

The present study proposes a multipurpose reservoir operation optimization for mitigating impact of rice fields’ contamination on the downstream river ecosystem. The developed model was applied in the Tajan River basin in Mazandaran Province, Iran, in which the rice is the main crop. We used soil and water assessment tool (SWAT) to simulate inflow of the reservoir and nitrate load at downstream river reach. Nash–Sutcliffe model efficiency coefficient was used to measure the robustness of SWAT. NSE indicated that SWAT is acceptable to simulate nitrate load of the rice fields. The results of SWAT was applied in the structure of a multipurpose reservoir operation optimization in which three metaheuristic algorithms including differential evolution algorithm, particle swarm optimization and biogeography-based algorithm were utilized in the optimization process. Reliability index, mean absolute error and failure index were used to measure the robustness of the optimization algorithms. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution was utilized to select the best algorithm. Based on results, particle swarm optimization is the best method to optimize reservoir operation in the case study. The reliability index and mean absolute error for water supply are 0.6 and 5 million cubic meters, respectively. Furthermore, the failure index of contamination is 0.027. Hence, it could be concluded that the proposed optimization system is reliable and robust to mitigate losses and nitrate contamination simultaneously. However, its performance is not perfect for minimizing impact of contamination in all the simulated months.

Land cover classification using Landsat 8 OLI in West Langsa Sub district, Langsa City

Land cover information is needed by various parties as a consideration in controlling land cover changes. The latest land cover information can be obtained using remote sensing techniques in the form of image classification maps. This technique is very effective in monitoring land cover because of its ability to quickly, precisely, and easily provide spatial information on the earth’s surface. The purpose of this study was to classify land cover in West Langsa Sub district, Langsa City using Landsat 8 OLI (Operational Land Imager) imagery. The classification method used in this study is the maximum likelihood classification (MLC) method. There are several considerations of various factors in the MLC method, including the probability of a pixel to be classified into a certain type or class. The results of Landsat 8 OLI image classification in West Langsa Sub district resulted in 6 land cover classes, namely mangrove forests, settlements, rice fields, shrubs, ponds and bodies of water. The largest land cover class is ponds with an area of 1981.54 ha (38.71%) and the smallest land cover is rice fields with an area of 115.58 ha (2.26%) of the total land cover class. Classification accuracy is indicated by the overall accuracy and kappa accuracy of 91.15% and 82.75%, respectively. These results meet the requirements set by the USGS (Overall Accuracy > 85%) and indicate that the Landsat 8 OLI image classification map can be used for various purposes.

Penilaian Status Kesuburan Tanah Desa Tijayan Kecamatan Manisrenggo Kabupaten Klaten

Tijayan Village is located in Manisrenggo District, Klaten Regency, which has an area of agricultural land in the form of rice fields which is 105.80 ha of 155.3 ha of the village area. The extent of agricultural land in Tijayan Village needs to be maintained to increase agricultural products ranging from rice, secondary crops, and horticulture commodities. The researcher found a lack of information about soil maintenance in Tijayan Village. Therefore, the researcher conducted this research to determine and study the soil fertility and soil management efforts based on the limiting factors of fertility in Tijayan Village. In addition, soil fertility assessment is based on a desk study, detailed survey, soil analysis, making fertility distribution maps, and descriptive analysis. Determination of soil fertility status based on Soil Research Guidelines published by Soil Research Center, Bogor Indonesia, with parameters of cation exchange capacity, base saturation, total phosphorus, total potassium, and C- organic. Map made by using the ArcGIS 10.4 application. The fertility of Tijayan Village is categorized as low soil fertility class. The limiting factors for soil fertility are soil cation exchange capacity 3.47 me/ 100 g until 12.33 me/100g, total potassium < 10 mg/100g, and C- organic 1.213% - 2.286% . Consequently, management needs to be done by adding organic matter to the soil, fertilizing organically or inorganically, and the principle of healthy plant cultivation for rice fields.

Continuous Maize Cropping Accelerates Loss of Soil Organic Matter in Northern Thailand as Revealed by Natural 13C Abundance

AimsThe loss of soil organic matter (SOM) has widely been reported in the tropics after changing land use from shifting cultivation to continuous cropping. We tested whether continuous maize cultivation accelerates SOM loss compared to upland rice and forest fallow. Methods: Because litter sources include C4 plants (maize in maize fields and Imperata grass in upland rice fields) in Thailand, C3-derived and C4-derived SOM can be traced using the differences in natural 13C abundance (δ13C) between C3 and C4 plants. We analyzed the effects of land use history (cultivation or forest fallow period) on C stocks in the surface soil. Soil C stocks decreased with the cultivation period in both upland rice and maize fields. ResultsThe rate of soil organic carbon loss was higher in maize fields than in upland rice fields. The decomposition rate constant (first order kinetics) of C3-plant-derived SOM was higher in the maize fields than in the upland rice fields and the C4-plant-derived SOM in the forest fallow. Soil surface exposure and low input of root-derived C in the maize fields are considered to accelerate SOM loss. Soil C stocks increased with the forest fallow period, consistent with the slow decomposition of C4-plant-derived SOM in the forest fallows. ConclusionsContinuous maize cultivation accelerates SOM loss, while forest fallow and upland rice cultivation could mitigate the SOM loss caused by continuous maize cultivation.