scholarly journals Quantification of Changes in Rice Production for 2003–2019 with MODIS LAI Data in Pursat Province, Cambodia

2021 ◽  
Vol 13 (10) ◽  
pp. 1971
Author(s):  
Yu Iwahashi ◽  
Rongling Ye ◽  
Satoru Kobayashi ◽  
Kenjiro Yagura ◽  
Sanara Hor ◽  
...  
Keyword(s):  
Socioeconomic Development ◽  
Management Practices ◽  
Moving Average ◽  
Dry Season ◽  
Rice Production ◽  
Smoothing Methods ◽  
Geographical Variations ◽  
Major Shift ◽  
The Difference ◽  
Modis Lai

Rice is not merely a staple food but an important source of income in Cambodia. Rapid socioeconomic development in the country affects farmers’ management practices, and rice production has increased almost three-fold over two decades. However, detailed information about the recent changes in rice production is quite limited and mainly obtained from interviews and statistical data. Here, we analyzed MODIS LAI data (MCD152H) from 2003 to 2019 to quantify rice production changes in Pursat Province, one of the great rice-producing areas in Cambodia. Although the LAI showed large variations, the data clearly indicate that a major shift occurred in approximately 2010 after applying smoothing methods (i.e., hierarchical clustering and the moving average). This finding is consistent with the results of the interviews with the farmers, which indicate that earlier-maturing cultivars had been adopted. Geographical variations in the LAI pattern were illustrated at points analyzed along a transverse line from the mountainside to the lakeside. Furthermore, areas of dry season cropping were detected by the difference in monthly averaged MODIS LAI data between January and April, which was defined as the dry season rice index (DSRI) in this study. Consequently, three different types of dry season cropping areas were recognized by nonhierarchical clustering of the annual LAI transition. One of the cropping types involved an irrigation-water-receiving area supported by canal construction. The analysis of the peak LAI in the wet and dry seasons suggested that the increase in rice production was different among cropping types and that the stagnation of the improvements and the limitation of water resources are anticipated. This study provides valuable information about differences and changes in rice cropping to construct sustainable and further-improved rice production strategies.

scholarly journals Assessing Opportunities to Increase Yield and Profit in Rainfed Lowland Rice Systems in Indonesia

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 777
Author(s):  
Erythrina Erythrina ◽  
Arif Anshori ◽  
Charles Y. Bora ◽  
Dina O. Dewi ◽  
Martina S. Lestari ◽  
...  
Keyword(s):  
Best Management Practices ◽  
Management Practices ◽  
Nutrient Management ◽  
Agricultural Research ◽  
Rice Yield ◽  
Information Access ◽  
Water Reservoir ◽  
Dry Season ◽  
Rice Production ◽  
Yield Gap

In this study, we aimed to improve rice farmers’ productivity and profitability in rainfed lowlands through appropriate crop and nutrient management by closing the rice yield gap during the dry season in the rainfed lowlands of Indonesia. The Integrated Crop Management package, involving recommended practices (RP) from the Indonesian Agency for Agricultural Research and Development (IAARD), were compared to the farmers’ current practices at ten farmer-participatory demonstration plots across ten provinces of Indonesia in 2019. The farmers’ practices (FP) usually involved using old varieties in their remaining land and following their existing fertilizer management methods. The results indicate that improved varieties and nutrient best management practices in rice production, along with water reservoir infrastructure and information access, contribute to increasing the productivity and profitability of rice farming. The mean rice yield increased significantly with RP compared with FP by 1.9 t ha–1 (ranges between 1.476 to 2.344 t ha–1), and net returns increased, after deducting the cost of fertilizers and machinery used for irrigation supplements, by USD 656 ha–1 (ranges between USD 266.1 to 867.9 ha–1) per crop cycle. This represents an exploitable yield gap of 37%. Disaggregated by the wet climate of western Indonesia and eastern Indonesia’s dry climate, the RP increased rice productivity by 1.8 and 2.0 t ha–1, with an additional net return gain per cycle of USD 600 and 712 ha–1, respectively. These results suggest that there is considerable potential to increase the rice production output from lowland rainfed rice systems by increasing cropping intensity and productivity. Here, we lay out the potential for site-specific variety and nutrient management with appropriate crop and supplemental irrigation as an ICM package, reducing the yield gap and increasing farmers’ yield and income during the dry season in Indonesia’s rainfed-prone areas.

Smoothing Facilitates the Detection of Coupled Responses in Psychophysiological Time Series

2000 ◽  
Vol 14 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Joni Kettunen ◽  
Niklas Ravaja ◽  
Liisa Keltikangas-Järvinen
Keyword(s):  
Time Series ◽  
Type I Error ◽  
Electrodermal Activity ◽  
Moving Average ◽  
Type I ◽  
Facial Electromyography ◽  
Response Characteristics ◽  
Smoothing Methods ◽  
Response Systems ◽  
Different Response

Abstract We examined the use of smoothing to enhance the detection of response coupling from the activity of different response systems. Three different types of moving average smoothers were applied to both simulated interbeat interval (IBI) and electrodermal activity (EDA) time series and to empirical IBI, EDA, and facial electromyography time series. The results indicated that progressive smoothing increased the efficiency of the detection of response coupling but did not increase the probability of Type I error. The power of the smoothing methods depended on the response characteristics. The benefits and use of the smoothing methods to extract information from psychophysiological time series are discussed.

Radiographic Prevalence of Osteochondrosis in Yearling Feral Horses

1999 ◽  
Vol 12 (03) ◽  
pp. 151-155 ◽  
Author(s):  
L. W. Valentino ◽  
E. M. Gaughan ◽  
D. R. Biller ◽  
R. H. Raub ◽  
J. D. Lillich
Keyword(s):  
Subchondral Bone ◽  
Management Practices ◽  
Articular Surface ◽  
Radiographic Images ◽  
Feral Horses ◽  
Metacarpophalangeal Joints ◽  
Genetic Base ◽  
Domestic Horses ◽  
The Difference ◽  
Metatarsophalangeal Joints

The purpose of the study is to document the prevalence of articular surface osteochondrosis lesions in feral horses. Eighty yearling feral horses were used. Radiographic images of the left stifle, both tarsocrural, metatarsophalangeal, metacarpophalangeal joints were taken. Radiographs were examined for the presence of osteochondral fragmentation and abnormal outline of subchondral bone suggestive of osteochondrosis. The prevalence of each lesion was calculated for each joint as well as for overall prevalence within the group, the latter being 6.25%. Typical osteochondrosis lesions were found within the tarsocrural and metatarsophalangeal joints. Based on the difference in prevalence of osteochondrosis between feral and certain domestic horses, management practices and perhaps genetic base may have a greater influence on the development of the disease in horses than trauma alone.

Carbon stocks in Tasmanian soils

Soil Research ◽  
2012 ◽  
Vol 50 (2) ◽  
pp. 83 ◽  
Author(s):  
W. E. Cotching
Keyword(s):  
Management Practices ◽  
Agricultural Soils ◽  
C Sequestration ◽  
Mean Annual Temperature ◽  
Soil C ◽  
C Stocks ◽  
Initial Soil ◽  
If Current ◽  
Intensive Cropping ◽  
The Difference

Soil carbon (C) stocks were calculated for Tasmanian soil orders to 0.3 and 1.0 m depth from existing datasets. Tasmanian soils have C stocks of 49–117 Mg C/ha in the upper 0.3 m, with Ferrosols having the largest soil C stocks. Mean soil C stocks in agricultural soils were significantly lower under intensive cropping than under irrigated pasture. The range in soil C within soil orders indicates that it is critical to determine initial soil C stocks at individual sites and farms for C accounting and trading purposes, because the initial soil C content will determine if current or changed management practices are likely to result in soil C sequestration or emission. The distribution of C within the profile was significantly different between agricultural and forested land, with agricultural soils having two-thirds of their soil C in the upper 0.3 m, compared with half for forested soils. The difference in this proportion between agricultural and forested land was largest in Dermosols (0.72 v. 0.47). The total amount of soil C in a soil to 1.0 m depth may not change with a change in land use, but the distribution can and any change in soil C deeper in the profile might affect how soil C can be managed for sequestration. Tasmanian soil C stocks are significantly greater than those in mainland states of Australia, reflecting the lower mean annual temperature and higher precipitation in Tasmania, which result in less oxidation of soil organic matter.

scholarly journals Has the fishery contributed to a major shift in the distribution of South African sardine?

2008 ◽  
Vol 65 (9) ◽  
pp. 1676-1688 ◽  
Author(s):  
Janet C. Coetzee ◽  
Carl D. van der Lingen ◽  
Laurence Hutchings ◽  
Tracey P. Fairweather
Keyword(s):  
South African ◽  
West Coast ◽  
Management Practices ◽  
Fishing Effort ◽  
South Coast ◽  
The West ◽  
Natal Homing ◽  
Distinct Unit ◽  
Major Shift ◽  
Sardine Population

Abstract Coetzee, J. C., van der Lingen, C. D., Hutchings, L., and Fairweather, T. P. 2008. Has the fishery contributed to a major shift in the distribution of South African sardine? – ICES Journal of Marine Science, 65: 1676–1688. A major shift in the distribution of South African sardine (Sardinops sagax) has resulted in a significant spatial mismatch in fishing effort vs. fish abundance in recent years. The sardine fishery started on the west coast during the 1940s, and processing capacity there increased rapidly. This trend together with increases in annual landings continued up to the early 1960s, but then the fishery collapsed as a consequence of overfishing. The population then recovered steadily during the 1980s and 1990s, coincident with, but perhaps not entirely attributable to, the inception of conservative management practices, to support catches similar to pre-collapse levels. Since 2001, however, most of the sardine population has been situated on South Africa’s south coast, far from processing facilities. Fishing effort has increased concomitantly on that coast, particularly during the past three years, reflecting the continued decline in the abundance of sardine on the west coast. Three hypotheses explaining the change in the distribution of sardine have been proposed: (i) intensely localized (i.e. west coast) fishing pressure depleted that part (or functionally distinct unit) of the population; (ii) the shift was environmentally induced; and (iii) successful spawning and recruit survival on the south coast contributed disproportionately more towards the bulk of recruitment, and progeny spawned there now dominate the population and exhibit natal homing. The first of these hypotheses is evaluated, and management implications of the shift discussed.

scholarly journals Prediksi Pemakaian Listrik Kelompok Tarif Menggunakan Jaringan Syaraf Tiruan dan ARIMA

2013 ◽  
Vol 7 (2) ◽  
pp. 189
Author(s):  
Silviani E Rumagit ◽  
Azhari SN
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Neural Networks ◽  
Statistical Method ◽  
Moving Average ◽  
Electric Energy ◽  
Backpropagation Neural Network ◽  
The Difference ◽  
The Government ◽  
Increasing Demand

AbstrakLatar Belakang penelitian ini dibuat dimana semakin meningkatnya kebutuhan listrik di setiap kelompok tarif. Yang dimaksud dengan kelompok tarif dalam penelitian ini adalah kelompok tarif sosial, kelompok tarif rumah tangga, kelompok tarif bisnis, kelompok tarif industri dan kelompok tarif pemerintah. Prediksi merupakan kebutuhan penting bagi penyedia tenaga listrik dalam mengambil keputusan berkaitan dengan ketersediaan energi listik. Dalam melakukan prediksi dapat dilakukan dengan metode statistik maupun kecerdasan buatan.            ARIMA merupakan salah satu metode statistik yang banyak digunakan untuk prediksi dimana ARIMA mengikuti model autoregressive (AR) moving average (MA). Syarat dari ARIMA adalah data harus stasioner, data yang tidak stasioner harus distasionerkan dengan differencing. Selain metode statistik, prediksi juga dapat dilakukan dengan teknik kecerdasan buatan, dimana dalam penelitian ini jaringan syaraf tiruan backpropagation dipilih untuk melakukan prediksi. Dari hasil pengujian yang dilakukan selisih MSE ARIMA, JST dan penggabungan ARIMA, jaringan syaraf tiruan tidak berbeda secara signifikan. Kata Kunci— ARIMA, jaringan syaraf tiruan, kelompok tarif.  AbstractBackground this research was made where the increasing demand for electricity in each group. The meaning this group is social, the household, business, industry groups and the government fare. Prediction is an important requirement for electricity providers in making decisions related to the availability of electric energy. In doing predictions can be made by statistical methods and artificial intelligence.            ARIMA is a statistical method that is widely used to predict where the ARIMA modeled autoregressive (AR) moving average (MA). Terms of ARIMA is the data must be stationary, the data is not stationary should be stationary  use differencing. In addition to the statistical method, predictions can also be done by artificial intelligence techniques, which in this study selected Backpropagation neural network to predict. From the results of tests made the difference in MSE ARIMA, ANN and merging ARIMA, artificial neural networks are not significantly different. Keyword—ARIMA, neural network, tarif groups

scholarly journals ‘B-M MODEL’ FOR FARMERS’ KNOWLEDGE MANAGEMENT IN INCREASING RICE PRODUCTION

2021 ◽  
Vol 2 (1) ◽  
pp. 30-45
Author(s):  
BK Mahalder ◽  
◽  
MB Ahmed ◽  
H Bhandari ◽  
MU Salam ◽  
...  
Keyword(s):  
Knowledge Management ◽  
Field Data ◽  
Production Systems ◽  
Rice Yield ◽  
Rice Production ◽  
Practice Change ◽  
Clear Understanding ◽  
Data Set ◽  
Production Practices ◽  
The Difference

Quantifying knowledge on agriculture can have many benefits to stakeholders. While many knowledge-based systems exist in modern days for farmers’ decision support, specific models are lacking on how knowledge traits can impact on agricultural production systems. This study employed modelling technique, supported by field data, to provide a clear understanding and quantifying how knowledge management in production practices can contribute to rice productivity in the environmentally stressed southwest Bangladesh. This research accounted for ‘Boro’ rice as the target crop and ‘BRRI dhan28’ as the test variety. The ‘B-M Model’ was developed following the principle and procedure from published literature, ‘brainstorming’ and data from field surveys. Three knowledge management traits (KMT) were defined and quantified as the inputs of the model. Those are: self-experience and observation (SEO), extension advisory services (EAS) and accessed information sources (AIS). The yield influencing process (YIP), the intermediate state variable of the model, was deduced by accounting for the two dominant agronomic practices, seedling age for transplanting and triple superphosphate (TSP) application. ‘Knowledge drives farmers’ practice change which in turn influences yield’ was composed as the theoretical framework of the ‘B-M Model’. The model performed strongly against an independently collected field data set. Across the 180 farmers’ data, the average relative rice yield (RRY) predicted by the model (0.705) and observed in the field (0.716) was close (root mean squared deviation (RMSD) = 0.018). The difference between predicted and observed RRY was not statistically different (LSD = 0.03), indicating the model fully captured the field data. A regression of predicted and observed RRY explained 96% variance in observation, further proving the model’s strength in estimating RRY in a wider range of farmers’ rice yield. In a normative analysis, the practicality and usefulness of the model to stakeholders were simulated for the understanding of how much achievable yield could be expected by changing farmers’ knowledge pool (the sum of three KMT) on rice production practices, and at what combination(s) of KMT to be considered at strategic hierarchy to materialize a targeted achievable yield. To the best of the knowledge, a model quantifying rice yield in relation to knowledge management trait does not exist in literature. Upon successful testing under diverse yield scenarios using multiple and sophisticated statistical tools that enhanced the credibility of the model, it is concluded that the model has the potential to be used for identifying quantitative pathways of farmers’ knowledge acquisition for practice change leading to improved productivity of rice in the southwest region of Bangladesh.

scholarly journals Mellem to verdener - Krigsrepræsentationer hos Walter Flex, Ernst Jünger og Erich Maria Remarque

2018 ◽  
pp. 65-84
Author(s):  
Adam Paulsen
Keyword(s):  
World War I ◽  
World War ◽  
Western Front ◽  
Major Shift ◽  
The Difference ◽  
To Come ◽  
The Wanderer

This article compares representations of war in Walter Flex’ The Wanderer between Two Worlds (1916), Ernst Jünger’s Storm of Steel (1920), and Erich Maria Remarque’s All Quiet on the Western Front (1929). It shows the extent to which these representations are shaped by political and ideological convictions. The difference between the romantic idealism of Flex and Jünger’s “soldierly nationalism”,which he proposed as a model for the time to come, reflects a major shift during World War I itself. By contrast, neither past nor future seem to be of any use in Remarque’s famous antiwar novel, in which the war generation surprisingly is described as having nothing else to live for beyond the present, i.e. beyond war. Finally, the article suggests how these different representations of war each, in their own way, contributed to the aesthetics and ideology of fascism.

scholarly journals Penggunaan metode algoritma wagner within dalam upaya pengendalian persediaan scrap besi di PT XYZ

2020 ◽  
Vol 5 (1) ◽  
pp. 56-73
Author(s):  
Somadi ◽  
Syah Rajendra Hari Septa ◽  
Nila Dahlia Juita
Keyword(s):  
Control Method ◽  
Moving Average ◽  
Demand Forecasting ◽  
Lot Size ◽  
Total Size ◽  
Total Cost ◽  
Smoothing Methods ◽  
Before And After ◽  
Iron Scrap ◽  
Total Inventory

The research objective is to determine the total size of the lot of iron scrap orders, and the total cost of the company's inventory before and after carrying out the method of controlling iron scrap inventory using the Wagner Within Algorithm method. Demand forecasting uses the Single Moving Averge, Weight Moving Average, and Exponential Smoothing methods. Based on the results of the study, the total lot size of iron scrap material orders is smaller than the size of previous lot orders without using the inventory control method, which is 15,362 tons per year. Total inventory of Rp. 105,076,125,840 and the total cost is more optimal when compared with the total cost of inventory with the company system that is Rp. 109,734,165,840 so that the company can save costs by Rp. 4,658,040,000.

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