scholarly journals Sugarcane maturity estimation through edaphic-climatic parameters

2004 ◽  
Vol 61 (5) ◽  
pp. 486-491 ◽  
Author(s):  
Maximiliano Salles Scarpari ◽  
Edgar Gomes Ferreira de Beauclair
Keyword(s):  
Weather Conditions ◽  
Saccharum Officinarum ◽  
Raw Material ◽  
Coefficient Of Determination ◽  
Soil Water Storage ◽  
Maturity Model ◽  
Sugarcane Crop ◽  
Production Factors ◽  
Using Data ◽  
One Year

Sugarcane (Saccharum officinarum L.) grows under different weather conditions directly affecting crop maturation. Raw material quality predicting models are important tools in sugarcane crop management; the goal of these models is to provide productivity estimates during harvesting, increasing the efficiency of strategical and administrative decisions. The objective of this work was developing a model to predict Total Recoverable Sugars (TRS) during harvesting, using data related to production factors such as soil water storage and negative degree-days. The database of a sugar mill for the crop seasons 1999/2000, 2000/2001 and 2001/2002 was analyzed, and statistical models were tested to estimate raw material. The maturity model for a one-year old sugarcane proved to be significant, with a coefficient of determination (R²) of 0.7049*. No differences were detected between measured and estimated data in the simulation (P < 0.05).

Minum Rice Supply Needs in South Sulawesi-The case of Bulog Divre South Sulawesi

2019 ◽  
Vol 1 (2) ◽  
pp. 36-43
Author(s):  
Asyriah Arifunddin Arifunddin ◽  
Abd. Rahman Kadir ◽  
Sumardi Sumardi
Keyword(s):  
Agricultural Sector ◽  
Raw Material ◽  
Literature Study ◽  
Safety Stock ◽  
Inventory Costs ◽  
South Sulawesi ◽  
Calculation Results ◽  
Point Calculation ◽  
Using Data ◽  
One Year

One issue of the decline in the performance of the agricultural sector is claimed due to  changing the authority of BULOG in managing strategic food through trade system instruments.This study aims to analyze the system of rice supply Perum BULOG South Sulawesi in terms of the number of economic orders, minimum inventory, maximum inventory, and determining the point of reorder. This research was conducted at the Office of Public Logistics Bureau at Jln. Andi Pangeran Pettarani, Makassar. In research using data collection techniques by means of observation, literature study, interviews and documentation. Analysis of the data that has been selected is the Economic Order Quantity (EOQ). The results showed that from the calculation results to determine the economical amount of inventory using EOQ calculations, it is known that the costs of South Sulawesi Bulog raw material inventory in 2017 amounted to 235.41 tons with a ordering frequency of 310 purchases in one year. Whereas from 2017 the realization of the absorption of Bulog rice procurement in South Sulawesi in 2017 amounted to 324,554 tons, with an ordering frequency of 305 times with an average of 1,064 tons per order. If the company can implement the EOQ method can provide savings on raw material inventory costs and the accuracy in managing the amount of inventory. Based on the calculation of the safety stock, it can be seen that in 2017 Bulog must have a safety stock of rice in the warehouse of 18,264 tons to avoid a stock out. Based on the reorder point calculation, Bulog must reorder when the stock is 18,383 tons. The maximum inventory of rice that can be stored in a warehouse is 18,499 tons.

STABILITAS HARGA IKAN DI KOTA AMBON MELALUI PERAN COLD STORAGE, OPTIMASI PRODUKSI DAN EFISIENSI TEKNIS

2018 ◽  
Vol 2 (2) ◽  
pp. 74-84
Author(s):  
Stevanus Marelly Siahainenia ◽  
Dionisius Bawole ◽  
Eygner Gerald Talakua
Keyword(s):  
Cold Storage ◽  
Secondary Data ◽  
Raw Material ◽  
Primary Data ◽  
Survey Method ◽  
Production Factors ◽  
Flying Fish ◽  
Qualitative Descriptive ◽  
Installed Capacity ◽  
Space Capacity

The purpose of this study was to find out the function of cold storage in stabilizing fish prices in Ambon City, analyzing optimal production levels of various types of dominant fish, and analyzing the level of efficiency of utilization of cold storage and auxiliary machinery. This study uses the survey method. Primary data collection through questionnaires is built empirically while secondary data is obtained from several agencies related to this study. The research sample was drawn by exhausting sampling, amounting to 6 cold storage units in Ambon City. The role of cold storage to stabilize fish prices was analyzed using a qualitative descriptive approach, while the quantitative techniques used included analysis of optimization of cold storage production with linear programming and analysis of the efficiency of utilization of cold storage. The results of the study show that cold storage has not played a role properly to stabilize fish prices in Ambon City. To achieve optimal use of production factors, the cold storage management needs to reduce the raw material by 24,915.9 kg / month; 7 HOK / month workforce; cold storage storage space capacity of 2.09 kg / month; and demand for flying fish 1,402.6 kg / month, while the use of production factors efficiently (fully utulized) is the capacity of the freezing machine, demand for tuna, skipjack, and cob. The level of technical efficiency of the utilization of cold storage facilities is reached, the total use of installed capacity must be proportional to the capacity used.

Elaboration of novel adsorbent from Moroccan oil shale using Plackett–Burman design

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Methylene Blue ◽  
Oil Shale ◽  
Screening Method ◽  
Raw Material ◽  
Coefficient Of Determination ◽  
Processing Temperature ◽  
Acid Pretreatment ◽  
Experimental Data Processing ◽  
Experimental Values ◽  
Maximal Capacity

The new adsorbents were prepared from Moroccan oil shale by chemical and physical process .In this study, experimental Plackett-Burman has been used as a screening method to study six factors for the development of materials to adsorbent basis of oil shale Moroccan. The factors have been identified by two levels, To Know temperature (°C), Processing time (min), mass ratio (m precursor/m acid), Pretreatment mixture the precursor with acid, origin of the raw material and type of the activating agent (H2SO4, H3PO4).And it was chosen as a response The maximum quantity of adsorption of the molecule of Methylene blue (Qads in mg/g) and the specific surface measure by the method bet (Sbet in m2/g), The predicted values were in agreement with the experimental values with a coefficient of determination (R2) of 0.98. The model has been validated by experiments subsequent to optimized conditions. The experimental data processing by software JMP 7 showed that the processing temperature The report of oil shale on the acid and activation time were the important effect on the maximal capacity of adsorption of methylene blue. The sample prepared at 237 °C during 215 min with pre-processing has a maximal capacity of adsorption equal to 54mg/g according to model of adsorption of Langmuir and SBET equal to 143 m2/g.

scholarly journals Using Machine Learning Methods to Identify Particle Types from Doppler Lidar Measurements in Iceland

2021 ◽  
Vol 13 (13) ◽  
pp. 2433
Author(s):  
Shu Yang ◽  
Fengchao Peng ◽  
Sibylle von Löwis ◽  
Guðrún Nína Petersen ◽  
David Christian Finger
Keyword(s):  
Machine Learning ◽  
Weather Conditions ◽  
Dust Storms ◽  
Machine Learning Algorithms ◽  
Lidar Data ◽  
Data Sets ◽  
Doppler Lidar ◽  
Lidar Measurements ◽  
Using Data ◽  
Filter Noise

Doppler lidars are used worldwide for wind monitoring and recently also for the detection of aerosols. Automatic algorithms that classify the lidar signals retrieved from lidar measurements are very useful for the users. In this study, we explore the value of machine learning to classify backscattered signals from Doppler lidars using data from Iceland. We combined supervised and unsupervised machine learning algorithms with conventional lidar data processing methods and trained two models to filter noise signals and classify Doppler lidar observations into different classes, including clouds, aerosols and rain. The results reveal a high accuracy for noise identification and aerosols and clouds classification. However, precipitation detection is underestimated. The method was tested on data sets from two instruments during different weather conditions, including three dust storms during the summer of 2019. Our results reveal that this method can provide an efficient, accurate and real-time classification of lidar measurements. Accordingly, we conclude that machine learning can open new opportunities for lidar data end-users, such as aviation safety operators, to monitor dust in the vicinity of airports.

scholarly journals Prediction of Healing Performance of Autogenous Healing Concrete Using Machine Learning

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4068
Author(s):  
Xu Huang ◽  
Mirna Wasouf ◽  
Jessada Sresakoolchai ◽  
Sakdirat Kaewunruen
Keyword(s):  
Machine Learning ◽  
Search Algorithm ◽  
Weather Conditions ◽  
Prediction Performance ◽  
Machine Learning Algorithms ◽  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Support Vector ◽  
Self Healing ◽  
Artificial Neural Network Ann

Cracks typically develop in concrete due to shrinkage, loading actions, and weather conditions; and may occur anytime in its life span. Autogenous healing concrete is a type of self-healing concrete that can automatically heal cracks based on physical or chemical reactions in concrete matrix. It is imperative to investigate the healing performance that autogenous healing concrete possesses, to assess the extent of the cracking and to predict the extent of healing. In the research of self-healing concrete, testing the healing performance of concrete in a laboratory is costly, and a mass of instances may be needed to explore reliable concrete design. This study is thus the world’s first to establish six types of machine learning algorithms, which are capable of predicting the healing performance (HP) of self-healing concrete. These algorithms involve an artificial neural network (ANN), a k-nearest neighbours (kNN), a gradient boosting regression (GBR), a decision tree regression (DTR), a support vector regression (SVR) and a random forest (RF). Parameters of these algorithms are tuned utilising grid search algorithm (GSA) and genetic algorithm (GA). The prediction performance indicated by coefficient of determination (R2) and root mean square error (RMSE) measures of these algorithms are evaluated on the basis of 1417 data sets from the open literature. The results show that GSA-GBR performs higher prediction performance (R2GSA-GBR = 0.958) and stronger robustness (RMSEGSA-GBR = 0.202) than the other five types of algorithms employed to predict the healing performance of autogenous healing concrete. Therefore, reliable prediction accuracy of the healing performance and efficient assistance on the design of autogenous healing concrete can be achieved.

scholarly journals Center-Based Child Care and Differential Improvements in the Child Development Outcomes of Disadvantaged Children

2021 ◽  
Author(s):  
Sarah Anne Reynolds
Keyword(s):  
Child Care ◽  
Child Development ◽  
Economic Status ◽  
Value Added ◽  
Additional Time ◽  
Nationally Representative ◽  
Using Data ◽  
Development Outcomes ◽  
One Year ◽  
The Impact

Abstract Background Research finds center-based child care typically benefits children of low socio-economic status (SES) but few studies have examined if it also reduces inequalities in developmental disadvantage. Objective I test if the length of time in center-based care between ages one and three years associates with child development scores at age three years, focusing on the impact for groups of children in the lower tercile of child development scores and in the lower SES tercile. Method Using data from 1,606 children collected in a nationally representative Chilean survey, I apply a value-added approach to measure gains in child development scores between age one and three years that are associated with length of time in center-based child care. Results Disadvantages at age one year were associated with lower child development scores at age three years. No benefits of additional time in center-based care were found for the non-disadvantaged group, but positive associations were found between more time in center-based care and child development outcomes for children with the SES disadvantage only. Center-based care was not associated with child development trajectories of children with lower child development scores at age one year, no matter their SES status. Conclusions There is evidence that Chilean center-based child care reduces SES inequality in child development scores between ages one and three years, but only if children already were not low-scorers at age one year.

Environmental Conditions Associated With Youth Delinquency Events: A Temporal, Meteorological, and Contextual Perspective

2021 ◽  
pp. 001391652110605
Author(s):  
Alexander Trinidad ◽  
César San Juan ◽  
Laura Vozmediano
Keyword(s):  
Violent Crime ◽  
Weather Conditions ◽  
Violent Crimes ◽  
Public Places ◽  
Youth Delinquency ◽  
Violent Youth ◽  
Direct Association ◽  
Using Data ◽  
Public Holidays ◽  
Rainfall Level

Research on youth delinquency has been essential for gaining a deeper understanding of the etiology of delinquent behavior. Studies considering the environmental perspective have increased during the last decade, but relatively little attention has been paid to temporal patterns and weather conditions. The present study explores the seasonality of youth delinquency as well as the association between violent and non-violent youth offenses and temperature, rainfall, level of darkness, type of day, type of place, and companionship, using data gathered by the police along with data obtained from official weather agencies. To this end, we conducted ANOVA and contingency table analyses. Seasonality was found for non-violent crimes. Companionship, semi-public, and public places were all associated with a higher likelihood of non-violent crime, while darkness and public holidays raise the odds of violent crime to happen. No direct association was found between temperature and type of crime.

scholarly journals Capacity of the mechanical harvesting process of sugar cane billets

2010 ◽  
Vol 67 (6) ◽  
pp. 619-623 ◽  
Author(s):  
Paulo Rodrigues Peloia ◽  
Marcos Milan ◽  
Thiago Libório Romanelli
Keyword(s):  
Sugar Cane ◽  
Saccharum Officinarum ◽  
Raw Material ◽  
Quality Requirements ◽  
Harvesting Process ◽  
Green Conditions

The mechanized harvest of sugar cane (Saccharum officinarum L.) in Brazil is an irreversible trend and it comes with a great concern about the quality of the cane delivered to the industry. A key component to quality is the billet length which affects the processing of raw material, cane deterioration, invisible losses and load density of transport vehicles. Thus, due to the importance of the billet standard in quality and cost of raw material, this study aimed to evaluate if the mechanized harvesting of sugar cane can supply the quality requirements for the crushing process, regarding the billet length. A plot with burnt sugar cane (3.2 ha) and another one with green sugar cane (8.0 ha) were selected to be harvested by two (2) self-propelled sugar cane harvesters. For each harvested 0.4 ha a sample from each infield wagon was collected. The sample was composed by ten billets. The variability in burnt sugar cane was higher than in green sugar cane, and both harvesters did not present the capacity of keeping the billets with similar lengths when operating either in burnt or green conditions.

scholarly journals Quantitative and Physical Evaluation of Patchouli Essential Oils Obtained from Different Sources of Pogostemon cablin

2012 ◽  
Vol 7 (7) ◽  
pp. 1934578X1200700 ◽  
Author(s):  
Norma Hussin ◽  
Luigi Mondello ◽  
Rosaria Costa ◽  
Paola Dugo ◽  
Nik Idris Nik Yusoff ◽  
...  
Keyword(s):  
Essential Oils ◽  
Internal Standard ◽  
Retention Indices ◽  
Raw Material ◽  
Volatile Constituent ◽  
Response Factors ◽  
Oil Storage ◽  
Valuable Product ◽  
Linear Retention Indices ◽  
One Year

Patchouli essential oil can be obtained from fresh, dried and fermented plant material. It is a highly valuable product in the fragrance industry and its quality changes depending upon raw material age and oil storage. In this work, patchouli essential oils derived from different treatments have been subjected to GC-FID quantitative analysis using an internal standard (ISTD) method with response factors (RF). Samples were obtained from i) fresh plants; ii) hydrodistillation of one year mature and fermented plants; iii) hydrodistillation of one year mature plants; iv) commercial products from Indonesia and Malaysia. Linear Retention Indices (LRI) for both polar and non-polar GC-MS analyses were also measured as a tool for qualitative analysis towards a homologous series of C7-C30 n-alkanes. The results obtained confirmed that, in all samples, patchouli alcohol was the main volatile constituent, with higher amount in lab-scale produced oils, compared with commercial samples. Other major compounds, in lab oils and commercial samples respectively, were: δ-guaiene, α-guaiene, pogostol, seychellene and α-patchoulene. Another 36 compounds were also found.

scholarly journals Water stress indices for the sugarcane crop on different irrigated surfaces

2016 ◽  
Vol 20 (10) ◽  
pp. 925-929 ◽  
Author(s):  
Rodrigo G. Brunini ◽  
José E. P. Turco
Keyword(s):  
Water Stress ◽  
Raw Materials ◽  
Irrigation System ◽  
Canopy Temperature ◽  
Ambient Air ◽  
Saccharum Officinarum ◽  
Stress Index ◽  
Stress Indices ◽  
Sugarcane Crop ◽  
Water Stress Index

ABSTRACT Sugarcane (Saccharum officinarum L.) is a crop of vital importance to Brazil, in the production of sugar and ethanol, power generation and raw materials for various purposes. Strategic information such as topography and canopy temperature can provide management technologies accessible to farmers. The objective of this study was to determine water stress indices for sugarcane in irrigated areas, with different exposures and slopes. The daily water stress index of the plants and the water potential in the soil were evaluated and the production system was analyzed. The experiment was carried out in an “Experimental Watershed”, using six surfaces, two horizontal and the other ones with 20 and 40% North and South exposure slopes. Water stress level was determined by measuring the temperatures of the vegetation cover and the ambient air. Watering was carried out using a drip irrigation system. The results showed that water stress index of sugarcane varies according to exposure and slope of the terrain, while areas whose water stress index was above 5.0 oC had lower yield values.

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