Measuring foliar moisture content with a moisture analyzer

Rossa, Carlos G.; Fernandes, Paulo M.; Pinto, Anita

doi:10.1139/cjfr-2014-0545

Cited by 12 publications

(6 citation statements)

References 9 publications

(10 reference statements)

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“…Many techniques, methods and models have been used to measure or predict the moisture content of dead surface fuels. These include oven drying, fuel sticks, and moisture analyzer (Rossa et al 2015) methods and instant moisture analyzers (e.g., the Wiltronics TH Fine Fuel Moisture Meter). Some methods have intrinsic problems or deficiencies with respect to the results obtained (Bilgili et al 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Some methods have intrinsic problems or deficiencies with respect to the results obtained (Bilgili et al 2014). The commonly accepted reference method for the reliable measurement of fuel moisture content is oven drying (Viney and Hatton 1990;Chatto and Tolhurst 1997;Rossa et al 2015). However, this method is time consuming and labor intensive.…”

Section: Introductionmentioning

confidence: 99%

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Modeling surface fuels moisture content in Pinus brutia stands

et al. 2018

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Fuel moisture content is an important variable for forest fires because it affects fuel ignition and fire behavior. In order to accurately predict fuel ignition potential, fuel moisture content must be assessed by evaluating fire spread, fireline intensity and fuel consumption. Our objective here is to model moisture content of surface fuels in normally stocked Calabrian pine (Pinus brutia Ten.) stands in relation to weather conditions, namely temperature, relative humidity, and wind speed in the Mugla province of Turkey. All surface fuels were categorized according to diameter classes and fuel types. Six fuel categories were defined: these were 0-0.3, 0.3-0.6, and 0.6-1 cm diameter classes, and cone, surface litter, and duff. Plastic containers 15 9 20 cm in size with 1 9 1 mm mesh size were used. Samples were taken from 09:00 to 19:00 h and weighed every 2 h with 0.01 g precision for 10 days in August. At the end of the study, samples were taken to the laboratory, oven-dried at 105°C for 24 h and weighed to obtain fuel-moisture contents. Weather measurements were taken from a fully automated weather station set up at the study site prior to the study. Correlation and regression analyses were carried out and models were developed to predict fuel moisture contents for desorption and adsorption phase for each fuel type categories. Practical fuel moisture prediction models were developed for dry period. Models were developed that performed well with reasonable accuracy, explaining up to 92 and 95.6% of the variability in fuel-moisture contents for desorption and adsorption phases, respectively. Validation of the models were conducted using an independent data set and known fuel moisture prediction models. The predictive power of the models was satisfactory with mean absolute error values being 1.48 and 1.02 for desorption and adsorption as compared to the 2.05 and 1.60 values for the Van Wagner's hourly litter moisture content prediction model. Results obtained in this study will be invaluable for fire management planning and modeling.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling surface fuels moisture content in Pinus brutia stands

et al. 2018

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“…Prinsip kerja dari alat Moisture Analyzer adalah termogravimetri, dimana berat awal sampel dicatat sebagai fungsi dari temperatur sesuai dengan program di dalam alat. Metode penentuan kadar air ini memiliki tingkat keakuratan yang tinggi, karena metode ini meminimalkan kesalahan yang berasal dari luar, seperti keadaan dalam temperatur ruang, serta tekanan, sebab pengukuran kadar air dilakukan dalam keadaan tertutup (Rossa et al, 2015).…”

Section: Hasil Dan Pembahasan Kadar Air Dalam Sampel Buah Kemasan Kalengunclassified

Analisis kadar logam berat (Fe, Zn, Pb, Cd) dan nilai risiko kesehatan dalam buah kemasan kaleng

Suhaili,

Yusuf

2021

chempublish

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Seiring dengan perkembangan teknologi yang semakin pesat, buah-buahan banyak dikemas dalam kaleng. Buah kemasan kaleng merupakan makanan yang sering dikonsumsi oleh manusia pada saat ini. Penyimpanan buah kemasan kaleng dalam waktu yang lama dapat menyebabkan terjadinya migrasi logam berat terhadap buah yang ada di dalam kemasan. Pada penelitian ini sampel yang digunakan yaitu 3 jenis buah-buahan dalam kemasan kaleng masing-masing dengan lama penyimpanan yang berbeda. Preparasi sampel dilakukan menggunakan metode destruksi basah dengan menambahkan campuran HNO3 pekat 65% dan H2O2 15% (3:1). Kandungan logam Fe, Zn, Pb, dan Cd dalam sampel ditentukan menggunakan metode Spektrofotometri Serapan Atom (SSA). Nilai Indeks Risiko Kesehatan (IRK) didapatkan dari hasil perhitungan Asupan Logam Harian (ALH) per dosis yang disarankan oleh WHO. Nilai ALH diperoleh dari perhitungan konsentrasi logam dengan SSA, faktor konversi, dan rata-rata asupan logam per berat badan manusia. Kadar logam berat di dalam ketiga jenis sampel secara umum diperoleh Fe>Zn>Pb>Cd. Konsentrasi logam berat berbanding lurus dengan lama produk disimpan dalam kemasan kaleng. Semakin lama produk disimpan maka konsentrasi logam yang diperoleh semakin tinggi. Nilai IRK yang diperoleh dari pengujian sampel untuk logam Cd yaitu >1 dapat diasumsikan adanya potensi risiko kesehatan, sedangkan untuk logam Pb, Fe, dan Zn <1 yang diasumsikan populasi dinyatakan aman. Nilai TIRK yang diperoleh dari penambahan nilai IRK logam Pb, Cd, Fe, dan Zn, didapatkan hasil dari setiap sampel >1 dapat dinyatakan bahwa sampel yang diuji memiliki potensi risiko kesehatan terhadap manusia. Penelitian lebih lanjut diperlukan untuk memperjelas hubungan antara kontaminasi buah oleh logam berat dari kemasan kaleng.

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“…Fuel load (w) and fuel bed density (ρ b ) exclude woody fuels, i.e., calculations were based solely on leaf litter and elevated foliage based on the assumption that thicker elements contribute less to the fire front advance. With a few exceptions, air temperature (T a ) and relative humidity (RH) were measured just before the burns, which were line-ignited after fuel sampling to assess fuel bed foliar moisture content (M) by oven-drying or using a moisture analyzer [27]. R 0 and R U were determined by timing the base of the flame over a given length, and flame length (L f , measured from the base of the fuel bed) and flame angle (A f , measured from the unburned fuel), except for those in [24], were visually assessed.…”

Section: Of 19mentioning

confidence: 99%

An Empirical Model for the Effect of Wind on Fire Spread Rate

Rossa

Fernandes

2018

Fire

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Predicting wind-driven rate of fire spread (RoS) has been the aim of many studies. Still, a field-tested model for general use, regardless of vegetation type, is currently lacking. We develop an empirical model for wind-aided RoS from laboratory fires (n = 216), assuming that it depends mainly on fire-released energy and on the extension of flame over the fuel bed in still air, and that it can be obtained by multiplying RoS in no-wind and no-slope conditions by a factor quantifying the wind effect. Testing against independent laboratory and field data (n = 461) shows good agreement between observations and predictions. Our results suggest that the fuel bed density effect detected by other work may be a surrogate for the amount of fuel involved in combustion, which depends on fuel load. Because RoS under windless conditions is unaffected by fuel load, the involved mechanisms differ from wind-aided propagation. Compared to shallow fuel beds, the wind effect is usually modest in deep vegetation, because tall fuel complexes are dominated by live fuels (high moisture content) and flames extend less above the vegetation when fuel moisture is high. The present work warrants further inspection in a broader range of field conditions.

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Measuring foliar moisture content with a moisture analyzer

Cited by 12 publications

References 9 publications

Modeling surface fuels moisture content in Pinus brutia stands

Modeling surface fuels moisture content in Pinus brutia stands

Analisis kadar logam berat (Fe, Zn, Pb, Cd) dan nilai risiko kesehatan dalam buah kemasan kaleng

An Empirical Model for the Effect of Wind on Fire Spread Rate

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