Relationship of weather and plant factors to alfalfa bloat in autumn

1991 ◽  
Vol 71 (3) ◽  
pp. 861-866 ◽  
Author(s):  
J. W. Hall ◽  
W. Majak
Keyword(s):  
Key Words ◽  
Total Nitrogen ◽  
Minimum Temperature ◽  
Dry Matter ◽  
Extreme Case ◽  
Weather Data ◽  
Maximum Temperature ◽  
Soluble Nitrogen ◽  
Acid Detergent Fiber ◽  
Relationship Of

The bloat status of cattle was recorded in the autumns of 6 yr when bloat occurred during the decade 1979–1988. Weather data were available for all 6 yr, plant dry matter, acid detergent fiber and plant chlorophyll for 3 yr and plant total nitrogen and soluble nitrogen for 4 yr. The percentages of dry matter and acid detergent fiber were lower and the concentrations of chlorophyll, total nitrogen and soluble nitrogen were higher on days when bloat occurred than when it did not. There was no difference in minimum temperature classified by bloat status on the same day, or in maximum temperature, hours of sunshine or precipitation classified by bloat status on the next day. Hours of sunshine and the temperature range were greater on days when bloat occurred. Bloat was observed after "killing frosts" of −2.2 °C in all years and in an extreme case after a daily minimum of −9.6 °C. Key words: Legume, bloat, alfalfa, cattle, climate

HIGH MOISTURE GROUND EAR CORN, HIGH MOISTURE BARLEY OR SODIUM HYDROXIDE TREATED BARLEY FOR LACTATING COWS: MILK PRODUCTION AND RATION UTILIZATION

1983 ◽  
Vol 63 (1) ◽  
pp. 155-162 ◽  
Author(s):  
L. KUNG Jr. ◽  
B. W. JESSE ◽  
J. W. THOMAS ◽  
J. T. HUBER ◽  
R. S. EMERY
Keyword(s):  
Sodium Hydroxide ◽  
Key Words ◽  
Milk Production ◽  
Dry Matter ◽  
Milk Composition ◽  
Dry Matter Intake ◽  
High Moisture ◽  
Acid Detergent Fiber ◽  
Lactating Cows ◽  
Fecal Ph

Whole barley was treated with sodium hydroxide (NaOH) in laboratory trials. Dry matter disappearance from nylon bags in the rumen of whole barley treated with 2.5, 3.5, or 4.9% NaOH for 30 h was 59.6, 72.4, and 93.0%, respectively, compared with 82.2% for untreated ground barley. In a subsequent lactation trial, 24 Holstein cows (eight per treatment) were fed high moisture ground ear corn, high moisture rolled barley or high moisture whole barley treated with 3.5% NaOH. Milk persistencies tended to be greater for cows fed high moisture rolled barley, next for ground ear corn and least for NaOH-treated barley. Milk composition was similar for all treatments. Dry matter intake was greatest for cows fed ground ear corn and lower for those fed the barley diets. Alpha-linked glucose and pH of feces were similar for cows fed ground ear corn and high moisture rolled barley diets, but fecal pH was lower and alpha-linked glucose concentrations three times greater for NaOH-treated barley. Digestibility percents of dry matter, acid detergent fiber and nitrogen were 61.4, 25.3, 64.7 for ground ear corn; 64.4, 38.0, 67.1 for high moisture rolled barley; and 56.8, 43.2, 54.8 for NaOH-treated barley, respectively. Rumen grain turnover estimated by excretion of ytterbium in feces was greatest for NaOH-treated barley (9.09%/h), intermediate for ground ear corn (6.10%/h) and lowest for high moisture rolled barley (4.93%/h). Key words: Dairy, sodium hydroxide, high moisture grains

Note. Effect of brining time on proteolytic changes in Idiazábal cheese during ripening / Nota. Cambios proteolíticos durante la maduración del queso Idiazábal por efecto del tiempo en salmuera

1996 ◽  
Vol 2 (5) ◽  
pp. 335-339 ◽  
Author(s):  
F.C. Ibáñez ◽  
A.I. Ordóñez ◽  
M.S. Vicente ◽  
M.I. Torres ◽  
Y. Barcina
Keyword(s):  
Amino Acids ◽  
Glutamic Acid ◽  
Total Nitrogen ◽  
Free Amino Acids ◽  
Free Amino ◽  
Dry Matter ◽  
Electrophoretic Analysis ◽  
Soluble Nitrogen ◽  
Clear Trend ◽  
Protein Nitrogen

Idiazábal cheeses were made employing brining times of 12 h (batch A) and 36 h (batch B). Proteolytic changes in both batches were examined over 270 d of ripening; proteolysis was low in both batches, but lower in batch B than in batch A. Electrophoretic analysis revealed incom plete breakdown of αs and β-caseins at the end of the ripening period, particularly in batch B. The proportion of soluble nitrogen as a percentage of total nitrogen was 17.55% in batch B and 19.48% in batch A, while the proportion of non-protein nitrogen was 11.78% in batch B and 15.16% in batch A. The proportion of non-protein nitrogen as a percentage of soluble nitrogen was 67.17% in batch B and 77.88% in batch A. The free amino acids, the smallest non-protein nitrogen frac tion, attained values of 1203 mg/100 g of dry matter in batch B and 1902 mg/100 g of dry matter in batch A. After 60 d of ripening, the main free amino acids were glutamic acid, valine, leucine, lysine, and phenylalanine in both batches, although levels were higher in the batch with the shorter brining time. There was no clear trend in the non-protein-forming amino acids with either ripening time or brining time.

scholarly journals The effects of fiber supplementation on diet digestibility by silver foxes

1991 ◽  
Vol 71 (3) ◽  
pp. 943-947 ◽  
Author(s):  
W. L. Faulkner ◽  
D. M. Anderson
Keyword(s):  
Weight Loss ◽  
Key Words ◽  
Water Consumption ◽  
Dry Matter ◽  
Apparent Digestibility ◽  
Acid Detergent Fiber ◽  
Oat Hulls ◽  
Fiber Diet ◽  
Oat Bran ◽  
Meat Type

A digestibility study with Silver foxes weighing 6.5 ± 0.1 kg was conducted to evaluate five fibers (hemicellulose (X), α-cellulose (C), pectin (P), oat bran (B) and oat hulls (H)) added at 5% to a meat-type diet (A). Apparent digestibility of dry matter in diet P (65.1%) was significantly poorer (P < 0.05) than all others except C (69.1%). Addition of all fibers reduced digestibility of acid detergent fiber. Diet P resulted in weight loss, increased water consumption, and faster rate of passage than diet A (P < 0.05). Key words: Digestibility, oat bran, rate of passage, hemicellulose, fiber, fox

scholarly journals A Comparative Study of Ensemble Classifiers for Paddy Blast Disease Prediction Model

2020 ◽  
Vol 8 (7) ◽  
pp. 09-17
Author(s):  
Varsha M., Dr. Poornima B.
Keyword(s):  
Prediction Model ◽  
Minimum Temperature ◽  
Blast Disease ◽  
Weather Data ◽  
Maximum Temperature ◽  
Research Station ◽  
Disease Prediction ◽  
Features Selection ◽  
Ensemble Classifiers ◽  
Epidemic Disease

Paddy blast has become most epidemic disease in many rice growing countries. Various statistical methods have been used for the prediction of paddy blast but previously used methods failed in predicting diseases with good accuracy. However the need to develop new model that considers both weather factors and non weather  data called blast disease data that influences paddy disease to grow. Given this point we developed ensemble classifier based paddy disease prediction model taking weather data from January 2013 to December 2019 from Agricultural and Horticulture Research Station Kathalgere Davangere District. For the predictive model we collected 7 kinds of weather data and 7 kinds of disease related data that includes Minimum Temperature, Maximum Temperature, Temperautre Difference,Relative Humidity, Stages of Paddy Cultivation, Varities of seeds, Season of cropping and so on. It is observed and analyzed that Minimum Temperature, Humidity and Rainfall has huge correlation with occurrence of disease. Since some of the variables are non numeric to convert them to numeric data one hot encoding approach is followed and to improve efficiency of ensemble classifiers  4 different filter based features selection methods are used such as Pearson’s correlation, Mutual information, ANNOVA F Value, Chi Square. Three different ensemble classifiers are used as predictive models and classifiers are compared it is observed that Bagging ensemble technique has achieved  accuracy of 98% compared to Adaboost of 97% and Voting classifier of 88%. Other classification metrics are used evaluate different classifiers like precision, recall, F1 Score, ROC and precision recall score. Our proposed ensemble classifers for paddy blast disease prediction has achieved high precision and high recall but when the solutions of model are closely looked bagging classifier is better compared to other ensemble classifers that are proposed in predicting paddy blast disease.

MONENSIN, CHLORTETRACYCLINE AND TYLOSIN EFFECTS ON PERFORMANCE AND DIGESTION IN LAMBS FED A GROUND ALFALFA DIET

1989 ◽  
Vol 69 (2) ◽  
pp. 505-508 ◽  
Author(s):  
Z. MIR
Keyword(s):  
Key Words ◽  
Feed Efficiency ◽  
Dry Matter ◽  
Control Diet ◽  
Average Daily Gain ◽  
Neutral Detergent Fiber ◽  
Dry Matter Intake ◽  
Acid Detergent Fiber ◽  
Finishing Diets ◽  
Daily Gain

Supplementing a control diet of ground alfalfa (CON) with monensin (MON), chlortetracycline (CTC) or tylosin (TYL) did not affect (P < 0.05) dry matter intake or average daily gain of market lambs. Feed efficiency with CTC was less than with the unsupplemented control (CON) (6.22 vs. 5.68) (P < 0.05). Mean digestibilities of dry matter, acid detergent fiber and neutral detergent fiber were lower (P < 0.05) with all antibiotic treatments than the CON diet. Relative to CON, nitrogen digestibility was increased with MON (66.3 vs. 70.9%) while that of energy was reduced with TYL (P < 0.05). Rumen ammonia and acetic, propionic and butyric acid concentrations were not influenced by any of the treatments. MON, CTC and TYL were not effective supplements for lambs fed alfalfa finishing diets. Key words: lamb, chlortetracycline, monensin, tylosin, alfalfa hay, digestibility

scholarly journals Simulating the Impact of Climate Change on Growth and Yield of Maize Using CERES-Maize Model under Temperate Kashmir

2019 ◽  
pp. 1-11 ◽  
Author(s):  
Bilal Ahmad Lone ◽  
Shivam Tripathi ◽  
Asma Fayaz ◽  
Purshotam Singh ◽  
Sameera Qayoom ◽  
...  
Keyword(s):  
Climate Variability ◽  
Minimum Temperature ◽  
Maize Yield ◽  
Climate Impact ◽  
Growth And Yield ◽  
Weather Data ◽  
Maximum Temperature ◽  
The Impact ◽  
Global Food ◽  
Process Based Models

Climate variability has been and continues to be, the principal source of fluctuations in global food production in countries of the developing world and is of serious concern. Process-based models use simplified functions to express the interactions between crop growth and the major environmental factors that affect crops (i.e., climate, soils and management), and many have been used in climate impact assessments. Average of 10 years weather data from 1985 to 2010, maximum temperature shows an increasing trend ranges from 18.5 to 20.5°C.This means there is an increase of 2°C within a span of 25 years. Decreasing trend was observed with respect to precipitation was observed with the same data. The magnitude of decrease was from 925 mm to 650 mm of rainfall which is almost decrease of 275 mm of rainfall in 25 years. Future climate for 2011-2090 from A1B scenario extracted from PRECIS run shows that overall maximum and minimum temperature increase by 5.39°C (±1.76) and 5.08°C (±1.37) also precipitation will decrease by 3094.72 mm to 2578.53 (±422.12) The objective of this study was to investigate the effects of climate variability and change on maize growth and yield of Srinagar Kashmir. Two enhanced levels of temperature (maximum and minimum by 2 and 4°C) and CO2 enhanced by 100 ppm & 200 ppm were used in this study with total combinations of 9 with one normal condition.  Elevation of maximum and minimum temperature by 4°C anthesis  and maturity of maize was earlier 14 days with a deviation of 18%  and  26 days with a deviation  of 20% respectively. Increase in temperature by 2 to 4°C alone or in combination with enhanced levels of CO2 by 100 and 200 ppm the growth and yield of maize was drastically declined with an reduction of about 40% in grain yield. Alone enhancement of CO2  at both the levels fails show any significant impact on maize yield.

scholarly journals A Comparative Study of Ensemble Classifiers for Paddy Blast Disease Prediction Model

2020 ◽  
Vol 8 (9) ◽  
pp. 05-13
Author(s):  
Varsha M., Dr. Poornima B.
Keyword(s):  
Prediction Model ◽  
Minimum Temperature ◽  
Blast Disease ◽  
Weather Data ◽  
Maximum Temperature ◽  
Research Station ◽  
Disease Prediction ◽  
Features Selection ◽  
Ensemble Classifiers ◽  
Epidemic Disease

Paddy blast has become most epidemic disease in many rice growing countries. Various statistical methods have been used for the prediction of paddy blast but previously used methods failed in predicting diseases with good accuracy. However the need to develop new model that considers both weather factors and non weather  data called blast disease data that influences paddy disease to grow. Given this point we developed ensemble classifer based paddy disease prediction model taking weather data from January 2013 to December 2019 from Agricultural and Horticulture Research Station Kathalgere Davangere District. For the predictive model we collected 7 kinds of weather data and 7 kinds of disease related data that includes Minimum Temperature, Maximum Temperature, Temperautre Difference,Relative Humidity, Stages of Paddy Cultivation, Varities of seeds, Season of cropping and so on. It is observed and analyzed that Minimum Temperature, Humidity and Rainfall has huge correlation with occurrence of disease. Since some of the variables are non numeric to convert them to numeric data one hot encoding approach is followed and to improve efficiency of ensemble classifiers  4 different filter based features selection methods are used such as Pearson’s correlation, Mutual information, ANNOVA F Value, Chi Square. Three different ensemble classifiers are used as predictive models and classifiers are compared it is observed that Bagging ensemble technique has achieved  accuracy of 98% compared to Adaboost of 97% and Voting classifier of 88%. Other classification metrics are used evaluate different classifiers like precision, recall, F1 Score, ROC and precision recall score. Our proposed ensemble classifers for paddy blast disease prediction has achieved high precision and high recall but when the solutions of model are closely looked bagging classifier is better compared to other ensemble classifers that are proposed in predicting paddy blast disease.

Maize–lablab intercropping is promising in supporting the sustainable intensification of smallholder cropping systems under high climate risk in southern Africa

2019 ◽  
Vol 56 (1) ◽  
pp. 104-117 ◽  
Author(s):  
Edith Rapholo ◽  
Jude J. O. Odhiambo ◽  
William C. D. Nelson ◽  
Reimund P. Rötter ◽  
Kingsley Ayisi ◽  
...  
Keyword(s):  
Soil Water ◽  
Southern Africa ◽  
Minimum Temperature ◽  
Cropping Systems ◽  
Sustainable Intensification ◽  
Climate Risk ◽  
Weather Data ◽  
Maximum Temperature ◽  
Cropping Season ◽  
Maize Yields

AbstractIdentifying options for the sustainable intensification of cropping systems in southern Africa under prevailing high climate risk is needed. With this in mind, we tested an intercropping system that combined the staple crop maize with lablab, a local but underutilised legume. Grain and biomass productivity was determined for four variants (i) sole maize (sole-maize), (ii) sole lablab (sole-lablab), (iii) maize/lablab with both crops sown simultaneously (intercropped-SP) and (iv) maize/lablab with lablab sown 28 days after the maize crop (intercropped-DP). Soil water and weather data were monitored and evaluated. The trial was conducted for two seasons (2015/2016 and 2016/2017) at two sites in the Limpopo Province, South Africa: Univen (847 mm rainfall, 29.2 °C maximum and 18.9 °C minimum temperature average for the cropping season over the years 2008–2017) and Syferkuil (491 mm rainfall, with 27.0 °C maximum and 14.8 °C minimum temperature). Analysis revealed three key results: The treatment with intercropped-SP had significantly lower maize yields (2320 kg ha−1) compared with maize in intercropped-DP (2865 kg ha−1) or sole-maize (2623 kg ha−1). As expected, maize yields in the El Niño affected in season 2015/2016 were on average 1688 kg ha−1 lower than in 2016/2017. Maize yields were significantly lower (957 kg ha−1) at Univen, the warmer site with higher rainfall, than at Syferkuil. In 2015/2016, maximum temperature at Univen exceeded 40 °C around anthesis. Furthermore, soil water was close to the estimated permanent wilting point (PWP) for most of the cropping season, which indicates possible water limitations. In Syferkuil, the soil water was maintained well above PWP. Lablab yields were low, around 500 ha−1, but stable as they were not affected by treatment across season and site. Overall, the study demonstrated that intercropped-DP appears to use available soil water more efficiently than sole maize. Intercropped-DP could therefore be considered as an option for sustainable intensification under high climate risk and resource-limited conditions for smallholders in southern Africa.

Interrelationships among Microbiological, Physicochemical, and Biochemical Properties of Terrincho Cheese, with Emphasis on Biogenic Amines

2004 ◽  
Vol 67 (12) ◽  
pp. 2779-2785 ◽  
Author(s):  
OLIVIA PINHO ◽  
ANA I. E. PINTADO ◽  
ANA M. P. GOMES ◽  
M. MANUELA E. PINTADO ◽  
F. XAVIER MALCATA ◽  
...  
Keyword(s):  
Amino Acids ◽  
Biogenic Amines ◽  
Total Nitrogen ◽  
Free Amino Acids ◽  
Free Amino ◽  
Dry Matter ◽  
Total Content ◽  
Biochemical Properties ◽  
Water Soluble ◽  
Soluble Nitrogen

Changes in the microbiological, physicochemical, and biochemical characteristics of Terrincho cheese as represented by native microflora, pH, water activity, soluble nitrogen fractions, free amino acids, and biogenic amines (e.g., ethylamine, dimethylamine, tryptamine, phenylethylamine, putrescine, cadaverine, histamine, tyramine, cystamine, and spermine) during ripening were monitored. Terrincho is a traditional Portuguese cheese manufactured from raw ewe's milk. The main groups of microorganisms (lactococci, lactobacilli, enterococci, pseudomonads, staphylococci, coliforms, yeasts, and molds) were determined following conventional microbiological procedures. Free amino acids and biogenic amines were determined by reverse-phase high-performance liquid chromatography, following extraction from the cheese matrix and derivatization with dabsyl chloride. The total content of free amino acids ranged from 1,730 mg/kg of dry matter at the beginning of the ripening stage to 5,180 mg/kg of dry matter by day 60 of ripening; such an increase was highly correlated with the increase of water-soluble nitrogen in total nitrogen, 12% trichloroacetic acid–soluble nitrogen in total nitrogen, and 5% phosphotungstic acid–soluble nitrogen in total nitrogen throughout ripening. Histamine was consistently present at very low levels, whereas putrescine, cadaverine, and tryptamine were the dominant biogenic amines and increased in concentration during ripening. Ethylamine, tryptamine, phenylethylamine, and cystamine reached maxima by 30 days of ripening and decreased thereafter. Significant correlations between amino acid precursors and corresponding biogenic amines, as well as between biogenic amines and microbial viable numbers, were observed.

scholarly journals Development of high spatial resolution weather data using daily meteorological observations over Indian region

MAUSAM ◽  
2021 ◽  
Vol 71 (4) ◽  
pp. 605-616
Author(s):  
NAGORI ROHIT ◽  
CHAUDHARI K. N.
Keyword(s):  
Spatial Resolution ◽  
Minimum Temperature ◽  
Spline Interpolation ◽  
Growth Dynamics ◽  
Weather Data ◽  
Maximum Temperature ◽  
Data Sets ◽  
Daily Weather Data ◽  
Quality Checks ◽  
Meteorological Observations

Finer spatial resolution interpolated weather data is essential to enable utilization of satellite-based images in studies related to crop growth dynamics, etc. Satellite data are available daily at 1 × 1 km or at the most within 5 × 5 km grid. To make the weather data timely available at the same spatial scale, the procedure has been developed to generate the spatially interpolated weather data product over India. Daily weather data (minimum & maximum temperature and rainfall) available at point scale on India Meteorology Department web site have been used in this study. A semi-automated user interactive Graphical User Interface (GUI) has been developed which quality checks the temperature data sets by filling the missing data sets as well as providing a platform to correct erroneous data which have been identified using statistical methods taking spatial as well as temporal incompatibility into account. Daily spatially interpolated product is generated in image form using thin plate spline interpolation technique that uses the quality checked weather data as well as elevation information from CARTODEM data in order to account for effect of      elevation on temperature. The validation was performed using “Jack-knife testing method” for three different seasons  i.e., monsoon, summer and winter. The mean absolute errors for decadal averaged products were found to vary within 1.2-1.5 °C for maximum temperature, 1.1-1.7 °C for minimum temperature, 1.0-7.0 mm for rainfall considering all seasons with higher error observed in monsoon for maximum temperature and rainfall and in winter for minimum temperature. It was found that errors were close to 1 °C for stations with elevation less than 550 m whereas in central portion of India, mean absolute errors were found to be less than 1 °C.

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