scholarly journals Growth characters and harvest time for the artificial cultivation of Mycoleptodonoides aitchisonii

2015 ◽  
Vol 13 (2) ◽  
pp. 114-118
Author(s):  
Young Kim ◽  
Bo-Mi Jung ◽  
An-Jin Wi ◽  
Whoa-Shig Park ◽  
Mi-Ae Bang ◽  
...  
Keyword(s):  
Harvest Time ◽  
Mycoleptodonoides Aitchisonii ◽  
Growth Characters ◽  
Artificial Cultivation

ANALYSIS OF PLANT FRAGARIA XANANASSA DISEASE DIAGNOSES USING PRODUCTION RULES BASE ON EXPERT SYSTEM

2020 ◽  
Vol 16 (1) ◽  
pp. 25-32
Author(s):  
Basiroh Basiroh ◽  
Wiji Lestari
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
General Public ◽  
Insect Pests ◽  
Fruit Rot ◽  
Proper Treatment ◽  
Harvest Time ◽  
Production Rules

Errors that occur in solving problems in strawberry plants (Fragaria Xananassa) such as the presence of leaf patches, fruit rot, perforated leaves, and insect pests can be the cause of not maximum in harvest time. The farmers and the general public who planted strawberry (Fragaria Xananassa) need to know the proper treatment of diseases and pests so that future yields as expected. Therefore, it takes an application as a solution in the delivery of information related to the problems that are often encountered in strawberry plants (Fragaria Xananassa). Methods of production rules can be used to diagnose the disease strawberry (Fragaria Xananassa) based on signs or symptoms that occur in the parts of plants and strawberry, the results of diagnosis using this method are the same as we do Consultation on experts.  The purpose of this study was to determine the early diagnosis of disease in strawberry plants (Fragaria Xananassa) based on signs or symptoms that occur in the plant and fruit parts. The results of the analysis of this study showed that the validation of disease and symptom data in strawberry plants (Fragaria Xananassa) reached 99%, meaning that between the data of symptoms and disease understudy the accuracy was guaranteed with the experts.

Quality of Carrots Grown for Processing as Affected by Nitrogen Fertilization and Harvest Term

2009 ◽  
Vol 70 (1) ◽  
pp. 135-144 ◽  
Author(s):  
Marek Gajewski ◽  
Zenon Węglarz ◽  
Anna Sereda ◽  
Marta Bajer ◽  
Agnieszka Kuczkowska ◽  
...  
Keyword(s):  
Nitrogen Fertilization ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Carrot Juice ◽  
Harvest Time ◽  
Experimental Station ◽  
Colour Parameters ◽  
Solids Content ◽  
Nitrates Content

Quality of Carrots Grown for Processing as Affected by Nitrogen Fertilization and Harvest TermIn 2007-2008 the effect of nitrogen fertilization and harvest term on quality of two carrot cultivars was investigated. The field experiment was carried out in Żelazna Experimental Station of Warsaw University of Life Sciences. Karotan F1and Trafford F1cultivars, commonly grown for juice industry, were the objects of the experiment. Carrot seeds were sown at the beginning of May. Nitrogen fertilization was applied in five rates, ranged from 0 to 120 kg·ha-1and in two terms — before sowing and in the middle of growing season. Roots were harvested in three terms: mid-September, mid-October and the first decade of November. After harvest there were determined: nitrates (NO3) content in carrot roots and juice, soluble solids, colour parameters of juice in CIE L*a*b*system. The dose and the term of nitrogen fertilization influenced nitrates content in carrots, and the highest NO3concentration was found in carrots fertilized with 120 kg·ha-1of N before sowing. Karotan showed higher nitrates accumulation than Trafford. The content of nitrates in the roots was markedly higher than in carrot juice. Nitrates content in carrots decreased with delaying of harvest time, in opposite to soluble solids content. Soluble solids content and colour parameters of carrot juice were not affected by nitrogen fertilization, but the lowest L*, a*and b*values were observed at the last term of harvest.

scholarly journals Effects of agronomic factors on yield and quality of whole corn plants and the impact of feeding high concentrations of corn silage in diets containing distillers grains to finishing cattle1

2017 ◽  
Vol 1 (3) ◽  
pp. 367-381 ◽  
Author(s):  
D. B. Burken ◽  
B. L. Nuttelman ◽  
J. L. Gramkow ◽  
A. L. McGee ◽  
K. M. Sudbeck ◽  
...  
Keyword(s):  
Corn Silage ◽  
Distillers Grains ◽  
Net Energy ◽  
Harvest Time ◽  
Marbling Score ◽  
Finishing Diets ◽  
Plant Yields ◽  
Corn Plants ◽  
The Impact ◽  
Corn Grain

Abstract Corn plants were sampled over 2 consecutive years to assess the effects of corn hybrid maturity class, plant population, and harvest time on whole corn plant quality and yield in Nebraska. A finishing experiment evaluated the substitution of corn with corn silage in diets with corn modified distillers grains with solubles (MDGS). The first 2 harvest dates were at the mid- and late-silage harvest times whereas the final harvest was at the grain harvest stage of plant maturity. Whole plant yields increased as harvest time progressed (yr 1 quadratic P < 0.01; yr 2 linear P < 0.01). However, differences in TDN concentration in both years were quite minimal across harvest time, because grain percentage increased but residue NDF in-situ disappearance decreased as harvest time was delayed. In the finishing experiment, as corn silage inclusion increased from 15 to 55% (DM basis) by replacing dry rolled and high moisture corn grain with corn silage in diets containing 40% MDGS, DMI, ADG, and G:F linearly decreased (P ≤ 0.01), with the steers on the 15% corn silage treatment being 1.5%, 5.0%, and 7.7% more efficient than steers on treatments containing 30, 45, and 55% corn silage, respectively. Calculated dietary NEm and NEg decreased linearly as corn silage inclusion increased indicating that net energy values were greater for corn grain than for corn silage. In addition, dressing percentage decreased linearly (P < 0.01) as silage inclusion increased suggesting more fill as silage inclusion increases in diets. Cattle fed greater than 15% corn silage in finishing diets based on corn grain will gain slower and be slightly less efficient and likely require increased days to market at similar carcass fatness and size. When 30% silage was fed with 65% MDGS, DMI, and ADG were decreased (P < 0.01) compared to feeding 30% silage with 40% MDGS suggesting some benefit to including a proportion of corn in the diet. Conversely, when 45% silage was fed with 40% MDGS, ADG, and G:F were greater (P < 0.04) than when 45% silage was fed with just grain implying a greater energy value for MDGS than for corn grain. Substituting corn silage for corn grain in finishing diets decreased ADG and G:F which would increase days to finish to an equal carcass weight; however, in this experiment, increasing corn silage levels with MDGS present reduced carcass fat thickness without significantly decreasing marbling score.

scholarly journals Impact of Foliar Application of Various Forms of Silicon on the Chemical Composition of Sugar Beet Plants

Sugar Tech ◽  
2021 ◽  
Author(s):  
Arkadiusz Artyszak ◽  
Małgorzata Kondracka ◽  
Dariusz Gozdowski ◽  
Alicja Siuda ◽  
Magda Litwińczuk-Bis
Keyword(s):  
Chemical Composition ◽  
Sugar Beet ◽  
Foliar Application ◽  
Foliar Spray ◽  
Water Shortage ◽  
Sugar Yield ◽  
Orthosilicic Acid ◽  
Harvest Time ◽  
Polysilicic Acid ◽  
Critical Phase

AbstractThe effect of marine calcite, a mixture of ortho- and polysilicic acid as well as orthosilicic acid applied as a foliar spray on the chemical composition of sugar beet leaves in the critical phase of nutrient supply (beginning of July) but also leaves and roots during harvest time in 2015–2016, was studied. The content of silicon in the leaves ranged from 1.24 to 2.36 g kg−1 d.m. at the beginning of July, 3.85–5.34 g kg−1 d.m. during harvest and 2.91–4.20 g kg−1 d.m. in the roots. The foliar application of silicon caused a significant increase in the content of magnesium and calcium in leaves (in July) as compared to the control. The sugar beet consumes approx. 75 kg Si ha−1, which is almost 3.5 times more than P and 20% more than Mg thus proving its importance for its species. About 70% of the silicon taken up by sugar beet is stored in roots and 30% in leaves. The pure sugar yield is most favorably influenced by two- and threefold foliar application of the product containing silicon in the form of orthosilicic acid stabilized with choline, and a threefold mixture of ortho- and polysilicic acid. The increase in the pure sugar yield is not the result of a change in the chemical composition of sugar beet plants, but their more efficient functioning after foliar application of silicon under stress conditions caused by water shortage.

Predicted harvest time effects on switchgrass moisture content, nutrient concentration, yield, and profitability

2018 ◽  
Vol 108 ◽  
pp. 74-89 ◽  
Author(s):  
Karen R. Lindsay ◽  
Michael P. Popp ◽  
Charles P. West ◽  
Amanda J. Ashworth ◽  
Alexandre Caldeira Rocateli ◽  
...  
Keyword(s):  
Moisture Content ◽  
Nutrient Concentration ◽  
Harvest Time ◽  
Time Effects

scholarly journals A Machine Vision Rapid Method to Determine the Ripeness Degree of Olive Lots

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2940
Author(s):  
Luciano Ortenzi ◽  
Simone Figorilli ◽  
Corrado Costa ◽  
Federico Pallottino ◽  
Simona Violino ◽  
...  
Keyword(s):  
Machine Vision ◽  
Nearest Neighbors ◽  
Calibration Method ◽  
Mobile App ◽  
Harvest Time ◽  
Automatic Assessment ◽  
K Nearest Neighbors ◽  
Olive Ripeness ◽  
Olive Ripening

The degree of olive maturation is a very important factor to consider at harvest time, as it influences the organoleptic quality of the final product, for both oil and table use. The Jaén index, evaluated by measuring the average coloring of olive fruits (peel and pulp), is currently considered to be one of the most indicative methods to determine the olive ripening stage, but it is a slow assay and its results are not objective. The aim of this work is to identify the ripeness degree of olive lots through a real-time, repeatable, and objective machine vision method, which uses RGB image analysis based on a k-nearest neighbors classification algorithm. To overcome different lighting scenarios, pictures were subjected to an automatic colorimetric calibration method—an advanced 3D algorithm using known values. To check the performance of the automatic machine vision method, a comparison was made with two visual operator image evaluations. For 10 images, the number of black, green, and purple olives was also visually evaluated by these two operators. The accuracy of the method was 60%. The system could be easily implemented in a specific mobile app developed for the automatic assessment of olive ripeness directly in the field, for advanced georeferenced data analysis.

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