Robotics in horticultural field production

2010 ◽  
Vol 6 (3) ◽  
pp. 1-11 ◽  
Author(s):  
Avital Bechar
Keyword(s):  
Field Production

scholarly journals Bioactive Compounds, Antioxidant Activity and Growth Behavior in Lettuce Cultivars Grown under Field and Greenhouse Conditions

Proceedings ◽  
2020 ◽  
Vol 70 (1) ◽  
pp. 52
Author(s):  
Melisa Lanza Volpe ◽  
Verónica C. Soto Vargas ◽  
Anabel Morón ◽  
Roxana E. González
Keyword(s):  
Antioxidant Activity ◽  
Bioactive Compounds ◽  
Antioxidant Activities ◽  
Growth Conditions ◽  
Growth Behavior ◽  
Total Phenolic ◽  
Spectrophotometric Methods ◽  
Leafy Greens ◽  
Growing Conditions ◽  
Field Production

Lettuce (Lactuca sativa L.) is one of the most important leafy greens worldwide. The nutritional value of its edible leaf depends on different factors including type and growing conditions. The aim was to determine the bioactive compounds content, antioxidant activity and growth behavior of twenty-two lettuce genotypes, cultivated under field and greenhouse conditions. Total phenolic compound, chlorophylls, carotenoids, anthocyanin contents and antioxidant activities were analyzed by spectrophotometric methods. Data were analyzed by analysis of variance (ANOVA). Significant differences between bioactive compounds, antioxidant activity and growth behavior were found among cultivars and morphological types, for both growth conditions. Carotenoid and chlorophyll content was higher in greenhouse conditions for all genotypes. In field production, butterhead and iceberg lettuces showed lower content of these bioactive compounds. The red-pigmented Falbala cultivar from field production showed the highest level of polyphenols and anthocyanin. Meanwhile, in greenhouse conditions, the oak leaf cultivar Grenadine displayed the highest concentration of these phenolic compounds. The iceberg type lettuce showed the lowest percentages of antioxidant activity in both environments. The results showed the effect of growing conditions and the high variability in lettuce bioactive compounds content and antioxidant activity among the different types.

scholarly journals Ensemble Machine Learning Assisted Reservoir Characterization Using Field Production Data–An Offshore Field Case Study

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1052
Author(s):  
Baozhong Wang ◽  
Jyotsna Sharma ◽  
Jianhua Chen ◽  
Patricia Persaud
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Reservoir Characterization ◽  
Time Lapse ◽  
Production Data ◽  
Oil Saturation ◽  
Ensemble Machine Learning ◽  
Input Parameters ◽  
Saturation Profiles ◽  
Field Production

Estimation of fluid saturation is an important step in dynamic reservoir characterization. Machine learning techniques have been increasingly used in recent years for reservoir saturation prediction workflows. However, most of these studies require input parameters derived from cores, petrophysical logs, or seismic data, which may not always be readily available. Additionally, very few studies incorporate the production data, which is an important reflection of the dynamic reservoir properties and also typically the most frequently and reliably measured quantity throughout the life of a field. In this research, the random forest ensemble machine learning algorithm is implemented that uses the field-wide production and injection data (both measured at the surface) as the only input parameters to predict the time-lapse oil saturation profiles at well locations. The algorithm is optimized using feature selection based on feature importance score and Pearson correlation coefficient, in combination with geophysical domain-knowledge. The workflow is demonstrated using the actual field data from a structurally complex, heterogeneous, and heavily faulted offshore reservoir. The random forest model captures the trends from three and a half years of historical field production, injection, and simulated saturation data to predict future time-lapse oil saturation profiles at four deviated well locations with over 90% R-square, less than 6% Root Mean Square Error, and less than 7% Mean Absolute Percentage Error, in each case.

scholarly journals Analysis of Critical Control Points of Post-Harvest Diseases in the Material Flow of Nam Dok Mai Mango Exported to Japan

Agriculture ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 200
Author(s):  
Matulaprungsan ◽  
Wongs-Aree ◽  
Penchaiya ◽  
Boonyaritthongchai ◽  
Srisurapanon ◽  
...  
Keyword(s):  
Material Flow ◽  
Hot Water ◽  
Control Points ◽  
Ripe Fruit ◽  
Post Harvest ◽  
Critical Control Points ◽  
Cultivar Selection ◽  
Fruit Decay ◽  
Processing Line ◽  
Field Production

‘Nam Dok Mai’ mango is a luxury commercial fruit in Thailand, but post-harvest diseases infecting the ripe fruit is a major problem affecting marketability. The objective of the present study was to map the supply chain of ‘Nam Dok Mai’ mangoes exported to Japan and analyze the critical points of post-harvest disease infection caused mainly by Colletotrichum gloeosporioides. Risk points of the post-harvest diseases were found by examining the material and information flows from processes ranging from field production to post-harvest handling, and these were obtained from mango growers and an exporter. The findings of interviews with mango growers and observations of the mangoes in field production were that the first point of risk was cultivar selection, while branch pruning and fruit bagging were further important processes causing post-harvest fruit decay. On the other hand, it was found that post-harvest handling was significant in decreasing anthracnose disease infection; this was seen at the step of dipping the fruit in 50 °C hot water for 3 min at the processing line.

scholarly journals Bulb and vegetative characteristics of garlic (Allium sativum L.) from in vitro culture through acclimatization and field production

2012 ◽  
Vol 7 (43) ◽  
pp. 5792-5795 ◽  
Author(s):  
I Metwally E ◽  
E El Denary M ◽  
M K Omar A ◽  
Naidoo Y ◽  
H Dewir Y
Keyword(s):  
In Vitro Culture ◽  
Allium Sativum ◽  
Field Production

scholarly journals Comparison Strawberry Field Production and Occurrence of Grey Mould at Strawberry Growing on System with Addition of Apple Tree Woody Chips

2017 ◽  
Vol 65 (4) ◽  
pp. 1253-1264
Author(s):  
David Novotný ◽  
Jana Brožová ◽  
Pavla Růžičková ◽  
Josef Sus ◽  
Martin Koudela ◽  
...  
Keyword(s):  
Botrytis Cinerea ◽  
Apple Tree ◽  
Grey Mould ◽  
Fruit Weight ◽  
Wood Chips ◽  
Average Weight ◽  
Tree Wood ◽  
Significant Difference ◽  
And Control ◽  
Field Production

In the years 2014 to 2016 the influence of apple tree wood chips and composted apple tree wood chips in which oyster mushroom grew and yielded which were supplemented into soil on strawberry field production and occurrence of grey mould at strawberry (cv. ‘Sonata’) was evaluated. Average weight and number of fruits per plant, average fruit weight, average weight and number of fruits affected by Botrytis cinerea per plant, percentage of weight and number of fruits affected by Botrytis cinerea was calculated. There were recorded differences concerning strawberry yield among the investigated variants of plots, but mainly there were not statistically significant. In 2015 and 2016 the highest average weight of yield and the highest number of fruits was reached at plants cultivated on plots with apple tree wood chips. Average weight of yield on plots with apple tree wood chips was 663.72 g and 822.41 g in 2015 and 2016, respectively. Number of fruits per plant on plots with apple tree wood chips was 67.88 pieces and 65.29 pieces in 2015 and 2016, respectively. Occurrence of grey mould caused by Botrytis cinerea on all variants of plots was similar and small differences was found out only but statistically significant difference was among the years. Grey mould was the most frequently found out in the year 2016. B. cinerea affected 48.27, 56.89 and 55.94 grams of fruits per plant from plots with composted apple tree wood chips, plots with apple tree wood chips and control plots in 2016, respectively.

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