114 research outputs found
The Efficacy of Four Sunburn Mitigation Strategies and Their Effects on Yield, Fruit Quality, and Economic Performance of Honeycrisp Cv. Apples under Eastern New York (USA) Climatic Conditions
Sunburn is a serious economic problem in practically all apple-growing regions of the world. Losses of apple fruit due to sunburn can range from 10% as high as 50%. Several years ago, this problem started to be a concern in Eastern New York State, especially in the Hudson Valley region with the cultivar ‘Honeycrisp’. The study was conducted in three ‘Honeycrisp’ apple tree orchards in the Hudson Valley region (Southeast, New York State) during the 2015 and 2016 growing seasons. Four sunburn mitigation strategies were tested (evaporative cooling, 20% crystal net, the sunscreen Raynox Plus® and the particle film ScreenDuo®) at a variety of timings throughout each growing season. Yield, sunburn incidence/severity, quality, and economic returns were evaluated. Treatments did not affect horticulture performance and fruit quality, but they did reduce sunburn damage to varying degrees. The greatest sunburn mitigation was achieved with the use of netting, followed by spray applications of Raynox Plus® and ScreenDuo®. Apples with sunburn damage had higher flesh firmness, soluble solids content and titratable acidity. Treatment differences in sunburn mitigation did not result in higher net returns to the grower.info:eu-repo/semantics/acceptedVersio
Long-term agronomical performance and iron chlorosis susceptibility of several Prunus rootstocks grown under loamy and calcareous soil conditions
The objective of this work was to evaluate the agronomic performance (vigor, yield, yield efficiency, number of root suckers), fruit quality (fruit weight, fruit size, flesh firmness, soluble solids content, and titratable acidity), leaf and fruit mineral nutrition (macro and micro elements), leaf chlorophyll concentration and iron chlorosis susceptibility of ‘Big Top’ nectarine cultivar grafted on 20 Prunus rootstocks and grown in loamy and calcareous soil under the hot climate conditions of the Ebro river basin (Spain). After the 10 years of the study (at 11th leaf), statistical analysis showed significant differences among rootstocks for most of the traits evaluated. Based on vigor and cumulative yield, ‘Big Top’ trees from Padac 04-03 rootstock were found to be the most vigorous and productive, followed by Castore, GF-677, Ishtara®, PS and Rootpac® 70. However, the most efficient rootstocks were Controller 5, Adesoto® 101, Rootpac® 40, Krymsk® 1, Ishtara®, Penta, IRTA-1, Polluce, and Padac-150. ‘Big Top’ fruits from Rootpac® 40 had the highest fruit weight and fruit size (>70 mm), with good soluble solids content and titratable acidity, but less firmness than the other ‘Big Top’ fruits. After 3 months with no application of chelate, chlorosis symptoms were visible in most of the trees, with those from Krymsk® 1 and PS showing the highest susceptibility. In contrast, AD-105, Adesoto® 101, Cadaman®, GF-677, Padac-150, Rootpac® 40 and Tetra were the least susceptible rootstocks. Controller 5, IRTA-1, Padac-04.03 and Penta had moderate susceptibility. In conclusion, Rootpac® 40, Ishtara®, IRTA-1 and Padac-150 may represent a good compromise between canopy size control, yield, yield efficiency, fruit size, and susceptibility to iron chlorosis.info:eu-repo/semantics/acceptedVersio
Races potencialment perilloses. Un debat en la societat actual
Treball presentat a l'assignatura de Deontologia i Veterinà ria Legal (21223
Rootstock affects quality and phytochemical composition of 'Big Top' nectarine fruits grown under hot climatic conditions
This study aimed to evaluate the stability of ‘Big Top’ nectarine fruit quality (fruit weight, fruit mineral elements and fruit phytochemical composition such as soluble solids content, titratable acidity, individual sugars, individual organic acids, total ascorbic acid content, total phenolics content, and antioxidant capacity) when grafted on 20 Prunus rootstocks over two consecutive seasons. For most of the evaluated traits, rootstock was the main source of variability, whereas for Mg, malic and citric acids, and glucose most of the variability was observed among years. Similarly, the interaction year × rootstock was not significant for most traits (14 out of 21), hence highlighting that most rootstocks responded in a similar manner to changes in the weather conditions. Thus said, some important micro- and macro-nutrients such as Ca, Mg, Fe, Zn, together with taste- (fructose, glucose and sucrose) or health-related (antioxidant capacity) compounds showed a differential influence of the rootstock depending on the year conditions and thereby suggested that climatic conditions can be a limiting factor in the choice of rootstocks for a given nectarine cultivar. Overall, the results from this study indicated that the cherry-plum hybrid Krimsk-1 and the peach-plum hybrid PS rootstocks are the most suitable rootstocks for ‘Big Top’ under the conditions investigated herein. Both rootstocks induced high values on sugar profile, ascorbic acid, antioxidant activity, and TPC of ‘Big Top’ nectarine being relatively stable regardless of the weather conditions. Finally, the rootstocks IRTA-1 and Rootpac-20 also induced good fruit quality and phytochemical properties to ‘Big Top’ fruit.info:eu-repo/semantics/acceptedVersio
Deadline constrained prediction of job resource requirements to manage high-level SLAs for SaaS cloud providers
For a non IT expert to use services in the Cloud is more natural to negotiate the QoS with the provider in terms of service-level metrics –e.g. job deadlines– instead of resourcelevel metrics –e.g. CPU MHz. However, current infrastructures only support resource-level metrics –e.g. CPU share and memory allocation– and there is not a well-known mechanism to translate
from service-level metrics to resource-level metrics. Moreover, the lack of precise information regarding the requirements of
the services leads to an inefficient resource allocation –usually, providers allocate whole resources to prevent SLA violations. According to this, we propose a novel mechanism to overcome this translation problem using an online prediction system which includes a fast analytical predictor and an adaptive machine learning based predictor. We also show how a deadline scheduler could use these predictions to help providers to make the most of their resources. Our evaluation shows: i) that fast algorithms are able to make predictions with an 11% and 17% of relative error for the CPU and memory respectively; ii) the potential of using accurate predictions in the scheduling compared to simple yet well-known schedulers.Preprin
Prediction of job resource requirements for deadline schedulers to manage high-level SLAs on the cloud
Abstract-For a non IT expert to use services in the Cloud is more natural to negotiate the QoS with the provider in terms of service-level metrics -e.g. job deadlines-instead of resourcelevel metrics -e.g. CPU MHz. However, current infrastructures only support resource-level metrics -e.g. CPU share and memory allocation-and there is not a well-known mechanism to translate from service-level metrics to resource-level metrics. Moreover, the lack of precise information regarding the requirements of the services leads to an inefficient resource allocation -usually, providers allocate whole resources to prevent SLA violations. According to this, we propose a novel mechanism to overcome this translation problem using an online prediction system which includes a fast analytical predictor and an adaptive machine learning based predictor. We also show how a deadline scheduler could use these predictions to help providers to make the most of their resources. Our evaluation shows: i) that fast algorithms are able to make predictions with an 11% and 17% of relative error for the CPU and memory respectively; ii) the potential of using accurate predictions in the scheduling compared to simple yet well-known schedulers
Physiological and Agronomical Responses of ‘Vairo’ Almond and ‘Big Top’ Nectarine Cultivars Grafted onto Different Prunus Rootstocks and Grown under Semiarid Mediterranean Conditions
Two trials were conducted under Mediterranean conditions to monitor several physiological indicators before harvest (leaf chlorophyll concentration, quantum yield of photosystem II
electron transport, stem water potential, and stomatal conductance) and some agronomic performance parameters before and at harvest (vigor, fruit growth, fruit size, fruit weight, and yield), of
‘Vairo’ almond and ‘Big Top’ nectarine cultivars grafted onto eight Prunus rootstocks, six of which
are common in both cultivars. For both ‘Vairo’ almond and ‘Big Top’ nectarine cultivars, factors
including rootstock, date, and the interaction between rootstock and date, from fruit set to harvest
were evaluated. Significantly affected were certain physiological and agronomical traits which were
evaluated before harvest, with stem water potential being the parameter affected by interaction in
both cultivars. In fact, the stem water potential presented low levels in Rootpac-20 and high levels
in Rootpac-40 for both cultivars. With regard to the other physiological traits evaluated during the
growing period, changes in stomatal conductance were observed in ‘Vairo’, but not in ‘Big Top’.
Comparing rootstocks throughout the season, Rootpac-40 and IRTA-1 exhibited the highest stomatal
conductance values, whereas the lowest was observed in Rootpac-R; Rootpac-20 and Ishtara also
presented low values. Regarding agronomical traits at harvest, GF-677 and IRTA-1 produced high
yields for ‘Vairo’ almond cultivar, whereas Rootpac-40 and Ishtara performed better with ‘Big Top’
nectarine cultivar.info:eu-repo/semantics/publishedVersio
Inheritance of Fruit Red-Flesh Patterns in Peach
Fruit color is an important trait in peach from the point of view of consumer preference, nutritional content, and diversification of fruit typologies. Several genes and phenotypes have been described for peach flesh and skin color, and although peach color knowledge has increased in the last few years, some fruit color patterns observed in peach breeding programs have not been carefully described. In this work, we first describe some peach mesocarp color patterns that have not yet been described in a collection of commercial peach cultivars, and we also study the genetic inheritance of the red dots present in the flesh (RDF) and red color around the stone (CAS) in several intra- and interspecific segregating populations for both traits. For RDF, we identified a QTL at the beginning of G5 in two intraspecific populations, and for CAS we identified a major QTL in G4 in both an intraspecific and an interspecific population between almond and peach. Finally, we discuss the interaction between these QTLs and some other genes previously identified in peach, such as dominant blood flesh (DBF), color around the stone (Cs), subacid (D) and the maturity date (MD), and the implications for peach breeding. The results obtained here will help peach germplasm curators and breeders to better characterize their plant materials and to develop an integrated system of molecular markers to select these traits.info:eu-repo/semantics/publishedVersio
Inheritance of Fruit Red-Flesh Patterns in Peach
Fruit color is an important trait in peach from the point of view of consumer preference, nutritional content, and diversification of fruit typologies. Several genes and phenotypes have been described for peach flesh and skin color, and although peach color knowledge has increased in the last few years, some fruit color patterns observed in peach breeding programs have not been carefully described. In this work, we first describe some peach mesocarp color patterns that have not yet been described in a collection of commercial peach cultivars, and we also study the genetic inheritance of the red dots present in the flesh (RDF) and red color around the stone (CAS) in several intra- and interspecific segregating populations for both traits. For RDF, we identified a QTL at the beginning of G5 in two intraspecific populations, and for CAS we identified a major QTL in G4 in both an intraspecific and an interspecific population between almond and peach. Finally, we discuss the interaction between these QTLs and some other genes previously identified in peach, such as dominant blood flesh (DBF), color around the stone (Cs), subacid (D) and the maturity date (MD), and the implications for peach breeding. The results obtained here will help peach germplasm curators and breeders to better characterize their plant materials and to develop an integrated system of molecular markers to select these traits
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