Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Organic and inorganic sources of zinc, copper and selenium in diets for dairy cows: intake, blood metabolic profile, milk yield and composition

The present study was carried out with the objective of evaluating the effects of feeding dairy cows with organic or inorganic sources of zinc (Zn), copper (Cu) and selenium (Se) on blood concentrations of these minerals, blood metabolic profiles, nutrient intake and milk yield and composition. Nineteen Holstein cows were selected and randomly assigned to two groups for receiving organic (n = 9) or inorganic (n = 10) sources of Zn, Cu and Se from 60 days before the expected date of calving to 80 days of lactation. Samples of feed, orts and milk were collected for analysis. Body condition score (BCS) was determined and blood samples were collected for analysis of Zn, Cu and Se concentrations, as well as for metabolic profile. Supplying organic or inorganic sources of Zn, Cu, and Se did not affect dry matter and nutrient intake, blood metabolic profile, milk yield and composition, plasma concentration of these minerals, and BCS or change the BCS in cows from 60 days before the expected date of calving to 80 days of lactation. An effect of time was observed on all feed intake variables, plasma concentrations of Zn and Se, milk yield, milk protein content, BCS and change in BCS.

Spatio-temporal variability of sugarcane yield efficiency in the state of São Paulo, Brazil

The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of São Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of São Paulo.

Yield mapping, soil fertility and tree gaps in an orange orchard

The current high competition on Citrus industry demands from growers new management technologies for superior efficiency and sustainability. In this context, precision agriculture (PA) has developed techniques based on yield mapping and management systems that recognize field spatial variability, which contribute to increase profitability of commercial crops. Because spatial variability is often not perceived the orange orchards are still managed as uniform and adoption of PA technology on citrus farms is low. Thus, the objective of the present study was to characterize the spatial variability of three factors: fruit yield, soil fertility and occurrence of plant gaps caused by either citrus blight or huanglongbing (HLB) in a commercial Valencia orchard in Brotas, São Paulo State, Brazil. Data from volume, geographic coordinates and representative area of the bags used on harvest were recorded to generate yield points that were then interpolated to produce the yield map. Soil chemical characteristics were studied by analyzing samples collected along planting rows and inter-rows in 24 points distributed in the field. A map of density of tree gaps was produced by georeferencing individual gaps and later by counting the number of gaps within 500 m² cells. Data were submitted to statistical and geostatistical analyses. A t test was used to compare means of soil chemical characteristics between sampling regions. High variation on yield and density of tree gaps was observed from the maps. It was also demonstrated overlapping regions of high density of plant absence and low fruit yield. Soil fertility varied depending on the sampling region in the orchard. The spatial variability found on yield, soil fertility and on disease occurrence demonstrated the importance to adopt site specific nutrient management and disease control as tools to guarantee efficiency of fruit production.

Correlations between yield and fruit quality characteristics of fresh market tomatoes

Genotypic, phenotypic and environmental correlations were estimated for all possible pairs among eleven characters of tomatoes. Fifteen treatments including five parents and ten hybrids of Instituto Agronômico (IAC) tomato breeding program were evaluated using a randomized complete block experimental design, with tree replications in Itatiba, São Paulo state, Brazil, during 2005/2006. The following traits were evaluated: fruit yield per plant (FP), fruit number per plant (FN), average fruit weight (FW), cluster number per plant (CN), fruit number per cluster (FC), number of locules per fruit (NL), fruit length (FL), fruit width (WI), fruit wall thickness (FT), total soluble solids (SS), and total titratable acidity (TA). The genotypic (rG), phenotypic (rF) and environmental correlations (rA) for two pairs of plant traits were estimated using the Genes© program. High similarity was found among the estimates of genotypic and phenotypic correlations. Positive and high phenotypic and genotypic correlations were observed between FP and the traits FN, FW and FT, and these associations contributed for yield increasing. FW and FT contributed to yield increase and should be considered together as primary yield components in tomato. Positive values of the genotypic and phenotypic correlations revealed that FP influenced FN with high direct effect and significant positive correlation. These traits may be included as the main selection criteria for tomato yield improvement.

Phosphite as phosphorus source to grain yield of common bean plants grown in soils under low or adequate phosphate availability

The effects of foliar and soil applied phosphite on grain yield in common bean (Phaseolus vulgaris L.) grown in a weathered soil under low and adequate phosphate availability were evaluated. In the first experiment, treatments were composed of a 2 x 7 + 2 factorial scheme, with 2 soil P levels supplied as phosphate (40 e 200 mg P dm-3 soil), 7 soil P levels supplied as phosphite (0-100 mg P dm-3 soil), and 2 additional treatments (without P supply in soil, and all P supplied as phosphite). In the second experiment, treatments were composed of a 2 x 3 x 2 factorial scheme, with 2 soil phosphate levels (40 e 200 mg P dm-3 soil), combined with 3 nutrient sources applied via foliar sprays (potassium phosphite, potassium phosphate, and potassium chloride as a control), and 2 foliar application numbers (single and two application). Additional treatments showed that phosphite is not P source for common bean nutrition. Phosphite supply in soil increased the P content in shoot (at full physiological maturity stage) and grains, but at the same time considerably decreased grain yield, regardless of the soil phosphate availability. Foliar sprays of phosphite decreased grain yield in plants grown under low soil phosphate availability, but no effect was observed in plants grown under adequate soil phosphate availability. In general, foliar sprays of phosphate did not satisfactorily improve grain yield of the common bean plants grown under low soil phosphate availability.

Assessment of cumulative damage by using ultrasonic C-scan on carbon fiber/epoxy composites under thermal cycling

In recent years, structural composites manufactured by carbon fiber/epoxy laminates have been employed in large scale in aircraft industries. These structures require high strength under severe temperature changes of -56° until 80 °C. Regarding this scenario, the aim of this research was to reproduce thermal stress in the laminate plate developed by temperature changes and tracking possible cumulative damages on the laminate using ultrasonic C-scan inspection. The evaluation was based on attenuation signals and the C-scan map of the composite plate. The carbon fiber/epoxy plain weave laminate underwent temperatures of -60° to 80 °C, kept during 10 minutes and repeated for 1000, 2000, 3000 and 4000 times. After 1000 cycles, the specimens were inspected by C-scanning. A few changes in the laminate were observed using the inspection methodology only in specimens cycled 3000 times, or so. According to the found results, the used temperature range did not present enough conditions to cumulative damage in this type of laminate, which is in agreement with the macro - and micromechanical theory.

Modified crop model estimation of depleted and potential soybean yield

Despite the great importance of soybeans in Brazil, there have been few applications of soybean crop modeling on Brazilian conditions. Thus, the objective of this study was to use modified crop models to estimate the depleted and potential soybean crop yield in Brazil. The climatic variable data used in the modified simulation of the soybean crop models were temperature, insolation and rainfall. The data set was taken from 33 counties (28 Sao Paulo state counties, and 5 counties from other states that neighbor São Paulo). Among the models, modifications in the estimation of the leaf area of the soybean crop, which includes corrections for the temperature, shading, senescence, CO2, and biomass partition were proposed; also, the methods of input for the model's simulation of the climatic variables were reconsidered. The depleted yields were estimated through a water balance, from which the depletion coefficient was estimated. It can be concluded that the adaptation soybean growth crop model might be used to predict the results of the depleted and potential yield of soybeans, and it can also be used to indicate better locations and periods of tillage.

Epistatic effects on grain yield of soybean [Glycine max (L.) Merrill]

Studies addressing the estimation of genetic parameters in soybean have not emphasized the epistatic effects. The purpose of this study was to estimate the significance of these effects on soybean grain yield, based on the Modified Triple Test Cross design. Thirty-two inbred lines derived from a cross between two contrasting lines were used, which were crossed with two testers (L1 and L2). The experiments were carried out at two locations, in 10 x 10 triple lattice designs with 9 replications, containing 32 lines (Pi ), 64 crosses (32 Pi x L1 and 32 Pi x L2 ) and controls. The variation between ( ͞L1i + ͞L2i - ͞Pi ) revealed the presence of epistasis, as well as an interaction of epistasis x environment. Since the predominant component of epistasis in autogamous species is additive x additive (i type), we suggest postponing the selection for grain yield to later generations of inbreeding in order to exploit the beneficial effects of additive x additive epistasis.

Fine Mapping of qroot-yield-1.06, a QTL for Root, Plant Vigor and Yield in Maize

Root-yield-1.06 is a major QTL affecting root system architecture (RSA) and other agronomic traits in maize. The effect of this QTL has been evaluated with the development of near isogenic lines (NILs) differing at the QTL position. The objective of this study was to fine map qroot-yield-1.06 by marker-assisted searching for chromosome recombinants in the QTL interval and concurrent root phenotyping in both controlled and field conditions, through successive generations. Complementary approaches such as QTL meta-analysis and RNA-seq were deployed in order to help prioritizing candidate genes within the QTL target region. Using a selected group of genotypes, field based root analysis by ‘shovelomics’ enabled to accurately collect RSA information of adult maize plants. Shovelomics combined with software-assisted root imaging analysis proved to be an informative and relatively highly automated phenotyping protocol. A QTL interval mapping was conducted using a segregating population at the seedling stage grown in controlled environment. Results enabled to narrow down the QTL interval and to identify new polymorphic markers for MAS in field experiments. A collection of homozygous recombinant NILs was developed by screening segregating populations with markers flanking qroot-yield-1.06. A first set of lines from this collection was phenotyped based on the adapted shovelomics protocol. QTL analysis based on these data highlighted an interval of 1.3 Mb as completely linked with the target QTL but, a larger safer interval of 4.1 Mb was selected for further investigations. QTL meta-analysis allows to synthetize information on root QTLs and two mQTLs were identified in the qroot-yield-1.06 interval. Trascriptomics analysis based on RNA-seq data of the two contrasting QTL-NILs, confirmed alternative haplotypes at chromosome bin 1.06. qroot-yield-1.06 has now been delimited to a 4.1-Mb interval, and thanks to the availability of additional untested homozygous recombinant NILs, the potentially achievable mapping resolution at qroot-yield-1.06 is c. 50 kb.

Analysis of cumulative effects of multiple stressors on saltmarshes and consideration of management options

Natural systems face pressures exerted by natural physical-chemical forcings and a myriad of co-occurring human stressors that may interact to cause larger than expected effects, thereby presenting a challenge to ecosystem management. This thesis aimed to develop new information that can contribute to reduce the existing knowledge gaps hampering the holistic management of multiple stressors. I undertook a review of the state-of-the-art methods to detect, quantify and predict stressor interactions, identifying techniques that could be applied in this thesis research. Then, I conducted a systematic review of saltmarsh multiple stressor studies in conjunction with a multiple stressor mapping exercise for the study system in order to infer potential important synergistic stressor interactions. This analysis identified key stressors that are affecting the study system, but also pointed to data gaps in terms of driver and pressure data and raised issues for potentially overlooked stressors. Using field mesocosms, I explored how a local stressor (nutrient availability) affects the responses of saltmarsh vegetation to a global stressor (increased inundation) in different soil types. Results indicate that saltmarsh vegetation would be more drastically affected by increased inundation in low than in medium organic matter soils, and especially in estuaries already under high nutrient availability. In another field experiment, I examined the challenges of managing co-occurring and potentially interacting local stressors on saltmarsh vegetation: recreational trampling and smothering by deposition of excess macroalgal wrack due to high nutrient loads. Trampling and wrack prevention had interacting effects, causing non-linear responses of the vegetation to simulated management of these stressors, such that vegetation recovered only in those treatments simulating the combined prevention of both stressors. During this research I detected, using molecular genetic methods, a widespread presence of S. anglica (and to a lesser extent S. townsendii), two previously unrecorded non-native Spartinas in the study areas.

Cyclotron production of 11^C: experimental assessment of saturation yield and validation with Monte Carlo simulation

Nell'ambito della Fisica Medica, le simulazioni Monte Carlo sono uno strumento sempre più diffuso grazie alla potenza di calcolo dei moderni calcolatori, sia nell'ambito diagnostico sia in terapia. Attualmente sono disponibili numerosi pacchetti di simulazione Monte Carlo di carattere "general purpose", tra cui Geant4. Questo lavoro di tesi, svolto presso il Servizio di Fisica Sanitaria del Policlinico "S.Orsola-Malpighi", è basato sulla realizzazione, utilizzando Geant4, di un modello Monte Carlo del target del ciclotrone GE-PETtrace per la produzione di C-11. Nel modello sono stati simulati i principali elementi caratterizzanti il target ed il fascio di protoni accelerato dal ciclotrone. Per la validazione del modello sono stati valutati diversi parametri fisici, tra i quali il range medio dei protoni nell'azoto ad alta pressione e la posizione del picco di Bragg, confrontando i risultati con quelli forniti da SRIM. La resa a saturazione relativa alla produzione di C-11 è stata confrontata sia con i valori forniti dal database della IAEA sia con i dati sperimentali a nostra disposizione. Il modello è stato anche utilizzato per la stima di alcuni parametri di interesse, legati, in particolare, al deterioramento dell'efficienza del target nel corso del tempo. L'inclinazione del target, rispetto alla direzione del fascio di protoni accelerati, è influenzata dal peso del corpo del target stesso e dalla posizione in cui questo é fissato al ciclotrone. Per questo sono stati misurati sia il calo della resa della produzione di C-11, sia la percentuale di energia depositata dal fascio sulla superficie interna del target durante l'irraggiamento, al variare dell'angolo di inclinazione del target. Il modello che abbiamo sviluppato rappresenta, dunque, un importante strumento per la valutazione dei processi che avvengono durante l'irraggiamento, per la stima delle performance del target nel corso del tempo e per lo sviluppo di nuovi modelli di target.