Prediction of internal bond strength in a medium density fiberboard process using multivariate statistical methods and variable selection

This paper presents new data mining-based multivariate calibration models for predicting internal bond strength from medium density fiberboard (MDF) process variables. It utilizes genetic algorithms (GA) based variable selection combined with several calibration methods. By adopting a proper variable selection scheme, the prediction performance can be improved because of the exclusion of non-informative variable(s). A case study using real plant data showed that the calibration models based on the process variables selected by GA produced better performance than those without variable selection, with the exception of the radial basis function (RBF) neural networks model. In particular, the calibration model based on supervised probabilistic principal component analysis (SPPCA) yielded better performance (only when using GA) than partial least squares (PLS), orthogonal-PLS (O-PLS), and radial basis function neural networks models. The SPPCA model benefits most from the use of GA-based variable selection in this case study. N. André and H.-W. Cho equally contributed to this work.     

Detection of Chalara fraxinea in common ash (Fraxinus excelsior) using real time PCR

A real time PCR assay was developed for the detection of Chalara fraxinea in common ash. PCR primers and Taqman probes, based on the internal transcribed spacer region of the multi‐copy gene rDNA, were tested for specificity and sensitivity. The primers amplified an 81 bp fragment for C. fraxinea but did not amplify DNA from other Chalara species or from other fungi isolated from ash, whether pathogenic or saprophytic. The limit of detection was 5 pg of genomic DNA per PCR. Moreover, naturally‐infected samples were correctly diagnosed. A procedure for DNA extraction from woody tissues using an electric drill yielded DNA of an appropriate quality for real time PCR. This molecular method could be useful for routine analysis of this emergent pathogen and for epidemiological studies.     

Sensitivity of Seeds to Chemical Mutagens,Detection of DNA Polymorphisms and Agro-Metrical Traits in M1 Generation of Coffee (Coffea arabica L.)

Journal of Crop Science and Biotechnology - Coffee (Coffea Arabica L.) is threatened by biotic and abiotic stresses. Nevertheless, the breeding of Arabica coffee is restricted due to its low...     

Unravelling the relationship between a seasonal environment and the dynamics of forage growth in grazed swards

It is well reported in the scientific literature that pastures can have similar net forage accumulation when managed with contrasting structures. However, we hypothesized that the dynamics of forage accumulation in grazed swards is linked to seasonal-environmental conditions. Marandu palisadegrass (Brachiaria brizantha [Hochst. ex A. Rich.] was used as the forage species model. The experimental treatments were four grazing heights (10, 20, 30 and 40 cm) allocated to experimental units according to a randomized complete block design with four replicates and evaluated throughout four contrasting environmental seasons (summer, autumn, winter–early spring and late spring). Under rainy and warm periods, greater net forage accumulation was observed in pastures maintained taller; on the contrary, during the mild and dry periods, net forage accumulation rate reduced as grazing height increased. Such patterns of responses were related to compensations between tiller population density and tissues flows during summer and late spring and the reduced capacity of taller canopies to compensate lower population with greater growth rates during autumn and winter–early spring. Grazed swards changed their patterns of forage growth as they transitioned from favourable to more abiotic stressful conditions, suggesting that seasonal adjustments in grazing intensities are necessary in order to maximize forage production.     

Inheritance of Aluminum Tolerance and its Effects on Grain Yield and Grain Quality in Oats (Avena Sativa L.)

Summary Aluminum toxicity due to the cation Al⁺³ is a major factor limiting yields in acid soils. Wide genetic variability to aluminum tolerance is found in oat genotypes. The objectives of this study were to determine the number of genes controlling aluminum tolerance in oats and to verify if any detrimental effects were present of the aluminum tolerance genes on grain yield and grain quality in Al⁺³free soils. Aluminum tolerance was estimated as the average regrowth of the main root after exposure to toxic levels of Al⁺³ in a hydroponic solution under controlled conditions. The number of genes controlling that trait was estimated from the distribution of the average root regrowth frequencies in a population of 333 recombinant inbred lines (RIL's) in generations F_5:6 and F_5:7. The effects on grain yield and grain quality were assessed in a subpopulation of 162 RIL's chosen based on their aluminum tolerance response. Aluminum tolerance in the evaluated population was controlled by one dominant major gene with the tolerant genotypes carying Al _a Al _a and the sensitive ones al _a al _a alleles. No detrimental effects of the Al _a allele on grain yield or grain quality were detected.Part of the Master of Science dissertation of the first author     

Responses to water withdrawal of tobacco plants genetically engineered with the AtTPS1 gene: a special reference to photosynthetic parameters

We have previously obtained several lines of tobacco transformed with a trehalose-6-phosphate synthase gene of plant origin (Arabidopsis thaliana), involved in the first step of the biosynthesis of trehalose, a known osmoprotectant. Two showed distinct intensity of expression: high (B5H) and low (B1F). Such lines were analyzed for trehalose-6-phosphate content and the obtained results demonstrated to be in accordance with the expression results. In order to study the responses of photosynthesis to water deficit of transgenic lines in comparison to wild type (WT), three experiments were performed under different conditions: (1) Relative water (2) Leaf gas exchange (3) Modulated Chlorophyll a Fluorescence. Different responses in RWC of plant lines to water withdrawal were detected, with transgenic line B5H indicating less water loss after the water withdrawal period. Similar responses to water deficit regarding the leaf gas exchanges were recorded for the three lines. When subjected to water deficit stress situations, higher F _v/F _m, Φ_PSII and qP were detected for the transgenic lines. Under a SWC of 20% where higher values for such parameters were detected with special relevance for the B5H line, indicating a possible higher ability to withstand severe drought stress and to resist to prolonged periods without water than the B1F and WT lines.     

Rubber tree early selection for yield stability in time and among locations

Rubber production in the rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Muell. Arg.] can be expressed differently in different environments. Thus the objective of the present study was to select productive progenies, stable and responsive in time and among locations. Thirty progenies were assessed by early yield tests at three ages and in three locations. A randomized block design was used with three replications and ten plants per plot, in 3 × 3 m spacing. The procedure of the mixed linear Reml/Blup model—restricted maximum likelihood/best non-biased linear prediction was used in the genetic statistical analyses. In all the individual analyses, the values observed for the progeny average heritability ( $ \hat{h}_{pa}^{2} $ ) were greater than those of the additive effect based on single individuals ( $ \hat{h}_{a}^{2} $ ) and within plot additive ( $ \hat{h}_{ad}^{2} $ ). In the joint analyses in time, there was genotype × test interaction in the three locations. When 20 % of the best progenies were selected the predicted genetic gains were: Colina G_G = 24.63 %, Selvíria G_G = 13.63 %, and Votuporanga G_G = 25.39 %. Two progenies were among the best in the analyses in the time and between locations. In the joint analysis among locations there was only genotype × location interaction in the first early test. In this test, selecting 20 %, the general predicted genetic gain was G_G = 25.10 %. Identifying progenies with high and stable yield over time and among locations contributes to the efficiency of the genetic breeding program. The relative performance of the progenies varies depending of the age of early selection test.