Effects of Cocoa-Derived Polyphenols on Cognitive Function in Humans. Systematic Review and Analysis of Methodological Aspects

Plant Foods for Human Nutrition - The effects of cocoa-derived polyphenols on cognitive functions have been analyzed through numerous studies using different interventions (doses, vehicles, time...     

Exploiting chemical ecology to manage hyperparasitoids in biological control of arthropod pests

Insect hyperparasitoids are fourth trophic level organisms that commonly occur in terrestrial food webs, yet they are relatively understudied. These top‐carnivores can disrupt biological pest control by suppressing the populations of their parasitoid hosts, leading to pest outbreaks, especially in confined environments such as greenhouses where augmentative biological control is used. There is no effective eco‐friendly strategy that can be used to control hyperparasitoids. Recent advances in the chemical ecology of hyperparasitoid foraging behavior have opened opportunities for manipulating these top‐carnivores in such a way that biological pest control becomes more efficient. We propose various infochemical‐based strategies to manage hyperparasitoids. We suggest that a push‐pull strategy could be a promising approach to ‘push’ hyperparasitoids away from their parasitoid hosts and ‘pull’ them into traps. Additionally, we discuss how infochemicals can be used to develop innovative tools improving biological pest control (i) to restrict accessibility of resources (e.g. sugars and alternative hosts) to primary parasitoid only or (ii) to monitor hyperparasitoid presence in the crop for early detection. We also identify important missing information in order to control hyperparasitoids and outline what research is needed to reach this goal. Testing the efficacy of synthetic infochemicals in confined environments is a crucial step towards the implementation of chemical ecology‐based approaches targeting hyperparasitoids. © 2019 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R2 adj), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.     

Strategy to identify resistance to white mould associated with high yield for irrigated common bean in Brazil

Development of common bean cultivars with partial white mould resistance through breeding techniques has been a challenge in Brazil. As yet, lines/cultivars from breeding programmes have not been investigated for resistance; therefore, this study screened 107 lines/cultivars for their reactions to white mould in 14 preliminary trials conducted under irrigation. Thirteen resistant lines/cultivars (three of Andean origin) and six Mesoamerican cultivars (three intermediately resistant and three susceptible) were selected for further investigation. These lines/cultivars and the resistant control A195 were evaluated in six advanced trials and two straw tests to assess the effectiveness of the screening procedure. In 11 preliminary trials, screenings were performed under moderate/high or higher disease pressure. These pressures occurred in two advanced trials in which, when yields were averaged across moderate/high and high pressures, 10 Mesoamerican lines/cultivars selected for resistance yielded 14%, 23%, and 38% more than intermediately resistant cultivars, A195, and susceptible cultivars, with median disease ratings (1–9 scale) of 4.5, 5.7, 5.7, and 6.7, respectively. In the straw test, three Andean lines/cultivars (A195 included) and two susceptible cultivars in the field were among those with the highest levels of physiological resistance. Thus, field rating under high disease pressure and greenhouse rating did not correlate significantly, suggesting that field trials are critical to evaluating resistance and to identifying high-yielding beans. Therefore, lines/cultivars from breeding programmes assessed in field trials may provide a low cost and fast way to identify high-yielding bean cultivars with partial resistance to white mould in the subtropical southern hemisphere.     

Comparison between vegetation indices for detecting spatial and temporal variabilities in soybean crop using canopy sensors

Precision Agriculture - Crop monitoring through remote sensing techniques enable greater knowledge of average variability in crop growth. Canopy sensors help provide information on the variability...     

Prediction of Genetic Gain in Sweet Corn using Selection Indexes

Journal of Crop Science and Biotechnology - The cultivation of sweet corn is expanding in Brazil, but there are serious constraints about the availability of commercial cultivars. The selection of...     

Genome-wide in silico analysis of SOD genes in common bean (Phaseolus vulgaris L.)

Journal of Crop Science and Biotechnology - Superoxide dismutases (SODs) are a group of enzymes that play essential roles in catalyzing the dismutation of superoxide radicals to protect cells from...     

Meta-analysis of fungicide efficacy on soybean target spot and cost–benefit assessment

Target spot of soybean has spread in Brazil, the southeastern United States and Argentina in the last decade. A collaborative network of field Uniform Fungicide Trials (UFT) in Brazil was created in 2011 to study the target spot control efficacy of fungicides, including azoxystrobin + benzovindiflupyr (AZ_BF), carbendazim (CZM), fluxapyroxad + pyraclostrobin (FLUX_PYRA), epoxiconazole + FLUX_PYRA (EPO_FLUX_PYRA), mancozeb (MZB) and prothioconazole + trifloxystrobin (PROT_TRIF). Network meta-analysis was used to conduct a quantitative synthesis of UFT data collected from 2012 to 2016 and to evaluate the effects of disease pressure (DP, low ≤ 35% target spot severity in the nontreated control < high) and year of experiment on the overall mean efficacy and yield response to each of the tested fungicides. Based on mean percentage control of target spot severity, the tested fungicides fall into three efficacy groups (EG): high EG, FLUX_PYRA (76.2% control relative to the nontreated control) and EPO_FLUX_PYRA (75.7% control); intermediate EG, PROT_TRIF (66.5% control) and low EG, MZB (49.6% control), AZ_BF (46.7% control) and CZM (32.4% control). DP had a significant effect on yield response. At DP_Low, the highest response was due to PROT_TRIF (+342 kg ha⁻¹, +12.8%) and EPO_FLUX_PYRA (+295.5 kg ha⁻¹, +11.2%), whereas at DP_High, EPO_FLUX_PYRA and FLUX_PYRA outperformed the other treatments, with yield responses of 503 kg ha⁻¹ (+20.2%) and 469 kg ha⁻¹ (+19.1%), respectively. The probability of a positive return on fungicide investment ranged from 0.26 to 0.56 at DP_Low and from 0.34 to 0.66 at DP_High.