Biological Activities of Chickpea in Human Health (Cicer arietinum L.). A Review

Plant Foods for Human Nutrition - Chickpea is one of the most consumed legumes worldwide. Among their benefits are the high protein concentration that reflects not only at the nutritional level but...     

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.     

Using graph theory to analyse and assess changes in Mediterranean woodland connectivity

Landscape Ecology - The Portuguese montado is an agro-silvopastoral system, similar to the Spanish dehesa, known for its cultural, economic and ecological value. Despite its importance, contrasting...     

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...     

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.     

P0 protein of cotton leafroll dwarf virus-atypical isolate is a weak RNA silencing suppressor and the avirulence determinant that breaks the cotton Cbd gene-based resistance

Cotton blue disease (CBD) is the most important disease present in cotton crops in South America and cotton leafroll dwarf virus (CLRDV) is the causal agent. The disease has been controlled by sowing cotton varieties resistant to CLRDV. However, in the 2009/10 growing season, an outbreak due to an atypical CLRDV isolate (CLRDV-at) occurred in northwest Argentina. Although CLRDV and CLRDV-at genomes are very closely related, the symptoms they produce in cotton plants are quite different. P0 is the most divergent protein between the isolates and in CLRDV is a silencing suppressor protein. This work characterized the silencing suppressor activity of the P0 protein encoded by CLRDV-at (P0^CL-at) and evaluated its role in Cbd-resistance break in cotton plants. It was demonstrated that P0^CL-at, despite having a mutation in the consensus of the F-box-like motif, was able to suppress local RNA silencing, but displayed lower activity than P0^CL. P0^CL and P0^CL-at showed no differences in the interaction with Gossypium hirsutum SKP1 orthologue (GSK1) and Nicotiana benthamiana SKP1 and both P0 proteins triggered destabilization of ARGONAUTE1. However, when the ability to enhance PVX symptoms was evaluated, P0^CL-at was shown to be a weaker pathogenicity factor than P0^CL in N. benthamiana. Interestingly, trans-expressed P0^CL-at enabled CLRDV to systemically infect CBD-resistant plants, and a chimeric CLRDV-P0^CL-at infectious clone succeeded in establishing infection in CBD-resistant cotton varieties with symptoms resembling those produced by CLRDV-at. These results strongly suggest that P0^CL-at is the avirulence (Avr) determinant involved in breaking cotton Cbd gene-based resistance.     

Phytophthora oleae,a new root pathogen of wild olives

Wild olive (Olea europaea subsp. europaea var. sylvestris) is an important component of Mediterranean forests and a key genetic source for olive improvement programmes. Since 2009, a severe decline caused by Phytophthora cryptogea and P. megasperma has been detected in a protected wild olive forest of high ecological value (Dehesa de Abajo, Seville, Spain). In this natural forest, sampling of roots and soil was carried out on 25 wild olives with symptoms in 2014 and 2015. Apart from the already known P. cryptogea A1 and P. megasperma, a third Phytophthora species was consistently isolated from wild olive rootlets with symptoms. These isolates conformed morphologically with the newly described species P. oleae and were confirmed by analysis of their ITS regions and cox1 sequences. Temperature–growth relationships showed a maximum growth at 19.9 °C on carrot agar medium, making it the lowest temperature Phytophthora species infecting wild olive roots. Pathogenicity was confirmed on 1-year-old healthy wild olive seedlings and was similar to the previously known pathogenic phytophthoras. As temperature requirements are quite different, the three Phytophthora species may be active against wild olive roots in different seasons. However, the prevalence of P. oleae infecting wild olives in recent years could be due to its introduction as a new invasive pathogen. The probable invasive nature of P. oleae, together with increasing rain episodes concentrated in short periods frequent in southern Spain, would allow the outbreak of infections in wild olive forests, and also put cultivated olive orchards at risk.