Finding niches for whole-farm design models – contradictio in terminis?

Whole-farm design models quantitatively analyze the effects of a variety of potential changes at the farm system level. Science-driven technical information is confronted with value-driven objectives of farmers or other social groupings under explicit assumptions with respect to exogenous variables that are important drivers of agricultural systems (e.g., market conditions). Hence, farm design is an outcome of objective specification and the potential of a system. In recent publications, whole-farm design modelling has been proposed to enhance (farm) innovation processes. A number of operational modelling tools now offers the opportunity to assess the true potential of whole-farm design modelling to enhance innovation. In this paper, we demonstrate that it is not trivial to find niches for the application of goal-based farm models. Model outcomes appeared not to match questions of farm managers monitoring and learning from their own and other farmers’ practices. However, our research indicates that whole-farm design modelling possesses the capabilities to make a valuable contribution to reframing. Reframing is the phenomenon that people feel an urge to discuss and reconsider current objectives and perspectives on a problem. Reframing might take place in a situation (i) of mutually felt dependency between stakeholders, (ii) in which there is sufficient pressure and urgency for stakeholders to explore new problem definitions and make progress. Furthermore, our research suggests that the way the researcher enters a likely niche to introduce a model and/or his or her position in this niche may have significant implications for the potential of models to enhance an innovation process. Therefore, we hypothesize that the chances of capitalizing on modelling expertise are likely to be higher when researchers with such expertise are a logical and more or less permanent component of ongoing trajectories than when these researchers come from outside to purposefully search for a niche.     

Bentazone Leaching in Spanish Soils

Adsorption, incubation and soil-column experiments with bentazone [3-isopropyl-1H-2,1,3-benzothiadiazin-4(3H)-one 2,2-dioxide] were carried out in ten different soils from the marches surrounding the Doñana National Park (Huelva, SW Spain). Adsorption isotherms for the different soils showed a good fit with the Freundlich equation. Bentazone was poorly adsorbed in all the soils studied, with no significant relationship between theK_f values and soil characteristics. A significant correlation was obtained between the soil organic matter content and the distribution constant values (K_d) calculated at an equilibrium concentration of 200 μg cm⁻³. The low adsorption and non-degradation of bentazone on these soils suggest that the herbicide readily percolates through soils to reach the surface and ground waters. The mobility of bentazone through three soil columns was also studied. The mass balances carried out showed that bentazone was totally eluted from the soil columns. The theoretical model applied to explain bentazone leaching under our experimental conditions seems to be suitable for soil columns with a uniform water-flow rate.     

Comparison of selection methods among and within full-sibling progenies in Urochloa humidicola

Hybridization in the Urochloa humidicola breeding programme allowed to explore the genetic variability of the apomictic sources and, thus, to obtain new sexual and apomictic parents with compatible ploidy and/or superior progenies. However, given the high variability arising from crosses, there is a need to adopt efficient selection strategies among and within progenies. The aim of this study was to compare the selection methods among U. humidicola progenies with (t-BLUP) and without (BLUP) the weighting based on prediction error and subsequent selection within progenies by individual simulated (BLUP_IS) or optimal individual BLUP. We evaluated seventy-one U. humidicola full-sib progenies from biparental crosses between nine sexual and ten apomictic parents. The experiment was set up in an incomplete block design with 64 blocks of 15 plots each, consisting of individual plants. Seven consecutive cuts were made and the traits total dry-matter, leaf dry-matter and regrowth scores were measured. Genetic variance was expressive for all traits. The selection procedure among progenies of U. humidicula based on t-BLUP proved to be more advantageous regarding the use of BLUP not weighted by the prediction error, resulting in higher selection gains, taking as reference the optimal procedure of the individual BLUP. Furthermore, the use of BLUP_IS allowed an optimized selection of hybrids, allowing the breeder to explore with variable selection intensity the genetic variability within the selected full-sib progenies based on relative genetic merit.     

In vitro ruminal fermentation parameters and methane production of Marandu palisadegrass (Urochloa brizantha) in a silvopastoral system associated with levels of protein supplementation

The addition of protein supplementation in a silvopastoral system can contribute to improved forage intake and digestibility. Our objective was to evaluate in vitro ruminal parameters, digestibility and gas production of Marandu palisadegrass [Urochloa brizantha (Hochst. ex A. Rich.) R. D. Webster] in a silvopastoral system and compare this to parameters obtained from diets with protein supplementation. Forage was sampled during the growing season (November to April) in 2016/17 and 2017/18. In vitro incubation treatments consisted of four levels of protein supplement (20% of crude protein; CP) in the diet (0.1, 0.2, 0.3 and 0.4 g/kg of body weight). The neutral detergent fibre, acid detergent fibre and indigestible neutral detergent fibre concentrations were highest in the first year. In the second year, CP concentration was 21% greater than in the first year. There was a linear increase for digestion rate, a quadratic effect for lag time and a linear decrease for average digestion time as supplementation levels were increased. The least lag time and digestion time occurred in the second year. There was no supplementation effect on ruminal pH, acetate and butyrate concentrations. Second-year in vitro dry matter digestibility (IVDMD) was greater than in the first year. Increases in supplementation levels linearly enhanced IVDMD and reduced methane (CH₄) production. The inclusion of a protein supplement contributed to reduced CH₄ and increased volatile fatty acids production; therefore, we recommended the supplement inclusion of >0.28 g/kg of BW for animals grazing in well-managed palisadegrass pastures.     

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...     

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.     

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.