Energy and water balance measurements for water productivity analysis in irrigated mango trees, Northeast Brazil

Crop water parameters, including actual evapotranspiration, transpiration, soil evaporation, crop coefficients, evaporative fractions, aerodynamic resistances, surface resistances and percolation fluxes were estimated in a commercial mango orchard during two growing seasons in Northeast Brazil. The actual evapotranspiration (E_a) was obtained by the eddy covariance (EC) technique, while for the reference evapotranspiration (E₀); the FAO Penman–Monteith equation was applied. The energy balance closure showed a gap of 12%. For water productivity analysis the E_a was then computed with the Bowen ratio determined from the eddy covariance fluxes. The mean accumulated E_a for the two seasons was 1419 mm year⁻¹, which corresponded to a daily average rate of 3.7 mm day⁻¹. The mean values of the crop coefficients based on evapotranspiration (K_c) and based on transpiration (K_cb) were 0.91 and 0.73, respectively. The single layer K_c was fitted with a degree days function. Twenty percent of evapotranspiration originated from direct soil evaporation. The evaporative fraction was 0.83 on average. The average relative water supply was 1.1, revealing that, in general, irrigation water supply was in good harmony with the crop water requirements. The resulting evapotranspiration deficit was 73–95 mm per season only. The mean aerodynamic resistance (r_a) was 37 s m⁻¹ and the bulk surface resistance (r_s) was 135 s m⁻¹. The mean unit yield was 45 tonne ha⁻¹ being equivalent to a crop water productivity of 3.2 kg m⁻³ when based on E_a with an economic counterpart of US$ 3.27 m⁻³. The drawback of this highly productive use of water resources is an unavoidable percolation flux of approximately 300 mm per growing season that is detrimental to the downstream environment and water users.     

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.     

Short-term spatiotemporal variation of soil CO2 emission,temperature, moisture and aeration in sugarcane field reform areas under the influence of precipitation events

Soil CO₂ emission (FCO₂) in agricultural areas results from the interaction of different factors such as climate and soil conditions. Our objective was to investigate the spatiotemporal variation of FCO₂, temperature (T_soil), moisture (M_soil) and air-filled pore space (AFPS), as well as their interactions, during the sugarcane field reform. The study was conducted on a 90 × 90 m sampling grid with 100 points at 10 m spacings. Ten assessments of FCO₂, T_soil and M_soil were carried out at each point over a 28-day period. The greatest mean values of FCO₂ (0.74 g m⁻² hr⁻¹) and M_soil (31.7%) were obtained on Julian day 276, 2013, being associated with precipitation events at the study site. Also, the smallest values of AFPS (19.17%) and T_soil (20.90°C) were observed on the same day. The spatial variability of FCO₂, T_soil, M_soil and AFPS was best described by an adjusted spherical model, although an exponential model better fitted some results. The spatial pattern of all soil attributes showed little temporal persistency, indicating a high complexity for FCO₂ during precipitation. Correlation maps assisted in identifying regions where M_soil and AFPS better controlled the emission process and where T_soil was important. A major challenge for world agriculture is to increase the efficiency of conventional soil management practices. We highlight the importance of the spatial pattern of soil properties that directly influence the CO₂ emission dynamics. Future mitigation actions should involve less intense tillage and ensure homogeneous applications of soil inputs, thereby reducing production costs and the contribution of these activities to CO₂ emissions during the sugarcane field reform.     

Uncertainty assessment of soya bean yield gaps using DSSAT‐CSM‐CROPGRO‐Soybean calibrated by cultivar maturity groups

Soya bean yield gap can be caused by different factors resulting in uncertainties when the objective is to use such information for farm decision‐making and reference yield determination. Thus, this study aimed to quantify the soya bean yield gap for four sites, located in Southern and Midwestern Brazil, as well as the uncertainties of that related to cultivars, sowing dates, soil types and reference yields. The crop simulation model DSSAT‐CSM‐CROPGRO‐Soybean was calibrated for cultivars with similar maturity groups, based on the data obtained from the best farmers at the county level. The yield gap by water deficit (YG_WD) was obtained through the difference between potential and attainable yields, and that one caused by sub‐optimum crop management (YG_CM) by subtracting actual yield of each county, obtained from official statistics between 1989/90 and 2014/15 growing seasons, from the estimated attainable yield. The yield was simulated using four sowing dates, three soil types and two soya bean maturity groups by county. The reference yield uncertainty was quantified using yield reference from crop model and regional winners of the soya bean yield context, conducted by CESB (Brazilian Soybean Strategic Committee), for the growing seasons from 2013/14 to 2015/16. The crop model showed a good agreement between measured and simulated crop development and growth using calibration by maturity group, with low root mean square error (347 kg/ha). Southern sites had a mean YG_WD of 1,047 kg/ha, while in the Midwest, it was lower than 100 kg/ha. The YG_CM was 1,067, 528, 984 and 848 kg/ha, respectively, for Castro, PR, Mamborê, PR, Montividiu, GO and Primavera do Leste, MT, representing the opportunity for yield gain when having the best farmers as reference. The maturity groups, sowing dates and soil types showed to be an important source of uncertainty for yield gap determination, being recommended to investigate the farms in detail for an appropriate quantification. The reference yield showed expressive uncertainties, with some farmers presenting conditions to increase their soya bean yields by more than 3,000 kg/ha, when considering as reference the yields obtained by the winners’ farmers. These results show that uncertainties must be reduced when assessing farm yield gaps, in order to ensure that expected rate of soya bean yield growth could be reached by adopting the same technologies from CESB winners and best farmers in the county as a reference.     

Oral cavity evaluation and dental chart registration of coati (Nasua nasua) in captivity

The aims of this study were to develop a dental evaluate any oral cavity disease, develop gypsum models of the dental arches, and to register the occlusions found in coatis (Nasua nasua) in captivity Formulation of the dental chart was assisted by intraoral radiographs from the head of an adult coati cadaver of the same species with the following dental formula.: I 3/3, C 1/1, P 4/3, M 2/2. Seven live coatis of the Nasua nasua species were evaluated. Five of the seven coatis presented with various dental abnormalities as follows: dental plaque (71.4 0%), gingivitis (71.4 %), periodontitis (57.1 %), dental stain (42.9 %), dental abrasion (57.1 %), dental fracture (57.1 %), pulp exposure (42.9 %), malocclusion (57.1 %) and supernumerary teeth (14.2 %).     

Landscape structure shapes carnivore-mediated seed dispersal kernels

Context

Seed dispersal is recognized as having profound effects on the distribution, dynamics and structure of plant populations and communities. However, knowledge of how landscape structure shapes carnivore-mediated seed dispersal patterns is still scarce, thereby limiting our understanding of large-scale plant population processes.

Objectives

We aim to determine how the amount and spatial configuration of forest cover impacted the relative abundance of carnivorous mammals, and how these effects cascaded through the seed dispersal kernels they generated.

Methods

Camera traps activated by animal movement were used for carnivore sampling. Colour-coded seed mimics embedded in common figs were used to know the exact origin of the dispersed seed mimics later found in carnivore scats. We applied this procedure in two sites differing in landscape structure.

Results

We did not find between-site differences in the relative abundance of the principal carnivore species contributing to seed dispersal patterns, Martes foina. Mean dispersal distance and the probability of long dispersal events were higher in the site with spatially continuous and abundant forest cover, compared to the site with spatially aggregated and scarcer forest cover. Seed deposition closely matched the spatial patterning of forest cover in both study sites, suggesting behaviour-based mechanisms underpinning seed dispersal patterns generated by individual frugivore species.

Conclusions

Our results provide the first empirical evidence of the impact of landscape structure on carnivore-mediated seed dispersal kernels. They also indicate that seed dispersal kernels generated strongly depend on the effect that landscape structure exerts on carnivore populations, particularly on habitat-use preferences.

     

Near infrared spectroscopy as a tool for intensive mapping of vineyards soil

The wine industry has always been particularly interested in the influence of the terroir characteristics on the features of a wine. Over the past few years, a growing interest has spurred on the mechanisms by which a particular soil influences the vine’s growth, grape variety characteristics and ultimately wine quality. Near-infrared spectroscopy (NIRS) is a rapid, non-destructive, low-cost and robust analytical method for chemical and physical property determination. Its use for soil characterization, discrimination and compound determination is rapidly increasing. In this work, NIRS data were collected in two vineyards, one in the Dão Wine Region (centre of Portugal) and one in the Vinhos Verdes Wine Region (North of Portugal) previously characterized in terms of soils. Wet, dried and dried-ground soil samples collected from specific vineyard locations were scanned on a Fourier-transform near infrared spectrometer (FTLA 2000, ABB, Quebec, Canada) in diffuse reflectance mode. Spectra were analysed with chemometric tools, namely principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Results revealed that dried, ground soil samples gave better results, but not substantially so when compared with wet or dried samples. Discriminant models showed that the NIRS method is able to discriminate the different vineyard soil types, reproducing very accurately the mapping generated by pedology methods. Variations within the same soil type (present at different locations in the vineyard) were also detected by NIRS. The NIRS technology was shown to be suitable for correlating, complementing and perhaps eventually replacing costly, time-consuming vineyard soil mapping methods.