Gustavo A. Lobos

Blueberries and Cranberries

Most blueberry breeding activity is focused on northern highbush, southern highbush and rabbiteye types. The major objectives of blueberry breeders center on high plant vigor, improved disease resistance, flavor, longer storing fruit and expanded harvest dates. Cranberry breeders have concentrated on early maturing fruit, uniform large size, intense color, keeping quality, high productivity, disease resistance and plant vigor. Considerable variability exists in blueberry and cranberry for most of the horticulturally important traits, and while only a limited number of genetic studies have been performed, most inheritance patterns fit quantitative models. Several genes have been identified through molecular, genetic and genomic approaches that are associated with cold hardiness. Wide hybridization is commonly employed in blueberry breeding and southern highbush types were derived primarily by incorporating genes from the diploid species Vaccinium darrowii into the highbush background via unreduced gametes. A wide array of molecular markers has been used in blueberry for fingerprinting and linkage mapping, and a major QTL regulating the chilling requirement in diploids has been identified. Transgenic blueberries have been produced with herbicide resistance and the Bt gene (Bacillus thuringiensis) has been incorporated into cranberry. A large EST library of highbush blueberry has been produced.

Wheat genotypic variability in grain yield and carbon isotope discrimination under Mediterranean conditions assessed by spectral reflectance.

A collection of 368 advanced lines and cultivars of spring wheat (Triticum aestivum L.) from Chile, Uruguay, and CIMMYT (Centro Internacional de Mejoramiento de Maíz y Trigo), with good agronomic characteristics were evaluated under the Mediterranean conditions of central Chile. Three different water regimes were assayed: severe water stress (SWS, rain fed), mild water stress (MWS; one irrigation around booting), and full irrigation (FI; four irrigations: at tillering, flag leaf appearance, heading, and middle grain filling). Traits evaluated were grain yield (GY), agronomical yield components, days from sowing to heading, carbon isotope discrimination (Δ(13) C) in kernels, and canopy spectral reflectance. Correlation analyses were performed for 70 spectral reflectance indices (SRI) and the other traits evaluated in the three trials. GY and Δ(13) C were the traits best correlated with SRI, particularly when these indices were measured during grain filling. However, only GY could be predicted using a single regression, with Normalized Difference Moisture Index (NDMI2: 2,200; 1,100) having the best fit to the data for the three trials. For Δ(13) C, only individual regressions could be forecast under FI (r(2): 0.25-0.37) and MWS (r(2): 0.45-0.59) but not under SWS (r(2): 0.03-0.09). NIR-based SRI proved to be better predictors than those that combine visible and NIR wavelengths.

Chlorophyll, anthocyanin, and gas exchange changes assessed by spectroradiometry in Fragaria chiloensis under salt stress

Chlorophyll and anthocyanin contents provide a valuable indicator of the status of a plants physiology, but to be more widely utilized it needs to be assessed easily and non-destructively. This is particularly evident in terms of assessing and exploiting germplasm for plant-breeding programs. We report, for the first time, experiments with Fragaria chiloensis (L.) Duch. and the estimation of the effects of response to salinity stress (0, 30, and 60 mmol NaCl/L) in terms of these pigments content and gas exchange. It is shown that both pigments (which interestingly, themselves show a high correlation) give a good indication of stress response. Both pigments can be accurately predicted using spectral reflectance indices (SRI); however, the accuracy of the predictions was slightly improved using multilinear regression analysis models and genetic algorithm analysis. Specifically for chlorophyll content, unlike other species, the use of published SRI gave better indications of stress response than Normalized Difference Vegetation Index. The effect of salt on gas exchange is only evident at the highest concentration and some SRI gave better prediction performance than the known Photochemical Reflectance Index. This information will therefore be useful for identifying tolerant genotypes to salt stress for incorporation in breeding programs.

Using Ridge Regression Models to Estimate Grain Yield from Field Spectral Data in Bread Wheat (Triticum Aestivum L.) Grown under Three Water Regimes

Plant breeding based on grain yield (GY) is an expensive and time-consuming method, so new indirect estimation techniques to evaluate the performance of crops represent an alternative method to improve grain yield. The present study evaluated the ability of canopy reflectance spectroscopy at the range from 350 to 2500 nm to predict GY in a large panel (368 genotypes) of wheat (Triticum aestivum L.) through multivariate ridge regression models. Plants were treated under three water regimes in the Mediterranean conditions of central Chile: severe water stress (SWS, rain fed), mild water stress (MWS; one irrigation event around booting) and full irrigation (FI) with mean GYs of 1655, 4739, and 7967 kg∙ha−1, respectively. Models developed from reflectance data during anthesis and grain filling under all water regimes explained between 77% and 91% of the GY variability, with the highest values in SWS condition. When individual models were used to predict yield in the rest of the trials assessed, models fitted during anthesis under MWS performed best. Combined models using data from different water regimes and each phenological stage were used to predict grain yield, and the coefficients of determination (R2) increased to 89.9% and 92.0% for anthesis and grain filling, respectively. The model generated during anthesis in MWS was the best at predicting yields when it was applied to other conditions. Comparisons against conventional reflectance indices were made, showing lower predictive abilities. It was concluded that a Ridge Regression Model using a data set based on spectral reflectance at anthesis or grain filling represents an effective method to predict grain yield in genotypes under different water regimes.

Effect of DPA [Diphenylamine] and 1-MCP [1-methylcyclopropene] on chemical compounds related to superficial scald of Granny Smith apples

Research was carried out to study the mode of action of diphenylamine (DPA) and 1-methylcyclopropene (1-MCP), on control of superficial scald of Granny Smith apples (Malus domestica Borkh.), and its relation with chemical compounds. Fruit was harvested from a commercial orchard in Chile, 182 and 189 days after full bloom and received the following treatments: DPA (2,000 ppm); 1-MCP (1.2 ppm) and control (no treatment). All fruit was stored for 4 or 6 months at 0 deg C. A completely randomized factorial design was used (2 harvest dates by 3 postharvest treatments). Monthly measurements were made on maturity indices, ethylene production rate (EPR), scald related compounds (alpha-farnesene (AF), conjugated trienes (CT), total anti-oxidants (AO)), and cell membrane stability. Following 4 and 6 months of storage, plus 7 days at 20 deg C, scald was evaluated. After 6 months, DPA-treated fruit, from both harvests, showed similar firmness, EPR and AO, compared to the control. However, AF and CT were lower, and cell membrane stability higher. Conversely, 1-MCP-treated fruit showed a noticeable EPR suppression and AF inhibition, along with higher firmness, lower CT and AO, compared to the control and DPA. Furthermore, cell membrane stability was superior to that of the control and similar to that of the DPA. Treated fruit (DPA and 1-MCP) showed an important reduction in scald compared to the control. The effect of 1-MCP on the investigated compounds and the reduction in scald, confirms that ethylene plays a major role on its development.

Firmness at Harvest Impacts Postharvest Fruit Softening and Internal Browning Development in Mechanically Damaged and Non-damaged Highbush Blueberries (Vaccinium corymbosum L.)

Fresh blueberries are very susceptible to mechanical damage, which limits postharvest life and firmness. Softening and susceptibility of cultivars “Duke” and “Brigitta” to developing internal browning (IB) after mechanical impact and subsequent storage was evaluated during a 2-year study (2011/2012, 2012/2013). On each season fruit were carefully hand-picked, segregated into soft (<1.60 N), medium (1.61–1.80 N), and firm (1.81–2.00 N) categories, and then either were dropped (32 cm) onto a hard plastic surface or remained non-dropped. All fruit were kept under refrigerated storage (0°C and 85–88% relative humidity) to assess firmness loss and IB after 7, 14, 21, 28, and 35 days. In general, regardless of cultivar or season, high variability in fruit firmness was observed within each commercial harvest, and significant differences in IB and softening rates were found. “Duke” exhibited high softening rates, as well as high and significant r2 between firmness and IB, but little differences for dropped vs. non-dropped fruit. “Brigitta,” having lesser firmness rates, exhibited almost no relationships between firmness and IB (especially for non-dropped fruit), but marked differences between dropping treatments. Firmness loss and IB development were related to firmness at harvest, soft and firm fruit being the most and least damaged, respectively. Soft fruit were characterized by greater IB development during storage along with high soluble solids/acid ratio, which could be used together with firmness to estimate harvest date and storage potential of fruit. Results of this work suggest that the differences in fruit quality traits at harvest could be related to the time that fruit stay on the plant after turning blue, soft fruit being more advanced in maturity. Finally, the observed differences between segregated categories reinforce the importance of analyzing fruit condition for each sorted group separately.

Effect of the Cooling System and 1-MCP on the Incidence of Superficial Scald in Granny Smith Apples

A study was carried out to determine the effects of two cooling systems and the application of 1-methylcyclopropene (1-MCP, SmartFresh TM )�ontheincidenceofsuperficialscaldinapples�(Malus domestica Borkh.) cv. Granny Smith. Fruit were collected from a commercial orchard (Colbun, Maule Region, Chile) during 2004-2005 season. A completely randomized design was used in a 2 x 2 factorial arrangement, using cooling systems (normal and step-wise cooling) and application of 1-MCP (0 and 625 nL L -1 i.a.) as the main factors. Fruit from normal cooling were kept at 0 °C throughout the storage period (180 days). Step-wise cooling consisted of storing the fruit at 10 °C for 10 days; 4 °C for the next 20 days and 0 °C for the remaining 150 days. Every month, maturity indices and the chemicals, global antioxidant content (AO), α-farnesene�(AF)�andconjugatedtrienes�(TC),�weremeasured.�Incidenceofsuperficial� scald was determined after 180 days of storage, plus 10 days at 20 °C. The application of 1-MCP with both cooling systemswascapableofmaintainingfirmnessvaluesaround�8.2�kguptotheendofthestorageperiod,�aswellas� decreasingtheconcentrationofAF,�TCandAOduringstorage.�Incidenceofsuperficialscaldonfruitwith�1-MCP� was 0%, regardless of the type of cooling. Among treatments without 1-MCP, step-wise-cooling was more effective inpreventingsuperficialscald,�resultingin�1.3%�incidencecomparedto�75.6%�withthenormalcoolingsystem.� Nevertheless,�fromthefourthmonthonwardsfirmnesswaslowerthanthatrequiredforexport.

Latin America: A Development Pole for Phenomics

Latin America and the Caribbean (LAC) has long been associated with the production and export of a diverse range of agricultural commodities. Due to its strategic geographic location, which encompasses a wide range of climates, it is possible to produce almost any crop. The climate diversity in LAC is a major factor in its agricultural potential but this also means climate change represents a real threat to the region. Therefore, LAC farming must prepare and quickly adapt to an environment that is likely to feature long periods of drought, excessive rainfall and extreme temperatures. With the aim of moving toward a more resilient agriculture, LAC scientists have created the Latin American Plant Phenomics Network (LatPPN) which focuses on LACs economically important crops. LatPPNs key strategies to achieve its main goal are: (1) training of LAC members on plant phenomics and phenotyping, (2) establish international and multidisciplinary collaborations, (3) develop standards for data exchange and research protocols, (4) share equipment and infrastructure, (5) disseminate data and research results, (6) identify funding opportunities and (7) develop strategies to guarantee LatPPNs relevance and sustainability across time. Despite the challenges ahead, LatPPN represents a big step forward toward the consolidation of a common mind-set in the field of plant phenotyping and phenomics in LAC.

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules.

Assessing Wheat Traits by Spectral Reflectance: Do We Really Need to Focus on Predicted Trait-Values or Directly Identify the Elite Genotypes Group?

Phenotyping, via remote and proximal sensing techniques, of the agronomic and physiological traits associated with yield potential and drought adaptation could contribute to improvements in breeding programs. In the present study, 384 genotypes of wheat (Triticum aestivum L.) were tested under fully irrigated (FI) and water stress (WS) conditions. The following traits were evaluated and assessed via spectral reflectance: Grain yield (GY), spikes per square meter (SM2), kernels per spike (KPS), thousand-kernel weight (TKW), chlorophyll content (SPAD), stem water soluble carbohydrate concentration and content (WSC and WSCC, respectively), carbon isotope discrimination (Δ13C), and leaf area index (LAI). The performances of spectral reflectance indices (SRIs), four regression algorithms (PCR, PLSR, ridge regression RR, and SVR), and three classification methods (PCA-LDA, PLS-DA, and kNN) were evaluated for the prediction of each trait. For the classification approaches, two classes were established for each trait: The lower 80% of the trait variability range (Class 1) and the remaining 20% (Class 2 or elite genotypes). Both the SRIs and regression methods performed better when data from FI and WS were combined. The traits that were best estimated by SRIs and regression methods were GY and Δ13C. For most traits and conditions, the estimations provided by RR and SVR were the same, or better than, those provided by the SRIs. PLS-DA showed the best performance among the categorical methods and, unlike the SRI and regression models, most traits were relatively well-classified within a specific hydric condition (FI or WS), proving that classification approach is an effective tool to be explored in future studies related to genotype selection.