A pachyderm perfume: odour encodes identity and group membership in African elephants.

Group-living animals that live in complex social systems require effective modes of communication to maintain social cohesion, and several acoustic, olfactory and visual signaling systems have been described. Individuals need to discriminate between in- and out-group odour to both avoid inbreeding and to identify recipients for reciprocal behaviour. The presence of a unique group odour, identified in several social mammals, is a proposed mechanism whereby conspecifics can distinguish group from non-group members. African elephants (Loxodonta africana) live in stable, socially complex, multi-female, fission-fusion groups, characterized by female philopatry, male dispersal and linear dominance hierarchies. Elephant social behaviour suggests that individuals use odour to monitor the sex, reproductive status, location, health, identity and social status of conspecifics. To date, it is not clear what fixed or variable information is contained in African elephant secretions, and whether odour encodes kinship or group membership information. Here we use SPME GC-MS generated semiochemical profiles for temporal, buccal and genital secretions for 113 wild African elephants and test their relationship with measures of genetic relatedness. Our results reveal the existence of individual identity odour profiles in African elephants as well as a signature for age encoded in temporal gland and buccal secretions. Olfactory signatures for genetic relatedness were found in labial secretions of adult sisters. While group odour was not correlated with group genetic relatedness, our analysis identified "group membership" as a significant factor explaining chemical differences between social groups. Saturated and short-chain fatty acids (SCFAs), derived from key volatile compounds from bacterial fermentation, were identified in temporal, buccal and genital secretions suggesting that group odour in African elephants may be the result of bacterial elements of the gut microbiome. The frequent affiliative behavior of African elephants is posited as a likely mechanism for bacterial transmission. Our findings favour flexible group-specific bacterial odours, which have already been proposed for other social mammals and present a useful form of olfactory communication that promotes bond group cohesion among non-relatives in fission-fusion mammals.

Classification of Browning on Intact Table Grape Bunches Using Near-Infrared Spectroscopy Coupled With Partial Least Squares-Discriminant Analysis and Artificial Neural Networks.

Table grape browning is a complex physiological disorder that occurs during cold storage. There is a need to investigate novel and innovative ways to manage the problem that hampers the progressive and sustainable growth of table grape industries. Given the complex nature of the browning phenomenon, techniques such as near-infrared (NIR) spectroscopy can be utilized for the non-destructive classification of different browning phenotypes. In this study, NIR coupled with partial least squares discriminant analysis (PLS-DA) and artificial neural networks (ANN) were used to classify bunches as either clear or as having chocolate browning and friction browning based on the spectra obtained from intact 'Regal Seedless' table grape bunches that were cold-stored over different periods. Friction browning appears as circular spots close to the pedicel area that are formed when table grape berries move against each other, and chocolate browning appears as discoloration, which originates mostly from the stylar-end of the berry, although the whole berry may appear brown in severe instances. The evaluation of the models constructed using PLS-DA was done using the classification error rate (CER), specificity, and sensitivity and for the models constructed using ANN, the kappa score was used. The CER for chocolate browning (25%) was better than that of friction browning (46%) for weeks 3 and 4 for both class 0 (absence of browning) and class 1 (presence of browning). Both the specificity and sensitivity of class 0 and class 1 for friction browning were not as good as that of chocolate browning. With ANN, the kappa score was tested to classify table grape bunches as clear or having chocolate browning or friction browning and showed that chocolate browning could be classified with a strong agreement during weeks 3 and 4 and weeks 5 and 6 and that friction browning could be classified with a moderate agreement during weeks 3 and 4. These results open up new possibilities for the development of quality checks of packed table grape bunches before export. This has a significant impact on the table grape industry for it will now be possible to evaluate bunches non-destructively during packaging to determine the possibility of these browning types being present when reaching the export market.

Editorial: Special Issue "Emerging Sensor Technology in Agriculture".

Research and innovation activities in the area of sensor technology can accelerate the adoption of new and emerging digital tools in the agricultural sector by the implementation of precision farming practices such as remote sensing, operations, and real-time monitoring [...].

Measuring Internal Maturity Parameters Contactless on Intact Table Grape Bunches Using NIR Spectroscopy.

The determination of internal maturity parameters of table grape is usually done destructively using manual methods that are time-consuming. The possibility was investigated to determine whether key fruit attributes, namely, total soluble solids (TSS); titratable acidity (TA), TSS/TA, pH, and BrimA (TSS - k x TA) could be determined on intact table grape bunches using Fourier transform near-infrared (FT-NIR) spectroscopy and a contactless measurement mode. Partial Least Squares (PLS) regression models were developed for the maturity and sensory quality parameters using grapes obtained from two consecutive harvest seasons. Statistical indicators used to evaluate the models were the number of latent variables (LVs) used to build the model, the prediction correlation coefficient (R2p) and root mean square error of prediction (RMSEP). For the respective parameters TSS, TA, TSS/TA, pH, and BrimA, the LVs were 21, 23, 5, 7, and 24, the R2p = 0.71, 0.33, 0.57, 0.28, and 0.77, and the RMSEP = 1.52, 1.09, 7.83, 0.14, and 1.80. TSS performed best when moving smoothing windows (MSW) + multiplicative scatter correction (MSC) was used as spectral pre-processing technique, TA with standard normal variate (SNV), TSS/TA with Savitzky-Golay first derivative (SG1d), pH with SG1d, and BrimA with MSC. This study provides the first steps towards a completely nondestructive and contactless determination of internal maturity parameters of intact table grape bunches.

Investigating 2-D and 3-D Proximal Remote Sensing Techniques for Vineyard Yield Estimation.

Vineyard yield estimation provides the winegrower with insightful information regarding the expected yield, facilitating managerial decisions to achieve maximum quantity and quality and assisting the winery with logistics. The use of proximal remote sensing technology and techniques for yield estimation has produced limited success within viticulture. In this study, 2-D RGB and 3-D RGB-D (Kinect sensor) imagery were investigated for yield estimation in a vertical shoot positioned (VSP) vineyard. Three experiments were implemented, including two measurement levels and two canopy treatments. The RGB imagery (bunch- and plant-level) underwent image segmentation before the fruit area was estimated using a calibrated pixel area. RGB-D imagery captured at bunch-level (mesh) and plant-level (point cloud) was reconstructed for fruit volume estimation. The RGB and RGB-D measurements utilised cross-validation to determine fruit mass, which was subsequently used for yield estimation. Experiment one's (laboratory conditions) bunch-level results achieved a high yield estimation agreement with RGB-D imagery (r2 = 0.950), which outperformed RGB imagery (r2 = 0.889). Both RGB and RGB-D performed similarly in experiment two (bunch-level), while RGB outperformed RGB-D in experiment three (plant-level). The RGB-D sensor (Kinect) is suited to ideal laboratory conditions, while the robust RGB methodology is suitable for both laboratory and in-situ yield estimation.

Thermal Imaging Reliability for Estimating Grain Yield and Carbon Isotope Discrimination in Wheat Genotypes: Importance of the Environmental Conditions.

Canopy temperature (Tc) by thermal imaging is a useful tool to study plant water status and estimate other crop traits. This work seeks to estimate grain yield (GY) and carbon discrimination (Δ13C) from stress degree day (SDD = Tc - air temperature, Ta), considering the effect of a number of environmental variables such as the averages of the maximum vapor pressure deficit (VPDmax) and the ambient temperature (Tmax), and the soil water content (SWC). For this, a set of 384 and a subset of 16 genotypes of spring bread wheat were evaluated in two Mediterranean-climate sites under water stress (WS) and full irrigation (FI) conditions, in 2011 and 2012, and 2014 and 2015, respectively. The relationship between the GY of the 384 wheat genotypes and SDD was negative and highly significant in 2011 (r2 = 0.52 to 0.68), but not significant in 2012 (r2 = 0.03 to 0.12). Under WS, the average GY, Δ13C, and SDD of wheat genotypes growing in ten environments were more associated with changes in VPDmax and Tmax than with the SWC. Therefore, the amount of water available to the plant is not enough information to assume that a particular genotype is experiencing a stress condition.

Integration of proteomics and metabolomics data of early and middle season Hass avocados under heat treatment.

Ripening heterogeneity of Hass avocados results in inconsistent quality fruit delivered to the triggered and ready to eat markets. This research aimed to understand the effect of a heat shock (HS) prior to controlled atmosphere (CA) storage on the reduction of ripening heterogeneity. HS prior to CA storage reduces more drastically the ripening heterogeneity in middle season fruit. Via correlation network analysis we show the different metabolomics networks between HS and CA. High throughput proteomics revealed 135 differentially expressed proteins unique to middle season fruit triggered by HS. Further integration of metabolomics and proteomics data revealed that HS reduced the glycolytic throughput and induced protein degradation to deliver energy for the alternative ripening pathways. l-isoleucine, l-valine, l-aspartic and ubiquitin carboxyl-terminal hydrolase involved in protein degradation were positively correlated to HS samples. Our study provides new insights into the effectiveness of HS in synchronizing ripening of Hass avocados.

Model development for non-destructive determination of rind biochemical properties of 'Marsh' grapefruit using visible to near-infrared spectroscopy and chemometrics.

Rind biochemical properties play major roles in defence mechanisms against the incidence of rind physiological disorders of citrus fruit during cold storage. Hence, multivariate calibration models were developed to rapidly and non-destructively determine rind biochemical properties of citrus fruit from visible to near-infrared (Vis/NIR) spectra acquired by Vis/NIR spectroscopy using partial least square regression algorithm. To achieve optimum models for determination of each rind biochemical property, several mathematical pre-processing methods were explored, including no pre-treatment. However, special emphases were given to the best model statistics in terms of coefficient of determination (R2) and residual predictive deviation (RPD). Models were performed by critical examination of different wavelength ranges (visible, near-infrared and full regions) and combinations of fruit harvested from different production regions and acquired before (week 0) and after (week 9) cold storage. Results obtained showed excellent models for determining parameters such as sucrose (R2 = 0.99 and RPD = 11.42), total flavonoids (R2 = 0.99 and RPD = 12.37), and chlorophyll b (R2 = 0.97 and RPD = 5.67). This study reported the first application of Vis/NIR and chemometrics in determining the rind biochemical properties of 'Marsh' grapefruit rapidly and non-destructively.

Effects of Three Irrigation Strategies on Gas Exchange Relationships, Plant Water Status, Yield Components and Water Productivity on Grafted Carménère Grapevines.

In the Chilean viticultural industry, Carménère is considered an emblematic cultivar that is cultivated mainly in arid and semi-arid zones. For this reason, it is necessary to use precise irrigation scheduling for improving water use efficiency (WUE), water productivity (WP), yield and wine quality. This study evaluated the effects of three deficit irrigation strategies on gas exchange variables, WUE, WP and yield components in a drip-irrigated Carménère vineyard growing under semi-arid climatic conditions during two consecutive seasons (2011/12 and 2012/13). The irrigation strategies were applied in completely randomized design from fruit set (S) to harvest (H). The first irrigation strategy (T1) involved continuous irrigation at 100% of actual evapotranspiration (ETa) from S to the veraison (V) period and at 80% of ETa from V to H. The second irrigation strategy (T2) involved irrigation at 50% of ETa from S to H and the third one (T3) involved no-irrigation from S to V and at 30% of ETa from V to H. The results indicated that there was a significant non-linear correlation between net CO2 assimilation (AN) and stomatal conductance (gs), which resulted in three zones of water stress (zone I = gs > 0.30 mol H2O m-2s-1; zone II = between 0.06 and 0.30 mol H2O m-2s-1; and zone III = gs < 0.06 mol H2O m-2s-1). The use of less water by T2 and T3 had a significant effect on yield components, with a reduction in the weight and diameter of grapes. A significant increase in WP (7.3 kg m-3) occurred in T3, which resulted in values of WUE that were significantly higher than those from T1 and T2. Also, a significant non-linear relationship between the integral water stress (SIΨ) and WP (R2 = 0.74) was established. The results show that grafted Carménère vines were tolerant to water stress although differences between cultivars/genotypes still need to be evaluated.

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.

Digital cover photography for estimating leaf area index (LAI) in apple trees using a variable light extinction coefficient.

Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAI(D)), which was compared with LAI estimated by the proposed digital photography method (LAI(M)). Results showed that the LAI(M) was able to estimate LAI(D) with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (f(f)) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.