Phytochemical screening of Cordia glabrata (MART.) A.DC. extracts and its potential antioxidant, photoprotective, antimicrobial and antiviral activities

Species of the genus Cordia have shown biological activities, such as anti-inflammatory, analgesic, antioxidant, antiviral, and antifungal activities. The species Cordia glabrata (MART) A.DC. Has no information concerning its phytochemical profile and possible biological activities. Thus, this study aimed to evaluate this profile in ethanolic extracts of young, adult and senescent leaves, as well as their antioxidant, photoprotective, antimicrobial, and virucidal potentials. Phytochemical analysis was performed by TLC (thin-layer chromatography) and showed the presence of flavonoids, tannins, and terpenes. The evaluation by UPLC-MS/MS (Ultra performance liquid chromatography - tandem mass spectrometer) evidenced the presence of caffeic (3.89 mgL-1), p-cumaric (6.13 mgL-1), and ferulic (0.58 mgL-1) acids, whilst, in GC/MS (Gas chromatography–mass spectrometry) analysis there was a greater amount of palmitic (51.17%), stearic (20.34%), linoleic (9.62%), and miristic (8.16%) fatty acids. The DPPH (2,2-Diphenyl-1-picrylhydrazyl) and ABTS+ (2′-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) radicals were used to verify the potential antioxidant activity, observing a better activity for the leaf extract in the adult phenological stage: 54.63 ± 1.06 µgmL-1 (DPPH) and 44.21 ± 1.69 mM (ABTS). The potential photoprotective activity of the extracts was determined by spectrophotometry and the in vitro values of SPF (Sun Protection Factor) in young and adult leaves (5.47 and 5.41, respectively) showed values close to the minimum SPF of 6.0 required by ANVISA (Brazilian Health Regulatory Agency). It was not observed an antimicrobial activity for Staphylococcus aureus with a minimum inhibitory concentration of 2000 μgmL-1, however the anti-herpetic assay against the Herpes simplex virus type 2 (HSV-2) showed a potent virucidal activity at the tested concentrations with CV50 value <0.195 μgmL-1 and a Selectivity Index (SI = CC50 / CV50) greater than 448. The results obtained in this study suggest that extracts of leaves of C. glabrata in their adult phenological stage have potential antioxidant, photoprotective and virucidal activity, considering in vitro test results.

Alternative products to control late season diseases in soybeans

ABSTRACT: In the last crop seasons, the complex of late season diseases (CLSD) of soybean (Glycine max L. (Merrill)), has been causing considerable reductions in the crop yield. Currently, there are no cultivars resistant to all pathogens that causes CLSD. The present study evaluated the effect of applying the acibenzolar-S-methyl resistance inducer, alternative products and fungicide on the severity of CLSD in the soybean cultivar BMX Potência RR during the 2013/2014 and 2014/2015 crops, in the field. The treatments for the experiments were: 1 - control (water); 2 - acibenzolar-S-methyl; 3 - calcium; 4 - micronutrients: copper, manganese and zinc; 5 - micronutrients: manganese, zinc and molybdenum; 6 - nitrogen-potassium fertilizer; 7 - Ascophyllum nodosum and 8 - azoxystrobin + cyproconazole with the addition of the adjuvant. Four applications of alternative products and two of fungicide were carried out in both harvests. A diagrammatic scale assessed the severity of CLSD at the phenological stage R7.1. The acibenzolar-S-methyl resistance inducer, alternative products (macro and micronutrients) and A. nodosum had no effect on the severity of CLSD in the two harvests. The fungicide (azoxystrobin + cyproconazole) reduced the severity of CLSD and prevented damage to productivity in both experiments.

Attacks by Termites (Blattoptera: Insecta) in cassava crops (Manioth esculenta Crantz.) in Daloa (Center-West, Côte d’Ivoire)

A study was carried out on the attack of termites in three cassava plots located in the zone of Daloa (town in the center-west of the Côte d’Ivoire). The main objective of this study was to ensure a sustainable productivity of cassava in the Daloa region by controlling termite’s pests of cassava crops according to the phenological stage, namely: the plot of cassava at the small stalk stage, the plot at the tuber production stage and the plot at the harvest stage. To this end, systematic excavations were carried out in the sections along the transects and plant-by-plant sampling in order to inventory the different species of termites on the plots and to highlight the damage they cause. This made it possible to identify 4 species of termites: Odontotermes sp., Macrotermes bellicosus, Pseudacanthotermes militaris and Nasutitermes latifrons, of which 1 species is common to all three environments. The comparative analysis of the different study environments showed that the plots at the production stage and at the harvest stage are the most colonized by termites. Odontotermes sp. observed only in plots at the small stage, as well as Nasutitermes latifrons which are only present on the plot at the production stage. Pseudacanthotermes militaris are best represented on all three plots.

The Sustainability of Irrigation Strategies in Traditional Olive Orchards

Olive trees are one of the few alternative crops available for farmers in arid environments. In many of these regions, surface irrigation is increasing. The aim of this study was to estimate the pattern of water soil reserves through the season considering different climatic scenarios, limitations in irrigation scheduling, and irrigation systems. Modeling was performed with the most common type of soil, and a tree density of 10 × 10 m was used. Three different climatic scenarios were estimated using eighteen agroclimatic stations along the zone (Jaén, Spain). In these climatic scenarios, different irrigation strategies were considered. First, the percentages of maximum flow available (100%, 50%, and 33%) were used. In each of these flows, the days available for irrigation were considered: daily irrigation (IDD), 20 days per month (ID20), and no irrigation, during August (RDI). The results suggest that a 33% flow strategy, the most common in the surveyed area, would produce the greatest water-stress period in the most sensitive phenological stage. However, 100%, in all scenarios, and 50% (only IDD and RDI) would obtain the best water status. According to the estimated water applied, 50% was the most advisable strategy. However, in a minimum rainfall scenario, water needs could be excessive.

Yield and vivipary of pecan nut (Carya illinoinensis[Wangenh.] K. Koch) in relation to soil moisture

Introduction: Viviparity in pecan nut (Carya illinoinensis [Wangenh.] K. Koch) has increased considerably. This genetic-environmental phenomenon can be controlled with soil moisture management and other quality variables.Objective: To determine the effect of soil moisture content on yield, nut size, kernel percentage and germinated nut on the tree.Materials and methods: Forty-year-old pecan nut trees were irrigated by 40 emitters with an output of 3.2 L∙h-1. From the phenological stage of shell hardening, irrigation time was 4, 6 and 8 h, corresponding to moisture levels of 0.257, 0.327 and 0.380 m3 of water per m3 of soil, at depths of 40 to 80 cm. Yield per tree, germinated nut percentage, fruit size and kernel percentage were evaluated during the production cycles of 2016 and 2017 production cycles.Results and discussion: During the two production cycles, when soil moisture level increased from 0.257 to 0.380 m3∙m-3, nut yield per tree, fruit length and diameter, and kernel percentage increased on average 23.8 %, 25.3 and 10 %, and 1.8 %, respectively; however, vivipary increased 11.2 %, which was reflected in the decrease of commercial pecan nut percentage. Treatments 0.327 and 0.380 m3∙m-3 had a similar effect (P > 0.05) on these variables.Conclusions: The lower moisture level (0.257 m3∙m-3), starting at the kernel filling stage, decreased vivipary and increased commercial kernel percentage.

Machine Learning Undercounts Reproductive Organs on Herbarium Specimens but Accurately Derives Their Quantitative Phenological Status: A Case Study of Streptanthus tortuosus

Machine learning (ML) can accelerate the extraction of phenological data from herbarium specimens; however, no studies have assessed whether ML-derived phenological data can be used reliably to evaluate ecological patterns. In this study, 709 herbarium specimens representing a widespread annual herb, Streptanthus tortuosus, were scored both manually by human observers and by a mask R-CNN object detection model to (1) evaluate the concordance between ML and manually-derived phenological data and (2) determine whether ML-derived data can be used to reliably assess phenological patterns. The ML model generally underestimated the number of reproductive structures present on each specimen; however, when these counts were used to provide a quantitative estimate of the phenological stage of plants on a given sheet (i.e., the phenological index or PI), the ML and manually-derived PI’s were highly concordant. Moreover, herbarium specimen age had no effect on the estimated PI of a given sheet. Finally, including ML-derived PIs as predictor variables in phenological models produced estimates of the phenological sensitivity of this species to climate, temporal shifts in flowering time, and the rate of phenological progression that are indistinguishable from those produced by models based on data provided by human observers. This study demonstrates that phenological data extracted using machine learning can be used reliably to estimate the phenological stage of herbarium specimens and to detect phenological patterns.

Oilseed Rape (Brassica napus L.) Phenology Estimation by Averaged Stokes-Related Parameters

Accurate and timely knowledge of crop phenology assists in planning and/or triggering appropriate farming activities. The multiple Polarimetric Synthetic Aperture Radar (PolSAR) technique shows great potential in crop phenology retrieval for its characterizations, such as short revisit time, all-weather monitoring and sensitivity to vegetation structure. This study aims to explore the potential of averaged Stokes-related parameters derived from multiple PolSAR data in oilseed rape phenology identification. In this study, the averaged Stokes-related parameters were first computed by two different wave polarimetric states. Then, the two groups of averaged Stokes-related parameters were generated and applied for analyzing averaged Stokes-related parameter sensitivity to oilseed rape phenology changes. At last, decision tree (DT) algorithms trained using 60% of the data were used for oilseed rape phenological stage classification. Four Stokes parameters (g0, g1, g2 and g3) and eight sub parameters (degree of polarization m, entropy H, ellipticity angle χ, orientation angle φ, degree of linear polarization Dolp, degree of circular polarization Docp, linear polarization ratio Lpr and circular polarization ratio Cpr) were extracted from a multi-temporal RADARSAT-2 dataset acquired during the whole oilseed rape growth cycle in 2013. Their sensitivities to oilseed rape phenology were analyzed versus five main rape phenology stages. In two groups (two different wave polarimetric states) of this study, g0, g1, g2, g3, m, H, Dolp and Lpr showed high sensitivity to oilseed rape growth stages while χ, φ, Docp and Cpr showed good performance for phenology classification in previous studies, which were quite noisy during the whole oilseed rape growth circle and showed unobvious sensitivity to the crop’s phenology change. The DT algorithms performed well in oilseed rape phenological stage identification. The results were verified at the parcel level with left 40% of the point dataset. Five phenology intervals of oilseed rape were identified with no more than three parameters by simple but robust decision tree algorithm groups. The identified phenology stages agree well with the ground measurements; the overall identification accuracies were 71.18% and 79.71%, respectively. For each growth stage, the best performance occurred at stage S1 with the accuracy of 95.65% for Group 1 and 94.23% for Group 2, and the worst performance occurred at stage S3 and S5 with the values around 60%. Most of the classification errors may resulted from the indistinguishability of S3 and S5 using Stokes-related parameters.