Technical and Economic Analysis of Aeroponics and other Systems for Potato Mini-Tuber Production in Latin America

Producing large quantities of high quality mini-tubers at low cost is essential for an economically viable supply of seed potatoes. Here we systematize the technical and economic aspects of aeroponics and provide a benchmark comparison of this technology with other mini-tuber production systems as developed in Latin America: conventional, semi-hydroponics, and fiber-cement tiles technology. Research methodologies included: 3-year registration of cash flows and production registers of aeroponics, economic and technical surveys, in-depth inquiry with managers of technologies. Results show that aeroponics as promoted by the International Potato Center (CIP) has several advantages, including high multiplication rates (up to 1:45), high production efficiency per area (> 900 mini-tubers per m²), savings in water, chemicals and/or energy, and positive economic indicators. The fiber-cement tiles technology from Brazil is also shown to be highly efficient and slightly more robust compared to aeroponics. Preconditions for the successful adoption of the different technologies in developing countries are discussed.     

Insecticide resistance profiles can be misleading in predicting the survival of Myzus persicae genotypes on potato crops following the application of different insecticide classes

BACKGROUND: The accuracy of predicting the survival of insecticide‐resistant aphids following the application of commonly used insecticides from the carbamate, the pyrethroid, a mix of the two or the neonicotinoid chemical classes was evaluated in a potato field in Scotland. Equal proportions of five genotypes of the peach‐potato aphid, Myzus persicae (Sulzer), with none, resistance to dimethyl‐carbamates, resistance to pyrethroids or combinations conferring resistance to both chemical classes were released into potato field plots. The insecticides were sprayed separately onto these plots, the aphid populations were analysed after 6–8 days and the process repeated. RESULTS: For each assessment after the three separate spray events, plots treated with the carbamate had 48, 147 and 28%, those treated with pyrethroid 53, 210 and 89%, those treated with carbamate/pyrethroid 28, 108 and 64% and those treated with neonicotinoid 43, 55 and 11% of the numbers of M. persicae by comparison with untreated controls. Only the proportions of surviving aphids from the genotype containing no insecticide resistance traits and the genotype containing elevated carboxylesterases matched ratios predicted from the selective advantage afforded by the resistance traits alone. Survival of aphids from the other three genotypes that carried 1–3 of the insecticide resistance traits differed from expectations in all cases, possibly owing to physiological differences, including their vulnerability to predators and hymenopterous parasitoids present at the site and/or their carrying unknown insecticide resistance mechanisms. CONCLUSION: Control strategies based on knowledge of the genetically determined insecticide resistance profile of an M. persicae population alone are insufficient. Hence, other important factors contributing to aphid survival under insecticide pressure need to be considered. Copyright © 2012 Society of Chemical Industry     

Pressurized liquid extraction and HPLC quantification of folic Acid in fortified wheat flours

A pressurized liquid extraction (PLE) method using phosphate buffer as solvent was applied for folic acid (FA) extraction from fortified wheat flours and was compared to a standard solid-liquid extraction (SLE) method. Extracted FA was quantified by reverse phase high-performance liquid chromatography (RP-HPLC) hyphenated with a phenyl column and an absorption photometric detector (λ = 280 nm). Detection and quantification limits were 0.12 and 0.4 ng, respectively, corresponding to 0.06 and 0.2 μg g(-1) of analyzed wheat flour. Equivalent FA contents were found by both extraction methods, but a single PLE allowed a total recovery of FA content, whereas at least three successive SLEs were needed to achieve a total recovery of FA. The obtained results indicated that PLE is a rapid and efficient technique for FA extraction from fortified wheat flour.     

Effect of fulvic acids on lead-induced oxidative stress to metal sensitive Vicia faba L. plant

Lead (Pb) is a ubiquitous environmental pollutant capable to induce various morphological, physiological, and biochemical functions in plants. Only few publications focus on the influence of Pb speciation both on its phytoavailability and phytotoxicity. Therefore, Pb toxicity (in terms of lipid peroxidation, hydrogen peroxide induction, and photosynthetic pigments contents) was studied in Vicia faba plants in relation with Pb uptake and speciation. V. faba seedlings were exposed to Pb supplied as Pb(NO₃)₂ or complexed by two fulvic acids (FAs), i.e. Suwannee River fulvic acid (SRFA) and Elliott Soil fulvic acid (ESFA), for 1, 12, and 24?h under controlled hydroponic conditions. For both FAs, Pb uptake and translocation by Vicia faba increased at low level (5?mg?l^?1), whereas decreased at high level of application (25?mg?l^?1). Despite the increased Pb uptake with FAs at low concentrations, there was no influence on the Pb toxicity to the plants. However, at high concentrations, FAs reduced Pb toxicity by reducing its uptake. These results highlighted the role of the dilution factor for FAs reactivity in relation with structure; SRFA was more effective than ESFA in reducing Pb uptake and alleviating Pb toxicity to V. faba due to comparatively strong binding affinity for the heavy metal.     

Discrimination of three Pegaga (Centella) varieties and determination of growth-lighting effects on metabolites content based on the chemometry of 1H nuclear magnetic resonance spectroscopy

The metabolites of three species of Apiaceae, also known as Pegaga, were analyzed utilizing (1)H NMR spectroscopy and multivariate data analysis. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) resolved the species, Centella asiatica, Hydrocotyle bonariensis, and Hydrocotyle sibthorpioides, into three clusters. The saponins, asiaticoside and madecassoside, along with chlorogenic acids were the metabolites that contributed most to the separation. Furthermore, the effects of growth-lighting condition to metabolite contents were also investigated. The extracts of C. asiatica grown in full-day light exposure exhibited a stronger radical scavenging activity and contained more triterpenes (asiaticoside and madecassoside), flavonoids, and chlorogenic acids as compared to plants grown in 50% shade. This study established the potential of using a combination of (1)H NMR spectroscopy and multivariate data analyses in differentiating three closely related species and the effects of growth lighting, based on their metabolite contents and identification of the markers contributing to their differences.     

Evaluation of mid-season sensor based nitrogen fertilizer recommendations for winter wheat using different estimates of yield potential

Optical sensors, coupled with mathematical algorithms, have proven effective at determining more accurate mid-season nitrogen (N) fertilizer recommendations in winter wheat. One parameter required in making these recommendations is in-season grain yield potential at the time of sensing. Four algorithms, with different methods for determining grain yield potential, were evaluated for effectiveness to predict final grain yield and the agronomic optimum N rate (AONR) at 34 site-years. The current N fertilizer optimization algorithm (CNFOA) outperformed the other three algorithms at predicting yield potential with no added N and yield potential with added N (R² = 0.46 and 0.25, respectively). However, no differences were observed in the amount of variability accounted for among all four algorithms in regards to predicting the AONR. Differences were observed in that the CNFOA and proposed N fertilizer optimization algorithm (PNFOA), under predicted the AONR at approximately 75 % of the site-years; whereas, the generalized algorithm (GA) and modified generalized algorithm (MGA) recommended N rates under the AONR at about 50 % of the site-years. The PNFOA was able to determine N rate recommendations within 20 kg N ha^?1 of the AONR for half of the site-years; whereas, the other three algorithms were only able recommend within 20 kg N ha^?1 of the AONR for about 40 % of the site-years. Lastly, all four algorithms reported more accurate N rate recommendations compared to non-sensor based methodologies and can more precisely account for the year to year variability in grain yields due to environment.     

Development of an in-season estimate of yield potential utilizing optical crop sensors and soil moisture data for winter wheat

When utilizing optical sensors to make in-season agronomic recommendations in winter wheat, one parameter often required is the in-season grain yield potential at the time of sensing. Current estimates use an estimate of biomass, such as normalized difference vegetation index (NDVI), and growing degree days (GDDs) from planting to NDVI data collection. The objective of this study was to incorporate soil moisture data to improve the ability to predict final grain yield in-season. Crop NDVI, GDDs that were adjusted based upon if there was adequate water for crop growth, and the amount of soil profile (0–0.80 m) water were incorporated into a multiple linear regression model to predict final grain yield. Twenty-two site-years of N fertility trials with in-season grain yield predictions for growth stages ranging from Feekes 3 to 10 were utilized to calibrate the model. Three models were developed: one for all soil types, one for loamy soil textured sites, and one for coarse soil textured sites. The models were validated with 11 independent site-years of NDVI and weather data. The results indicated there was no added benefit to having separate models based upon soil types. Typically, the models that included soil moisture, more accurately predicted final grain yield. Across all site years and growth stages, yield prediction estimates that included soil moisture had an R² = 0.49, while the current model without a soil moisture adjustment had an R² = 0.40.