Effect of the irrigation method and genotype on the bioaccumulation of toxic and trace elements in rice

The total concentration of three toxic elements (As, Cd and Pb) and five oligoelements (Cu, Mn, Mo, Ni and Se) has been determined using an original and completely validated ICP-MS method. This was applied to rice grains from 26 different genotypes cultivated in the same soil and irrigated with the same water in three different ways: by the traditional continuous flooding (CF) and by two intermittent methods, the sprinkler irrigation (SP) and the periodical saturation of the soil (SA). The adoption of SP hugely minimizes the average amounts of almost all elements in kernels (−98% for As, −90% for Se and Mn, −60% for Mo, −50% for Cd and Pb), with the only exception of Ni, whose concentration increases the average amount found in the CF rice by 7.5 times. Also SA irrigation is able to reduce the amounts of As, Mo and Pb in kernels but it significantly increases the amounts of Mn, Ni and – mainly - Cd. Also the nature of the genotype determined a wide variability of data within each irrigation method. Genotypes belonging to Indica subspecies are the best bioaccumulators of elements in both CF and SP methods and, never, the worst bioaccumulators for any element/irrigation method combination. In the principal component analysis, PC1 can differentiate samples irrigated by SP by those irrigated by CF and SA, whereas PC2 provides differentiation of CF samples by SA samples. When looking at the loading plot Ni is negatively correlated to the majority of the other elements, except Cu and Cd having negative loadings on PC2. These results allow to envisage that a proper combination of the irrigation method and the nature of rice genotype might be a very valuable tool in order to successfully achieve specific objectives of food safety or the attainment of functional properties

Global Antifungal Profile Optimization of Chlorophenyl Derivatives against Botrytis cinerea and Colletotrichum gloeosporioides

Twenty-two aromatic derivatives bearing a chlorine atom and a different chain in the para or meta position were prepared and evaluated for their in vitro antifungal activity against the phytopathogenic fungi Botrytis cinerea and Colletotrichum gloeosporioides. The results showed that maximum inhibition of the growth of these fungi was exhibited for enantiomers S and R of 1-(40-chlorophenyl)- 2-phenylethanol (3 and 4). Furthermore, their antifungal activity showed a clear structure-activity relationship (SAR) trend confirming the importance of the benzyl hydroxyl group in the inhibitory mechanism of the compounds studied. Additionally, a multiobjective optimization study of the global antifungal profile of chlorophenyl derivatives was conducted in order to establish a rational strategy for the filtering of new fungicide candidates from combinatorial libraries. The MOOPDESIRE methodology was used for this purpose providing reliable ranking models that can be used later

Alleviating poverty through Islamic microfinance: factors and measures of financial performance, and roles of Islamic values and financial policies

Indonesia has a strong presence of microfinance sector with the number of Islamic Microfinance Institutions (IMFIs) estimated to be around 5,000 currently. Microfinance is an effective tool in alleviating poverty in Indonesia due to the limited access to financial services by the poor who accounted for approximately 96 million Indonesians (or 37% of the total population), living on less than USD 1.90 a day. In the absence of collateral and steady income, the poor are considered too risky to be given credit facilities by the formal financial services providers and living in remote areas has also limited their access to formal financial services. This study aims to examine the poverty alleviation efforts from the perspective of the IMFIs in view of their direct involvement in the process and having rich information about financial issues facing the borrowers. The managers also understand about financial inclusion agenda as well as financial guidelines and regulations issued by the relevant authorities. A total of 34 managers of Baitulmaal Wa Tamwil (BMTs), which registered under the Sharia Cooperative Centre (INKOPSYAH) are taken as respondents from the Jakarta, Bogor, Depok, Tangerang and Bekasi (JABODETABEK) areas. The first instrument was a survey questionnaire, and the second one was an in-depth interview to outline data related to the model design. The findings of this research are expected to contribute to better decision-making for the BMTs to further enhance its role in alleviating poverty. The findings also elaborate several dimensions to improving financial inclusion among the poor including providing financial services, implementing Islamic principles, significant policies, community-based framework concept and training financial education. This research highlights the need for a variety of strategies to warrant success of poverty alleviation efforts by BMT

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts