Glyphosate is used widely to control weeds. Glyphosate is a broad spectrum, non-selective, systemic and post-emergent herbicide. Glyphosate excessive use and impact on the environment is promoting the analysis of glyphosate in water, soil and food materials. Methods to analyse glyphosate at low levels are needed because glyphosate has a short half-life due to easy microbial degradation. Glyphosate has a high polarity and solubility in water, has high binding affinity with soil and is non-volatile. The absence of chromophoric groups in the molecular structure makes the detection difficult. Therefore, detection can be achieved by derivatisation, which makes glyphosate more volatile and stable for spectroscopic analysis. Derivatisation is commonly done by alkyl chloroformates, acylating agents, 9-fluoroenylmethylchloroformate, 4-methoxybenzenesulfonylfluoride and o-phthalaldehyde. Immunosensors allow detection at microlevels. Nanocrystals and nanotechnology allow detection at nanolevels. Here, we review methods to derivatise and analyse glyphosate.

The transverse water proton relaxation in three widely differing types of sample, native lysozyme solutions, skimmed milk and apple, has been analysed. The relaxation times show characteristic variations with CPMG pulse spacing and morphology which can be interpreted in terms of chemical exchange and molecular diffusion without recourse to popular concepts such as various amounts and types of 'bound' water. Our suggest that transverse water proton relaxation might be used as a sensitive probe of changes in water distribution during cellular growth and differentiation, freeze-thawing and dehydration-rehydration in food systems.

To provide stable and low-cost naturally derived yellow pigments, a variety of food byproducts were evaluated and the constituents of lemon peel have emerged yielding a highly promising natural product with applications as a food dye. Here we report a new, highly stable and water soluble food dye called yellow #15 from the ethanol extract of the zest of Citrus limon. The structure of lemon yellow #15 was carefully assigned on the basis of spectroscopic data, including 1D and 2D NMR spectroscopy, and the absolute configuration was established by comparison of the experimental CD with calculated electronic circular dichroism (ECD) spectral data. CIELAB values and Delta CIELAB were measured and revealed this new water-soluble pigment has superior light stability relative to other natural products used as food dyes.

Nowadays consumers are aware of environmental problems. As an alternative to petrochemical polymers for food packaging, researchers have been focused on biopolymeric materials as raw material. The aim of this study was to evaluate mechanical properties (toughness, burst strength and distance to burst), water adsorption, light-barrier properties and transparency of composite films based on cellulose, glycerol and polyvinyl alcohol. Scanning electron microscopy, spectral analysis (FT-IR and UV–VIS-NIR) and differential scanning calorimetry were performed to explain the morphology, structural and thermal properties of the films. Results showed that polyvinyl alcohol enhances the toughness of films up to 44.30 MJ/m3. However, toughness decreases when glycerol concentration is increased (from 23.41 to 10.55 MJ/m3). Water adsorption increased with increasing polyvinyl alcohol concentration up to 222%. Polyvinyl alcohol increased the film thickness. The films showed higher burst strength (up to 12014 g) than other biodegradable films. The films obtained have optimal values of transparency like those values of synthetic polymers. Glycerol produced a UV protective effect in the films, an important effect for food packaging to prevent lipid oxidative deterioration. Results showed that it is feasible to obtain cellulose-glycerol-polyvinyl alcohol composite films with improved properties.

The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km2 (26 575 200 ha), comparing a water-surplus year (2000-2001) and a water-deficit year (2002-2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61-100% for various land-use classes and 61-81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R2-values between 0.82 and 0.86. The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002-2003) when compared with the water-surplus year (2000-2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.

The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km2 (26 575 200 ha), comparing a water-surplus year (2000-2001) and a water-deficit year (2002-2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61-100% for various land-use classes and 61-81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R2-values between 0.82 and 0.86. The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002-2003) when compared with the water-surplus year (2000-2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.

In this research, a novel 1,8–naphthalimide–based colorimetric and ratiometric fluorescence chemoprobe (NAPH) was realistically developed for the recognition of copper (II) (Cu²⁺) in different vegetables and drinkable water samples. The sensing studies of NAPH depicted a ratiometric ''turn–on'' fluorescent response from bright yellow to blue as well as a colorimetric response toward Cu²⁺ from yellow to colorless, and it was found to be unselective towards various metal ions, anions and amino acids. The fast response of NAPH to Cu²⁺ caused a wavelength shift from 550 nm to 454 nm, and hence NAPH was used to recognize Cu²⁺ with an ultralow detection limit (9.53 nM). To validate the spectral data of NAPH, the study was performed using important analytical parameters and statistical tests. The binding stoichiometry between NAPH and Cu²⁺ was computed as 1:1 by Job's plot method as well MALDI TOF MS. Besides, the binding constant between the NAPH and Cu²⁺ was found to be 6.84 × 10³ M–¹. In addition to sensing studies, density–functional theory (DFT) findings strongly confirmed spectral data, and the Smartphone sensing results demonstrated that NAPH could be utilized as a powerful tool for the monitoring of Cu²⁺ without the need for sophisticated equipment. A test paper application was also performed to achieve semi–quantitative detection and to produce test kits with excellent selectivity toward Cu²⁺ without interfering metal ions. Furthermore, the newly designed probe NAPH was not only successfully used to recognize Cu²⁺ in bottled drinking waters (93.93–103.97%) but also was employed for vegetables with satisfactory results (92.97–109.92%).