Accurate information on irrigated areas’ spatial distribution and extent are crucial in enhancing agricultural water productivity, water resources management, and formulating strategic policies that enhance water and food security and ecologically sustainable development. However, data are typically limited for smallholder irrigated areas, which is key to achieving social equity and equal distribution of financial resources. This study addressed this gap by delineating disaggregated smallholder and commercial irrigated areas through the random forest algorithm, a non-parametric machine learning classifier. Location within or outside former apartheid “homelands” was taken as a proxy for smallholder, and commercial irrigation. Being in a medium rainfall area, the huge irrigation potential of the Inkomati-Usuthu Water Management Area (UWMA) is already well developed for commercial crop production outside former homelands. However, information about the spatial distribution and extent of irrigated areas within former homelands, which is largely informal, was missing. Therefore, we first classified cultivated lands in 2019 and 2020 as a baseline, from where the Normalised Difference Vegetation Index (NDVI) was used to distinguish irrigated from rainfed, focusing on the dry winter period when crops are predominately irrigated. The mapping accuracy of 84.9% improved the efficacy in defining the actual spatial extent of current irrigated areas at both smallholder and commercial spatial scales. The proportion of irrigated areas was high for both commercial (92.5%) and smallholder (96.2%) irrigation. Moreover, smallholder irrigation increased by over 19% between 2019 and 2020, compared to slightly over 7% in the commercial sector. Such information is critical for policy formulation regarding equitable and inclusive water allocation, irrigation expansion, land reform, and food and water security in smallholder farming systems.

Accurate information on irrigated areas’ spatial distribution and extent are crucial in enhancing agricultural water productivity, water resources management, and formulating strategic policies that enhance water and food security and ecologically sustainable development. However, data are typically limited for smallholder irrigated areas, which is key to achieving social equity and equal distribution of financial resources. This study addressed this gap by delineating disaggregated smallholder and commercial irrigated areas through the random forest algorithm, a non-parametric machine learning classifier. Location within or outside former apartheid “homelands” was taken as a proxy for smallholder, and commercial irrigation. Being in a medium rainfall area, the huge irrigation potential of the Inkomati-Usuthu Water Management Area (UWMA) is already well developed for commercial crop production outside former homelands. However, information about the spatial distribution and extent of irrigated areas within former homelands, which is largely informal, was missing. Therefore, we first classified cultivated lands in 2019 and 2020 as a baseline, from where the Normalised Difference Vegetation Index (NDVI) was used to distinguish irrigated from rainfed, focusing on the dry winter period when crops are predominately irrigated. The mapping accuracy of 84.9% improved the efficacy in defining the actual spatial extent of current irrigated areas at both smallholder and commercial spatial scales. The proportion of irrigated areas was high for both commercial (92.5%) and smallholder (96.2%) irrigation. Moreover, smallholder irrigation increased by over 19% between 2019 and 2020, compared to slightly over 7% in the commercial sector. Such information is critical for policy formulation regarding equitable and inclusive water allocation, irrigation expansion, land reform, and food and water security in smallholder farming systems.

Water sorption isotherms and effective moisture diffusivities were determined at 20 degrees C for sponge cakes at high water activity as a function of their initial porosity, in the range 86 and 52% (0 g/g dry basis fat content), and of their fat content, ranging between 0 and 0.30 g/g dry basis (67% initial porosity). The equilibrium moisture values were not affected by food structure and decreased with increasing fat content. The effective moisture diffusivity decreased from 7.5 to 0.3 X 10(-10) m2/s with increasing moisture content from 0.30 to 2.20 g/g dry basis. Decreasing initial porosity from 86 to 52% decreased effective moisture diffusivity by more than four orders of magnitude. This behaviour was related to differences of water transfer mechanisms, with the contribution from liquid water diffusion in the solid matrix and from vapour water diffusion in pores. Increasing fat content of 0.30 g/g dry basis in sponge cake, independently of porosity, decreased effective moisture diffusivity by more than five orders of magnitude. A predictive mathematical model was used to simulate moisture intake in two-composite food systems: sponge cakes with varying initial porosities and fat contents and an agar gel as a model of a non-rate limiting water source. Increasing the density of the structure or addition of fat in the cereal-based phase could increase shelf life of composite foods.

Artificial reefs have been advocated and implemented as management tools for aquaculture, species conservation and habitat replacement. However, the shelter capacity of artificial reefs and its influencing factors are still not well understood. In this study, we identified factors that may limit the shelter capacity of artificial reefs for sea cucumber (<i>Apostichopus japonicas</i>) with a laboratory experiment. We investigated how water flow and food availability affect the shelter capacity and conducted shelter utilization experiments to determine whether sea cucumber sheltering behavior was density dependent. The results revealed that shelter capacity of artificial reefs in high velocity is significantly higher than that of artificial reefs in low velocity or no velocity. The artificial reefs that were provided food had significantly higher shelter capacity than those that did not have food. The densities did not affect the sheltering capacity of artificial reefs in the laboratory experiment. There was a logarithmic relationship between the shelter capacity and shelter availability assessed by the exposed surface area of the artificial reefs. In conclusion, abundant food resources and high water flow may have a positive effect on the shelter capacity of artificial reefs.

Environmental pollution by heavy metals resulting from rapid economic development is a major concern. Soil, water, wheat, and rice samples were collected from the Lihe River Watershed in the Taihu Region (east China). In this study area, many types of industrial plants, including ceramics factories, plants working with refractory materials, and chemical plants are densely distributed and cause serious heavy metal pollution. In addition, well-developed transportation and agricultural activities are also important sources of heavy metals. Thus, the concentrations of selected heavy metals including cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) in the samples were analyzed to evaluate their potential integral risk (IR) to the health of the local population. Accordingly, the spatial distribution pattern of the IR values was determined in the study. The soil in the study area showed heavy Cd pollution, whereas the pollution by other elements was relatively slight. When the proportions of grain samples in which the concentrations exceeded the tolerance limits were examined, the grains were primarily contaminated with Pb, Ni, Cd, and Zn; and less contaminated with Cu and Cr. The drinking water of the local inhabitants was safe. The average IR value was 3.53 for adults and 3.91 for children, indicating that both adults and children may experience adverse health effects. The spatial distribution pattern of the IR values among the exposed populations in the study area showed high values in the eastern and middle parts, with maximum values >5, and low values in the western part, with minimum values <2. This is consistent with the distributions of the industries and the population. The study may provide a basis for comparison to other regions both in China and worldwide.

The absence of reliable estimates of distributions of antioxidants in food emulsions hinders the development of a useful method for comparing the efficiencies of antioxidants. Here we describe the application of a pseudophase kinetic model, originally developed for homogeneous microemulsions, to the determination of distribution constants of tert-butylhydroquinone, TBHQ, in a fluid, opaque, model food emulsion composed of the nonionic emulsifier C12E6, octane, and water. This kinetic method should be applicable to a wide variety of charged and uncharged antioxidants in emulsions composed of charged and uncharged emulsifiers. The distribution constants for partitioning of TBHQ between the oil and surfactant film regions, Ko(l), and the aqueous and surfactant film regions, Kw(l), were obtained by fitting changes in first-order rate constants, K(obs), with emulsifier volume fraction for the reaction of 4-hexadecyl-2,6-dimethylbenzenediazonium ion, 16-ArN2(+), with TBHQ. The rate of formation of the reduced arene product hexadecyl-2,6-dimethylbenzene, 16-ArH, was followed by HPLC. About 90% of the TBHQ is in the surfactant film at about 2% volume fraction of C12E6, which suggests that this region may be the primary site of antioxidant activity for neutral phenolic antioxidants.