Investigating Agricultural Management Practices and Environmental Sustainability in Jordan

Jordan, as other developing countries in the world, is struggled by instable agricultural development due to existing various water pressures (e.g. increase in irrigation demands, deterioration of water quality, industrial pollution, water borne sewerage, etc.), climate change impacts, and biophysical and socioeconomic barriers (e.g. rapid population growth, social unsettlements, sudden refuges and migrations, limited economic resources, low levels of technology, environmental limitations and stresses, and widespread poverty). One of the adaptive key issues for the Jordanian environmental sustainable development is the awareness of farmers on the water savings and environmental protections at farm level. The aim of this study was to present a descriptive analysis for the adopted conventional farming practices at the Jordan Valley and explore potential of adoption of new technologies in agricultural management coupled with sustainable environmental performances, as pursued by the project “Improving the Environmental Sustainability of Irrigated Agricultural Production in Lebanon and Jordan (ENSIAP)”. Twenty farmers were selected to represent the heterogeneity of the farming practices along the three zones (districts) of Jordan Valley: Northern, Middle, and Southern Jordan Valley. A detailed survey questionnaire was developed to investigate for the potential improvements in the conventional and the newly introduced farming practices to ensure the sustainability of all natural resources. The heterogeneity of the farmers\u27 knowledge, experience, and capabilities were determined in addition to various components of cropping/ farming practices. Seven themes were emphasized in this study including (1) Farm characteristics, (2) Soil description and management, (3) Crop characteristics and management, (4) Water Irrigation parameters, (5) Cultivation and fertilizer use, (6) Environmental related issues, and (7) Farmer experience. Results indicated that most of the farmers are not fully aware with environmental sustainability issues. The irrigation systems, fertilizer use, and management practices currently in use are not resource-conservative and do not follow Best Agricultural and Management Practices, leading to high soil and groundwater degradation and pollution

Estimating spatial variations in soil organic carbon using satellite hyperspectral data and map algebra

This study evaluated the effectiveness of using Hyperion hyperspectral data in improving existing remote-sensing methodologies for estimating soil organic carbon (SOC) content on farmland. The study area is Big Creek Watershed in Southern Illinois, USA. Several data-mining techniques were tested to calibrate and validate models that could be used for predicting SOC content using Hyperion bands as predictors. A combined model of stepwise regression followed by a five hidden nodes artificial neural network was selected as the best model, with a calibration coefficient of determination (R 2) of 78.9% and a root mean square error (RMSE) of 3.3 tonnes per hectare (t ha−1). The validation RMSE, however, was found to be 11.3 t ha−1. Map algebra was implemented to extrapolate this model and produce a SOC map for the watershed. Hyperspectral data improved marginally the predictability of SOC compared to multispectral data under natural field conditions. They could not capture small annual variations in SOC, but could measure decadal variations with moderate error. Satellite-based hyperspectral data combined with map algebra can measure total SOC pools in various ecosystem or soil types to within a few per cent error

Investigating the Pearl Millet (<i>Pennisetum glaucum</i>) as a Climate-Smart Drought-Tolerant Crop under Jordanian Arid Environments

To investigate drought tolerance under arid conditions, eleven pearl millet breeds (HHVBC tall B6; IP13150; IP19586; IP19612; IP22269; IP6110; IP7704; MC94C2; P. millet icms7709; Sudan-pop I; Sudan-pop III) were tested under arid water-scarce climatic conditions. A field randomized complete block design experiment with three replicates per year was conducted at the Deir-Alla Regional Agriculture Research center in the middle Ghor within the Jordan Valley from 2010 to 2020. The plant-deficit irrigation was maintained at 80% based on the crop water requirements using a time-domain reflectometer. The plant morphological characteristics, forage production, seed formation, and water-use efficiency (WUE) were monitored for ten years for two case scenarios: seed and forage production. The individual and combined drought indices of the precipitation, temperature, and vegetation were calculated and correlated with the millet morphological and yield parameters. Climate change analyses show significant impacts, reaching a 1 mm/year reduction in precipitation and a 0.04 mm/year increase in air temperature, which causes the study area to be more prone to drought events. Along with the proven increase in the drought intensity over time, the millet breeds showed significant drought-tolerance capacities under arid, drought-prone conditions by adjusting their system to tolerate salt, heat, and water stresses. For the seed production scenario, the WUE ranged from 27 to 57.3 kg/ha·mm, and from 7.1 to 14.9 kg/ha·mm for fresh and dry conditions, respectively. The IP13150 millet breed showed the highest capacity to tolerate the drought of Jordan’s environment, and it is thus recommended as a good substitute under water-scarcity situations, with an average production of 17.7 ton/ha. For the vegetative production scenario, the WUE ranged from 32.03 to 64.82 kg/ha·mm for the fresh biomass and from 10.8 to 24.6 kg/ha·mm for the dry biomass. Based on the WUEs and vegetative production results, the IP19586, IP22269, IP19612, IP7704, and HHVBC tall B6 millet breeds are recommended as forage support due to their phenological characteristics, which tolerate drought and heat conditions. In contrast to the vegetation drought index, both the precipitation and temperature drought indices show strong correlations (above r > 0.6) with the plant growth factors and a moderate correlation (0.3 < r < 0.6) with the yield factors. Both precipitation and temperature indices are capable of explaining the variations among millet breeds, especially as related to millets’ morpho-physiological characteristics