Monitoring the variation of soil quality with sewage sludge application rates in absence of rhizosphere effect

Agricultural soils in semi-arid regions have frequently been degraded due to adverse climatic conditions, organic matter depletion, and poor farming practices. To enhance soil quality, this study examines the reuse of sewage sludge (SS) as an available source of organic matter in a typical Mediterranean sandy-loam soil. Accordingly, we studied the cumulative effect of two annual applications of 40, 80 and 120 tons of sludge per ha on soil quality in absence of vegetation. The dose-dependent improvement of organic matter content was the most significant event that reflected sludge application rates, and consequently influenced other soil properties. Accordingly, soil structural stability increased by 13.3%, 28.8% and 59.4% for treatments SS-40, SS-80 and SS-120 respectively as compared to unamended control. Structural stability improvement was also confirmed by the dose-dependent variation of other edaphic factors including calcium content, the microbial quotient as well as Welt and C:N ratios. These parameters are involved in cementing soil aggregates by cation bridging, the formation of microbial mucilage, and clay-humic complexes. Soil magnetic susceptibility (SMS) was measured in situ as a possible rapid tool to evaluate soil condition. SMS showed significant correlation with sludge dose and stability amelioration testifying to the aggregation role that can play Al2O3 and particularly Fe2O3 minerals added by the hematite-rich sludge. Besides, analytical results and field observations revealed no trends of soil salinization or acidification by excessive sludge amounts. By avoiding the rhizosphere effect, outcomes could reflect the resilience and intrinsic capacity of the soil to cope with excessive sludge loads.This study was financially supported by a research grant from the Tunisian Ministry of Higher Education and Scientific Research. The authors would like to thank the National Sanitation Utility (ONAS) for providing urban sewage sludge. The technical support of Rym Ghrib is hereby acknowledged

International cooperation projects in support of entrepreneurship in southern Tunisia: activities and relations with public actors

In Tunisia, international cooperation projects in support of entrepreneurship boomed after the 2011 revolution. This paper analyses to what extent such projects have built the capacities of those involved in local entrepreneurial “ecosystems”. It analyses the main international cooperation projects supporting entrepreneurship in the Kebili and Medenine governorates (southern Tunisia) between 2011 and 2020. The activities of these projects were mapped and two workshops were conducted with actors of the local entrepreneurial ecosystems to discuss their implementation. Fourteen international cooperation projects were identified. These projects mostly focused on increasing the number of enterprises created, e.g., by supporting training, networking and sometimes funding. However, only one project provided support after creation of businesses, and few promoted a culture of entrepreneurship. Overall, these projects generally based their actions on the existing ecosystem of public actors in charge of supporting entrepreneurship. They made limited attempts to build the capacities of those actors, evaluate the functioning of local entrepreneurial ecosystems and coordinate among themselves

Sentinel 1 response to cereal leaf area index (lai): study case for central tunisia

Leaf area index (LAI) is very used to reveal the vegetation situation. To estimate the LAI for cereal, both direct and indirect methods have been used. In particular, remote sensing is a fast and reliable technique to develop the LAI estimation models. In this work, we present the potential of Sentinel 1 images for cereal estimation LAI in the center of Tunisia under semi arid climate. We established a statistical relationship between field LAI measurement for irrigated and rainfed wheat and backscatter coefficient based on an empirical analysis. This will be very useful in order to predict the water stress in a subsequent step. For experimental validation, the LAI of wheat crops were determined through the crop growth stages using eight Sentinel-1 images. The results showed a significant correlations, for the irrigated wheat, between LAI and backscatter coefficient for VV polarization (r values of -0.7) and for HV (r value of -0.5). For the rainfed wheat only the VV polarization showed a significant correlation (r= 0.6)

Evaluation of the potential of Sentinel-1 and Sentinel-1 data for clay content mapping

International audienceSoil texture is a key parameter in agricultural processes and an important measure for agricultural prediction, water cycle, filtering of pollutants and carbon storage. Besides, its estimation is essential for agronomists, hydrologists, geologists and environmentalists and for modeling in these application areas. Several studies have been based on understanding and modeling the biological, physical and chemical processes in the soil. Regarding the texture of the soil, few researches propose soil texture spatialization, and are generally based on ground measurements. Among other things, field observations or laboratory analyzes are very expensive and are not very representative. Indeed, the soil texture presents a strong heterogeneity even at the scale of a field. It is then necessary to use precise and spatialized information on soils. These methods are generally based on remote sensing data and particularly optical data to restore soil component. However, these techniques are strongly affected by atmospheric conditions. This constraint is not valid for Radar sensors (Radio Detection And Ranging). Radar data are mainly sensitive to soil moisture and soil roughness, and has also been evaluated for its ability to perform texture measurements. The aim of this study is evaluate the potential of these techniques based on optical and radar data for soil texture estimation. By its composition, its structure, its texture and its porosity, soil moisture is strongly influenced by the soil nature. With the arrival of Sentinel-1 (S-1) and Sentinel-2 (S-2) ESA spatial missions, data are acquired with high spatial and temporal resolution between July and early December 2017, on a semi-arid area in central Tunisia. This study is therefore conducted using S-2 SWIR (Short-Wave Infrared) bands (B11 and B12, most sensitive to clay) and soil moisture products derived from radar data. And algorithms based on the support vector machine (SVM) and random forest (RF) methods are proposed for the classification and mapping of clay content. In order to evaluate the approach and determine the adequate data (between optical and radar data) allowing to precisely characterize the clay content, a cross-validation was used. The SWIR bands lead to less satisfactory outcomes compared to soil moisture. With an overall accuracy of approximately 65%, soil moisture achieved the best performance for estimating soil texture. The results also showed that RF and SVM are robust classifiers for texture estimation despite the small number of training data. However, RF displays greater accuracy and speed of simulation compared to SVM

Clay Content Mapping Using Soil Moisture Products Derived From a Synergetic Use of Sentinel-1 and Sentinel-2 Data

International audienceThis study aimed to explore the potential of Sentinel satellites to predict topsoil texture, and more precisely to produce clay content map at fine spatial resolution. With its components and its porosity, soil texture is directly linked to soil moisture. In this context and with the arrival of Sentinel constellation, data are acquired with high spatial and temporal resolution. And soil moisture is retrieved from a synergetic use of Sentinel-1 (S-1) and Sentinel-2 (S-2) data between July and early December 2017, over a semi-arid area in central Tunisia. Relationship between soil moisture and clay content is studied and used to produce texture map.Classification algorithm based on random forest (RF) is used for the mapping of clay content classes. The results showed the potential of S-1 and S-2 products to predict soil texture

Genetic variation of salt-stressed durum wheat (Triticum turgidum subsp. durum Desf.) genotypes under field conditions and gynogenetic capacity

Agriculture has new challenges against the climate change: the preservation of genetic resources and the rapid creation of new varieties better adapted to abiotic stress, specially salinity. In this context, the agronomic performance of 25 durum wheat (Triticum turgidum subsp. durum Desf.) genotypes (nineteen landraces and six improved varieties), cultivated in two semi-arid regions in the center area of Tunisia, were assessed. These sites (Echbika, 2.2 g l−1; Barrouta, 4.2 g l−1) differ by their degree of salinity of the water irrigation. The results showed that most of the agronomic traits (e.g. spike per meter square, thousand kernels weight and grain yield) were reduced by salinity. Durum wheat landraces, Mahmoudi and Hmira, and improved varieties, Maali and Om Rabia showed the widest adaptability to different quality of irrigation water. Genotypes including Jneh Kotifa and Arbi were estimated as stable genotypes under adverse conditions. Thereafter, salt-tolerant (Hmira and Jneh Khotifa) and the most cultivated high-yielding (Karim, Razzak and Khiar) genotypes were tested for their gynogenetic ability to obtain haploids and doubled haploid lines. Genotypes with good induction capacity had not necessarily a good capacity of regeneration of haploid plantlets. In our conditions, Hmira and Khiar exhibited the best gynogenetic ability (3.1% and 2.9% of haploid plantlets, respectively). Keywords: Durum wheat, Genetic variation, Salinity, In vitro gynogenesi