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In order to improve the estimation accuracy of soil organic matter, this paper aims to establish a modified model for hyperspectral estimation of soil organic matter content based on the positive and inverse grey relational degrees.

Based on 82 soil sample data collected in Daiyue District, Tai'an City, Shandong Province, firstly, the spectral data of soil samples are transformed by the first order differential and logarithmic reciprocal first order differential and so on, the correlation coefficients between the transformed spectral data and soil organic matter content are calculated, and the estimation factors are selected according to the principle of maximum correlation. Secondly, the positive and inverse grey relational degree model is used to identify the samples to be identified, and the initial estimated values of the organic matter content are obtained. Finally, based on the difference information between the samples to be identified and their corresponding known patterns, a modified model for the initial estimation of soil organic matter content is established, and the estimation accuracy of the model is evaluated using the mean relative error and the determination coefficient.

The results show that the methods of logarithmic reciprocal first order differential and the first-order differential of the square root for transforming the original spectral data are more effective, which could significantly improve the correlation between soil organic matter content and spectral data. The modified model for hyperspectral estimation of soil organic matter has high estimation accuracy, the average relative error (MRE) of 11 test samples is 4.091%, and the determination coefficient (R²) is 0.936. The estimation precision is higher than that of linear regression model, BP neural network and support vector machine model. The application examples show that the modified model for hyperspectral estimation of soil organic matter content based on positive and inverse grey relational degree proposed in this article is feasible and effective.

The model in this paper has clear mathematical and physics meaning, simple calculation and easy programming. The model not only fully excavates and utilizes the internal information of known pattern samples with “insufficient and incomplete information”, but also effectively overcomes the randomness and grey uncertainty in the spectral estimation of soil organic matter. The research results not only enrich the grey system theory and methods, but also provide a new approach for hyperspectral estimation of soil properties such as soil organic matter content, water content and so on.

The paper succeeds in realizing both a modified model for hyperspectral estimation of soil organic matter based on the positive and inverse grey relational degrees and effectively dealing with the randomness and grey uncertainty in spectral estimation.

The service environment of urban polyethylene (PE) pipes has a crucial influence on their long-term safety and performance. Based on the application and structural performance analysis of PE pipe failure cases, this study aims to investigate the impact of organic substances in the soil on the aging behavior of PE pipes by designing organic solutions with different concentrations, which are based on the composition of organic substances in the soil environment, and periodic immersion tests.

Soil samples in the vicinity of the failed pipes were analyzed by gas chromatography-mass spectrometry, sensitive organic substances were screened and soaking solutions of different concentrations were designed. After the soaking test, the PE pipe samples were analyzed using differential scanning calorimetry, Fourier-transform infrared spectroscopy and other testing methods.

The performance difference between the outer surface and the middle of the cross section of PE pipes highlights the influence of the soil service environment on their aging. Different organic solutions can have varying impacts on the aging behavior of PE pipes when immersed. For instance, when exposed to amine organic solutions, PE pipes may have an increased weight and decreased material yield strength, although there is no reduction in their thermal or oxygen stability. On the contrary, when subjected to ether organic solutions, the surface of PE pipe specimens may be affected, leading to a reduction in material fracture elongation and a decrease in their thermal and oxygen stability. Furthermore, immersion in either amine or ether organic solutions may result in the production of hydroxyl and other aging groups on the surface of the material.

Understanding the potential impact of organic substances in the soil environment on the aging of PE pipe ensures the long-term performance and safety of urban PE pipe. This research approach will provide valuable insights into improving the durability and reliability of urban PE pipes in soil environments.

The present study focused on examining the effect of treated wastewater (TWW) on soil chemical properties. Also, efforts were made to compare the soil chemical properties under TWW irrigation with that under groundwater (GW).

During the years 2021 and 2022, surface and subsurface soil samples were randomly collected in triplicate by using an auger fortnightly at two depths (20 and 40 cm) from the selected spot areas to represent the different types of irrigation water sources: TWW and GW. Samples of the GW and the TWW were collected for analysis.

This study examines the impact of TWW on soil characteristics and the surrounding environment. TWW use enhances soil organic matter, nutrient availability and salt redistribution, while reducing calcium carbonate accumulation in the topsoil. However, it negatively affects soil pH, electrical conductivity and sodium adsorption ratio, although remaining within acceptable limits. Generally, irrigating with TWW improves most soil chemical properties compared to GW.

In general, almost all of the soil’s chemical properties were improved by irrigating with TWW rather than GW. Following that, wastewater is used to irrigate the soil. Additionally, the application of gypsum to control the K/Na and Ca/Na ratios should be considered under long-term TWW and GW usage in this study area in order to control the salt accumulation as well as prevent soil conversion to saline-sodic soil in the future. However, more research is needed to thoroughly investigate the long-term effects of using TWW on soil properties as well as heavy metal accumulation in soil.

This paper finds the returns from soil conservation practices and examines whether the welfare implications of adopting the conservation practices are heterogeneous across the farming groups in Indian agriculture.

The study uses an endogenous switching regression (ESR) method on the data collected from the 77th round of National Sample Survey (2019–21) to quantify the returns from adopting soil conservation practices.

It finds that farmers adopting soil health conservation practices would have reduced their crop yield by 13% if they did not implement them. Similarly, smallholders who have not adopted soil health management practices would have increased crop yield by 16% if they had adopted the practices. The authors also observed that the returns from adopting soil health management practices vary across farming groups, where marginal and large farms tend to gain higher yields. Finally, the authors find that regardless of farm size, smallholders who did not adopt soil health management practices would benefit from adopting these with increased crop yields of 29%–31%.

More data could have been better for drawing policy implications, since the number of soil card users are relatively less.

This research work uses nationally representative data, which is first in nature on this very aspect.

There is an urgent need to develop climate-smart agrosystems capable of mitigating climate change and adapting to its effects. Conventional agricultural practices prevail in Mauritius, whereby synthetic chemical fertilizers, pesticides and insecticides are used. It should be noted that Mauritius remains a net-food importing developing country of staple food such as cereals and products, roots and tubers, pulses, oil crops, vegetables, fruits and meat (FAO, 2011). In Mauritius, the agricultural sector faces extreme weather conditions like drought or heavy rainfall. Moreover, to increase the crop yields, farmers tend to use 2.5 times the prescribed amount of fertilizers in their fields. These excess fertilizers are washed away during heavy rainfall and contaminate lakes and river waters. By using smart irrigation and fertilization system, a better management of soil water reserves for improved agricultural production can be implemented. Soil Nitrogen, Phosphorus and Potassium (NPK) content, humidity, pH, conductivity and moisture data can be monitored through the cloud platform. The data will be processed at the level of the cloud and an appropriate mix of NPK and irrigation will be used to optimise the growth of the crops. Machine learning algorithms will be used for the control of the land drainage, fertilization and irrigation systems and real time data will be available through a mobile application for the whole system. This will contribute towards the Sustainable Development Goals (SDGs): 2 (Zero Hunger), 11 (Sustainable cities and communities), 12 (Responsible consumption and production) and 15 (Life on Land). With this project, the yield of crops will be boosted, thus reducing the hunger rate (SDG 2). On top of that, this will encourage farmers to collect the waters and reduce fertilizer consumption thereafter sustaining the quality of the soil on which they are cultivating the crops, thereby increasing their yields (SDG 15).

The aim of this paper is to assess whether the current European target to increase the areas under organic farming to 25% by 2030 is attainable and whether the simple increase in areas under organic farming may be sufficient to improve the sustainability of European agriculture.

The analysis has been carried out through a simple data processing related to areas under organic farming, for the period 2012–2020 (Eurostat database), in order to highlight the trends of areas under organic farming and to verify whether the annual average change rates may be compatible with the stated target.

The analysis showed that organic farming has a productive weight not corresponding to the amount on the total of the areas under cultivation and a small impact on the total of food consumption. It is a plausible hypothesis, the one that shows the increase in areas under organic farming will engage forms of agriculture and farms that, already, are more sustainable, so the achievement of 25% target will not particularly impact the European potential productive and the less environmental sustainable forms of agriculture.

This paper contributes to the debate, involving scientific community, policy maker and civil society, about the real contribution of organic farming to sustainability, and it will be developed in future research.

The purpose of this paper is to investigate the effects of climate smart agriculture knowledge transfers. As well as to examine the application of climate-smart agricultural (CSA) knowledge such as conservation agriculture, irrigation systems, integrated soil fertility management, bioenergy and agroforestry by smallholder farmers in Kenya.

The study applied comparative research methodology to compare climate smart agriculture knowledge application between smallholder participants in farmer field schools (FFS) and no FFS participation. This study used household data from 759 randomly selected rural agricultural households in three counties in Kenya. The study applied multivariate probit model to estimate CSA knowledge application by farmers who participated in field trainings and non-FFS participation farmers.

This study established that climate smart agriculture knowledge transfer through FFS increases farmers’ application of critical aspects of climate smart agriculture knowledge practices such as irrigation system, conservation agriculture and soil and water conservation. Such aspects have been noted as effective interventions against adverse climate change effects such as persistent droughts and flooding and soil infertility. Further findings illustrated that farmers who received CSA knowledge transfers applied agricultural insurance to mitigate rising climatic risks on their farms. Knowledge transfer interventions targeting affordability through subsidizing agricultural insurance are probable and more cost-effective measures that can be used to reduce smallholder farmers’ exposure to climate change-related risks.

This study provides information that was previously unknown about climate smart agriculture knowledge transfers and application among farmers who participated in field trainings and non-FFS participation farmers by using empirical data.

There is growing interest around the world in more effectively linking public payments to the provision of public goods from agriculture. However, published evidence syntheses suggest mixed, weak or uncertain evidence for many agri-environment scheme options. To inform any future “public money for public goods” based policy, further synthesis work is needed to assess the evidence-base for the full range of interventions currently funded under agri-environment schemes. Further empirical research and trials should then focus on interventions for which there is mixed or limited evidence. Furthermore, to ensure the data collected is comparable and can be synthesised effectively, it is necessary to reach agreement on essential variables and methods that can be prioritised by those conducting research and monitoring. Future policy could then prioritise public money for the public goods that can most reliably be delivered, offering better value for taxpayers and improving the provision of ecosystem services from agricultural landscapes.

From the perspective of any nation, rural areas generally present a comparable set of problems, such as a lack of proper healthcare, education, living conditions, wages and market opportunities. Some nations have created and developed the concept of smart villages during the previous few decades, which effectively addresses these issues. The landscape of traditional agriculture has been radically altered by digital agriculture, which has also had a positive economic impact on farmers and those who live in rural regions by ensuring an increase in agricultural production. We explored current issues in rural areas, and the consequences of smart village applications, and then illustrate our concept of smart village from recent examples of how emerging digital agriculture trends contribute to improving agricultural production in this chapter.

Human actions on natural ecosystems have not only jeopardized human well-being but also threatened the existence of other species. On the other hand, the benefits resulting from a greater integration between the logic of nature and human occupations have been seen as motivating factors for the prevention and mitigation of environmental impacts in landscape planning, since it provides human well-being through the grant of resources, regulation of the environment and socio-cultural services called ecosystem services. This article highlights the relevance of using ecosystem integrity indicators related to the functioning of ecological support processes for landscape planning.

The research used the photosynthetic performance of vegetation through carbon fluxes in the landscape, defining areas where different approaches to green infrastructure can be applied, gaining over the majority of work in this area, in which low degrees of objectivity on measurement and consequent ecological recovery still prevail. Thus, using the conceptual support of restoration ecology and remote sensing, the work identified different vegetation performances in relation to the supporting ecological processes using the multispectral CO₂flux index, linked to the carbon flux to identify the photosynthetic effectiveness of the vegetation and the Topographic Wetness Index (TWI).

With a study in the Distrito Federal (DF), the results of the different performances of vegetation for ecological support, through electromagnetic signatures and associated vegetation formations, allowed for the identification of hotspots of greater integrity that indicate multifunctional areas to be preserved and critical areas that deserve planning actions using green infrastructure techniques for their restoration and integration into the landscape.

This approach could be the initial step towards establishing clear and assertive criteria for selecting areas with greater potential for the development of supporting ecological processes in the territorial mosaic.