Soil: the great connector of our lives now and beyond COVID-19

Humanity depends on the existence of healthy soils, both for the production of food and for ensuring a healthy, biodiverse environment, among other functions. COVID-19 is threatening food availability in many places of the world due to the disruption of food chains, lack of workforce, closed borders and national lockdowns. As a consequence, more emphasis is being placed on local food production, which may lead to more intensive cultivation of vulnerable areas and to soil degradation. In order to increase the resilience of populations facing this pandemic and future global crises, transitioning to a paradigm that relies more heavily on local food production on soils that are carefully tended and protected through sustainable management is necessary. To reach this goal, the Intergovernmental Technical Panel on Soils (ITPS) of the Food and Agriculture Organization of the United Nations (FAO) recommends five active strategies: improved access to land, sound land use planning, sustainable soil management, enhanced research, and investments in education and extension

Mexican poppy (Argemone mexicana) control in cornfield using deep learning neural networks: a perspective

Mexican poppy (Argemone mexicana) is a widespread noxious annual weed associated with crops such as corn (Zea mays L.), and this weed is persistent because it produces a seed bank. This invasive weed species must be controlled even in the dry season because Mexican poppy has a deep-reaching root system, which taps water from deep soil layers. Cases of a human death caused by Mexican poppy seeds in South Africa, India, and other Eastern countries were reported from the early years of the twentieth century. However, when weeds are controlled uniformly instead of site-specific or precision farming method across the spatially variable fields, there are environmental pollution challenges. Site-specific weed control techniques have gained interest in the precision farming community over the last years mainly because of Global Positioning System (GPS) applications, and a controlled measure of herbicides are applied where there are weeds in the field, and areas with more clusters of weeds receive the correct amount of herbicide application. Mexican poppy has prickles and is a nuisance to farmers, and herbicides represent a severe health hazard to humans due to chemical concentrations in water. For that reason, we propose the design of a site-specific weed control plan to use a row-guided robot to detect and identify weeds with accuracy, control speed timeously, and spray herbicides with a high level of precision and automation. These robotics methods are reported to be environmentally conscious, and economically efficient with less labour and management. The proposed method of deep learning neural networks, which use row-guided robots, a machine is trained on multiple images to identify weeds automatically from the main crop, and release a controlled measure of herbicides based on weed location and density, and spray weeds on-the-go upon emergence

Coronavirus (COVID-19), environmental safety, and the dynamics of soil management

The 2009 H1N1 influenza pandemic, the epidemic of the Ebola virus, and currently the COVID-19 pandemic is an essential wake-up call for all countries to transform the approach to soil assessment and environmental management, and these diseases have proved how quickly a new virus can spread to every corner of the globe. With so many countries declaring the state of the emergency protocol due to the Coronavirus (COVID-19) pandemic, adopting and intensifying the provisions for the fourth industrial revolution technologies such as robotics and state-of-the-art mobile laboratories could be the only way to transform and expedite the approach to soil assessment, mapping, monitoring, and environmental management. This article proposes the fourth industrial revolution methodologies that can be adapted to assist the farmers and community in managing soils and the environment when the world nations are in a predicament of the pandemic such as COVID-19. The task would be to develop an outdoor automated or semi-autonomous machine vision system (drone or a robot) that can exceptionally substitute human labour on soil management tasks that are critical and cannot be performed by human labour as a result of COVID-19 national lockdown and any other related limitations of infield conventional assessment methods