Advancements in technology and innovation for sustainable agriculture: Understanding and mitigating greenhouse gas emissions from agricultural soils

Enhancing collaboration quotient in crop protection research and development - multi-disciplinary cross-learning to promote sustainability

After a decade of consolidation with a focus on top market players, global crop protection research is undergoing a paradigm transition by integrating new cutting-edge technologies originating from established and new research organizations. Both development and distribution organizations are working together to make these innovations available to the global farming community. For this, excellent crop protection products are in demand, creating value for farmers and society with superior biological performance and at the same time very high product safety profiles. However, the enormous constraints researchers are exposed to, require the discovery and development of innovative solutions in the shortest possible time frame, while embracing environmental, social, and governance (ESG) objectives as the new normal across the whole industry. Today, fully integrated research and development (R&D) companies are addressing the whole plethora of agrochemistry, biologicals and plant health products, organic farming, seeds and traits, new application technologies, digital farming, improved diagnostics, artificial intelligence (AI), and machine learning (ML)-based approaches. However, there is still a strong need for further innovations from a wide range of sources. Targeted collaboration across various market players is key to combining required activities. This mandates a high level of discipline to frame the proprietary and knowledge environment across the industry. Furthermore, the cooperation of industry and academia will enable an extra push for innovation in the crop protection landscape. Current trends and suggestions are given of how collaborations need to be framed within the industry as well as within the public sector. © 2024 Society of Chemical Industry.

Raw feedstock vs. biochar from olive stone: Impact on the sorption-desorption of diclosulam and tropical soil improvement

The addition of carbon-rich materials, such as raw feedstocks (RAW) and biochars, to agricultural soils is on the rise. This activity has many advantages, such as improving fertility, increasing water retention, and sequestering carbon. However, they can also increase the sorption of residual herbicides in the soil, reducing the effectiveness of weed control. Thus, the objective of this study was to evaluate soil improvement and the sorption-desorption process of diclosulam in soil unamended and amended with RAW from olive stone and their biochars produced in two pyrolysis temperatures (300 and 500 °C). Oxisol was used in this study, unamended and amended with RAW and biochars (BC300 and BC500) in a rate of 10% (w w-1). The sorption-desorption process was assessed by batch-equilibrium experiments and the analysis was performed using high-performance liquid chromatography (HPLC). The addition of the three materials to the soil increased the contents of pH, organic carbon, P, K, Ca, Mg, Zn, Fe, Mn, Cu, B, cation exchange capacity, base saturation and decreased H + Al. The unamended soil had Kf (Freundlich sorption coefficient) values of diclosulam sorption and desorption of 1.56 and 12.93 mg(1 - 1/n) L1/n Kg-1, respectively. Unamended soil sorbed 30.60% and desorbed 13.40% of herbicide. Soil amended with RAW, BC300, and BC500 sorbed 31.92, 49.88, and 30.93% of diclosulam and desorbed 13.33, 11.67, and 11.16%, respectively. The addition of RAW and biochars from olive stone has the potential to change the soil fertility, but does not interfere with the bioavailability of diclosulam in weed control under field conditions, since the materials slightly influenced or did not alter the sorption-desorption of diclosulam.

Environmental regulation, innovation choices, and agricultural green total factor productivity under a multi-regulatory perspective

As environmental challenges escalate, green development is crucial for sustainability. This study analyzes China's county-level agricultural green total factor productivity using SBM and ML index, introducing a comprehensive index to quantify the impact of different types of environmental regulations on productivity. The findings reveal the following: baseline analysis reveals that comprehensive environmental regulation notably boosts agricultural green total factor productivity (AGTFP), with regulatory intensity positively linked to productivity growth. Other factors like policy intervention, industrial structure, savings levels, and per capita GDP also favorably impact productivity. All three types of regulations, command, incentive, and voluntary type, substantially enhance AGTFP. The mediating effect test results show that all three types of regulations directly and positively impact AGTFP. Indirect effects vary: command-type regulation's mediating effect through independent R&D is significant, accounting for 39% of the impact. For incentive type, both industry structure upgrading (23.79%) and independent R&D (3.1%) mediate the effect. For voluntary type, technological advancement via independent R&D mediates about 13.0% of the impact. Heterogeneity analysis reveals distinct impacts of different environmental regulations on AGTFP across regions. Command-type regulation is most effective in the west, while in the central region, both command- and incentive-type regulations have similar promotional effects. In the east, incentive- and voluntary-type regulations show stronger impacts. Robustness tests, including endogeneity testing, dependent variable substitution, sample winsorizing, and model substitution, consistently confirm the baseline finding that environmental regulation significantly boosts AGTFP.

Cultivating a sustainable future in the artificial intelligence era: A comprehensive assessment of greenhouse gas emissions and removals in agriculture

Agriculture is a leading sector in international initiatives to mitigate climate change and promote sustainability. This article exhaustively examines the removals and emissions of greenhouse gases (GHGs) in the agriculture industry. It also investigates an extensive range of GHG sources, including rice cultivation, enteric fermentation in livestock, and synthetic fertilisers and manure management. This research reveals the complex array of obstacles that are faced in the pursuit of reducing emissions and also investigates novel approaches to tackling them. This encompasses the implementation of monitoring systems powered by artificial intelligence, which have the capacity to fundamentally transform initiatives aimed at reducing emissions. Carbon capture technologies, another area investigated in this study, exhibit potential in further reducing GHGs. Sophisticated technologies, such as precision agriculture and the integration of renewable energy sources, can concurrently mitigate emissions and augment agricultural output. Conservation agriculture and agroforestry, among other sustainable agricultural practices, have the potential to facilitate emission reduction and enhance environmental stewardship. The paper emphasises the significance of financial incentives and policy frameworks that are conducive to the adoption of sustainable technologies and practices. This exhaustive evaluation provides a strategic plan for the agriculture industry to become more environmentally conscious and sustainable. Agriculture can significantly contribute to climate change mitigation and the promotion of a sustainable future by adopting a comprehensive approach that incorporates policy changes, technological advancements, and technological innovations.

The spatial and source heterogeneity of agricultural emissions highlight necessity of tailored regional mitigation strategies

Agriculture contributes considerable greenhouse gas emissions while feed the constantly expanding world population. The challenge of balancing food security with emissions reduction to create a mutually beneficial situation is paramount. However, assessing targeted mitigation potential for agricultural emissions remains challenging, lacking comprehensive sub-national evaluations. Here, we have meticulously compiled the agricultural greenhouse gas emission inventories of China spanning the years 2000 to 2019, employing spatial analysis techniques to identify regional characteristics. We find that the peak of China's agricultural production emissions occurred in 2015 (1.03 × 109 tCO2 equivalent), followed by a valley in 2019 (0.94 tCO2 equivalent), largely attributed to shifts in livestock-related activities. Notably, methane emissions were the most dominant greenhouse gas, the Hunan province emerged as a prominent contributor, livestock raising stood out as a major activity, and enteric fermentation ranked as the primary emission source. There were substantial differences in the emission structure and sources among the provinces. Further spatial analysis showed geographical disparities in both total emissions and per capita emissions. The west-east blocked spatial characteristics of per capita emissions at the Hu Line sides emerged. We advocate that tailored mitigation strategy focusing on specific emission sources and regions can achieve substantial progress with minimal effort.