Spatially and Temporally Explicit Life Cycle Environmental Impacts of Soybean Production in the U.S. Midwest

Assessment of the environmental impacts of soybean production within fields in Madhya Pradesh: a life cycle analysis approach

Soybean is a versatile crop that can be used as an oilseed or food crop. Increasing soybean production is beneficial to agricultural economies, but significant concerns have been raised about its environmental impacts. This study evaluates the environmental footprint of soybean production using life cycle assessment (LCA) within the "cradle-to-gate" system in Madhya Pradesh (central India) for the first time. The analysis demonstrated that untreated residue on the ground increases the global warming potential by 19.78 kg CO2 eq ha-1 and land use emissions by 3.61 m2a crop eq ha-1. Additionally, burning residue significantly increases global warming potential by 210.80 kg CO2 eq. ha-1. Furthermore, the potential for aquatic eutrophication ranges between 0.38 and 0.80 kg N eq. and between 0.16 and 0.21 kg P eq ha-1 for marine and freshwater systems, respectively. This assessment reinforces that global warming potential, fossil resource scarcity, acidification, and land use emissions are the primary environmental concerns linked to soybean cultivation. These issues predominantly arise from fuel combustion in agricultural machinery and the application of soil nutrients throughout the production process. This investigation provides a basis for informed decision-making and the development of sustainable practices to balance the agricultural significance of soybean with environmental considerations.

Comparing life cycle environmental impacts of food access and consumption pre- and during COVID 19 in New York State's Capital Region

The COVID-19 pandemic has significantly influenced household food shopping, food consumption, and food waste generation. However, the dietary environmental impacts for different income groups during COVID-19 remain unknown. To analyze dietary environmental impacts for various income groups, a process-based life cycle assessment (LCA) was conducted based on two electronic food access surveys implemented in the New York State's Capital Region during the COVID-19 pandemic and public and proprietary databases. We found that life cycle global warming potential, cumulative energy demand, acidification potential, and water resource depletion of per capital food consumption in the studied area tended to be lower during COVID-19 than pre-COVID-19. In contrast, life cycle eutrophication during COVID-19 was slightly higher than pre-COVID-19. The environmental impacts occurring at the food production stage were higher than those at the local transportation and waste disposal stages. The lowest income group had the lowest dietary environmental impacts due to their lowest food consumption of all the food categories. The second-highest income group had the highest dietary environmental impacts, since they consumed the most red meat which has a high impact intensity. This is the first study to our knowledge to investigate the differences in dietary environmental impacts among income groups during COVID-19.

Climate adaptation through crop migration requires a nexus perspective for environmental sustainability in the North China Plain

Crop migration can moderate the impacts of global warming on crop production, but its feedback on the climate and environment remains unknown. Here we develop an integrated framework to capture the climate impacts and the feedback of adaptation behaviours with the land-water-energy-carbon nexus perspective and identify opportunities to achieve the synergies between climate adaptation and environmental sustainability. We apply the framework to assess wheat and maize migration in the North China Plain and show that adaptation through wheat migration could increase crop production by ~18.5% in the 2050s, but at the cost of disproportional increment in land use (~19.2%), water use (~20.2%), energy use (~19.5%) and carbon emissions (~19.9%). Irrigation and fertilization management are critical mitigation opportunities in the framework, through which wheat migration can be optimized to reduce the climatic and environmental impacts and avoid potential carbon leakage. Our work highlights the sustainable climate adaptation to mitigate negative environmental externalities.

Toward Low-Carbon Rice Production in China: Historical Changes, Driving Factors, and Mitigation Potential

Under the "Double Carbon" target, the development of low-carbon agriculture requires a holistic comprehension of spatially and temporally explicit greenhouse gas (GHG) emissions associated with agricultural products. However, the lack of systematic evaluation at a fine scale presents considerable challenges in guiding localized strategies for mitigating GHG emissions from crop production. Here, we analyzed the county-level carbon footprint (CF) of China's rice production from 2007 to 2018 by coupling life cycle assessment and the DNDC model. Results revealed a significant annual increase of 74.3 kg CO2-eq ha-1 in the average farm-based CF (FCF), while it remained stable for the product-based CF (PCF). The CF exhibited considerable variations among counties, ranging from 2324 to 20,768 kg CO2-eq ha-1 for FCF and from 0.36 to 3.81 kg CO2-eq kg-1 for PCF in 2018. The spatiotemporal heterogeneities of FCF were predominantly influenced by field CH4 emissions, followed by diesel consumption and soil organic carbon sequestration. Scenario analysis elucidates that the national total GHG emissions from rice production could be significantly reduced through optimized irrigation (48.5%) and straw-based biogas production (18.0%). Moreover, integrating additional strategies (e.g., advanced crop management, optimized fertilization, and biodiesel application) could amplify the overall emission reduction to 76.7% while concurrently boosting the rice yield by 11.8%. Our county-level research provides valuable insights for the formulation of targeted GHG mitigation policies in rice production, thereby advancing the pursuit of carbon-neutral agricultural practices.

Soy Milk Consumption in the United States of America: An NHANES Data Report

With the increasing adoption of plant-based diets in the United States, more and more individuals replace cow milk with plant-based milk alternatives. Soy milk is a commonly used cow milk substitute, which is characterized by a higher content of polyunsaturated fatty acids and fibers. Despite these favorable characteristics, little is known about the current prevalence of soy milk consumption the United States. We used data from the National Health and Nutrition Examination Surveys (NHANES) to assess soy milk usage in the United States and identified potential predictors for its consumption in the US general population. The proportion of individuals reporting soy milk consumption in the NHANES 2015-2016 cycle was 2%, and 1.54% in the NHANES 2017-2020 cycle. Non-Hispanic Asian and Black ethnicities (as well as other Hispanic and Mexican American ethnicities in the 2017-2020 cycle) significantly increased the odds for soy milk consumption. While a college degree and weekly moderate physical activity were associated with significantly higher odds for consuming soy milk (OR: 2.21 and 2.36, respectively), sex was not an important predictor. In light of the putative health benefits of soy milk and its more favorable environmental impact as compared to cow milk, future investigations should attempt to identify strategies that may help promote its consumption in selected populations.

Environmental impacts of eco-nutrition swine feeding programs in spatially explicit geographic regions of the United States

This study was conducted to determine greenhouse gas (GHG) emissions, water consumption, land use, as well as nitrogen (N), phosphorus (P), and carbon (C) balance of five diet formulation strategies and feeding programs for growing-finishing pigs (25-130 kg body weight) in the three spatially explicit geographic regions where the majority of U.S. pork production occurs. Feeding programs evaluated consisted of 1) standard corn-soybean meal (CSBM) diets, 2) CSBM containing 15% corn distillers dried grains with solubles (DDGS), 3) CSBM with 8.6% thermally processed supermarket food waste (FW), 4) low crude protein CSBM diets supplemented with synthetic amino acids (SAA), and 5) CSBM with phytase enzyme (PHY) added at 600 FTU (phytase units)/kg of diet. An attributional Life Cycle Assessment approach using a highly specialized, spatially explicit Food System Supply-Chain Sustainability (FoodS3) model was used to quantify GHG emissions, water consumption, and land use of corn, soybean meal, and DDGS based on county level sourcing. The DDGS, FW, and SAA feeding programs had less estimated N and P intake and excretion than CSBM, and the PHY feeding program provided the greatest reduction in P excretion. The FW feeding program had the least overall GHG emissions (319.9 vs. 324.6 to 354.1 kg CO2 equiv./market hog), land use (331.5 vs. 346.5 to 385.2 m2/market hog), and water consumption (7.64 vs. 7.70 to 8.30 m3/market hog) among the alternatives. The DDGS feeding program had the greatest GHG emissions (354.1 kg CO2 equiv./market hog) among all programs but had less impacts on water consumption (7.70 m3) and land use (346.5 m2) per market hog than CSBM and PHY. The SAA feeding program provided a 6.5-7.4% reduction in land use impacts compared with CSBM and PHY, respectively. Regardless of feeding program, the Midwest had the least contributions to GHG emissions and land use attributed to feed and manure among regions. Water consumption per market hog associated with feeding programs was much greater in the Southwest (59.66-63.58 m3) than in the Midwest (4.45-4.88 m3) and Mid-Atlantic (1.85-2.14 m3) regions. Results show that diet composition and U.S. geographic region significantly affect GHG emissions, water consumption, and land use of pork production systems, and the potential use of thermally processed supermarket food waste at relatively low diet inclusion rates (<10%) can reduce environmental impacts compared with other common feeding strategies.

Closing Greenhouse Gas Emission Gaps of Staple Crops in China

China is facing the dual challenge of achieving food security and agricultural carbon neutrality. Developing spatially explicit crop emission profiles can help inform policy to mitigate agricultural greenhouse gases (GHGs), but previous life-cycle studies were conducted mostly at national and provincial levels. Here, we estimate county-level carbon footprint of China's wheat and maize production based on a nationwide survey and determine the contribution of different strategies to closing regional emission gaps. Results show that crop carbon footprint varies widely between regions, from 0.07 to 3.00 kg CO₂e kg^-1 for wheat and from 0.09 to 2.30 kg CO₂e kg^-1 for maize, with inter-county variation generally much higher than interprovince variation. Hotspots are mainly concentrated in Xinjiang and Gansu provinces, owing to intensive irrigation and high plastic mulch and fertilizer inputs. Closing the regional emission gaps would benefit mostly from increasing crop yields and nitrogen use efficiency, but increasing manure use (e.g., in Northeast, East, and Central China) and energy use efficiency (e.g., in North and Northwest China) can also make important contributions. Our county-level carbon footprint estimates improve upon previous broad-scale results and will be valuable for detailed spatial analysis and the design of localized GHG mitigation strategies in China.

Biomolecular characterisation of marine microalga in comparison to fishmeal and soymeal as an alternative feed ingredient

INTRODUCTION

Marine microalgae protein has better solubility and digestibility than other protein-based feeds. Apart from protein, high-value biomolecules have an immense potential to enhance the quality of feed, but knowledge about them is scarce.

OBJECTIVE

Marine microalga Picochlorum sp. biomass molecular characterisation along with commonly used protein feed such as fishmeal and soymeal for potential feed ingredients.

METHODOLOGY

Liquid chromatography coupled with mass spectrometry (LC-MS) was used for biomolecular characterisation. The correlation of biomolecules sets was evaluated using principal component analysis (PCA) and heatmap clustering.

RESULTS

LC-MS identified 116 biomolecules cumulatively among microalga, fishmeal, and soymeal that includes fatty acids, acylglycerols, vitamins, sterols, pigments, nucleotides, unique amino acids, amines, sugars and miscellaneous. These 116 biomolecules were screened based on their functional importance as feed ingredients. Among the different sets of biomolecules, microalga contained a more diverse set of fatty acids, pigments, sterols, and vitamins than acylglycerols, unique amino acids, nucleotides, and sugars. Fishmeal contained a more diverse set of acylglycerols, unique amino acids, nucleotides, and amines, while soymeal contained the highest number of sugars and miscellaneous biomolecules. The PCA confirmed the significance level (P > 95%) and heatmap clustering showed the diversity and relatedness of biomolecules among the microalga, fishmeal, and soymeal.

CONCLUSION

This study showed that the marine microalga Picochlorum sp. biomass has a rich source of biomolecules and could complement fishmeal or soymeal in feed and is also sustainable and economical as compared to fishmeal and soymeal.

Life Cycle Assessment of Biofuels

Life cycle assessment (LCA) assesses the environmental burdens or impacts of products from cradle to grave. It is also possible to assess such burdens or impacts for parts of the life cycle. A brief overview is given of LCA methodology. A number of choices have to be made in the goal and scope definition, inventory analysis, and impact assessment stages of life cycle assessments. Such choices can have substantial impacts on LCA outcomes. There are uncertainties in outcomes linked to inventory data and modeling. In the case that future biofuels and production processes are studied, assessment outcomes are characterized by relatively large uncertainties. Choices and uncertainties should be considered in the interpretation stage of life cycle assessments. Methodologies applied to several important environmentally relevant aspects of biofuel life cycles are discussed. These aspects are: emissions of substances impacting climate, depletion of virtually nonrenewable abiotic resources, primary energy demand, and water footprint. LCA can be useful in identifying life cycle stages and processes that are major contributors to environmental burdens, for determining the energetic return on energy invested in biofuels, for the identification of environmental trade-offs, and for comparing the life cycle environmental burdens of products.

Estimation of Unit Process Data for Life Cycle Assessment Using a Decision Tree-Based Approach

Lacking unit process data is a major challenge for developing life cycle inventory (LCI) in life cycle assessment (LCA). Previously, we developed a similarity-based approach to estimate missing unit process data, which works only when less than 5% of the data are missing in a unit process. In this study, we developed a more flexible machine learning model to estimate missing unit process data as a complement to our previous method. In particular, we adopted a decision tree-based supervised learning approach to use an existing unit process dataset (ecoinvent 3.1) to characterize the relationship between the known information (predictors) and the missing one (response). The results show that our model can successfully classify the zero and nonzero flows with a very low misclassification rate (0.79% when 10% of the data are missing). For nonzero flows, the model can accurately estimate their values with an R² over 0.7 when less than 20% of data are missing in one unit process. Our method can provide important data to complement primary LCI data for LCA studies and demonstrates the promising applications of machine learning techniques in LCA.