Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh

Chemical Composition and Nutritive Value of Sea Buckthorn Leaves

Sea buckthorn leaves (SBT_LVs) form notable by-product during harvesting and post-harvest management of the berries. It is already known that sea buckthorn berries are important for their chemical composition and based on this, they occupy a wide field in nutrition. SBT_LVs also have a rich chemical composition, like the berries. The aim of this study was to describe these by-products in the context of protein and complex carbohydrates-dietary fiber fractions, including qualitative and quantitative composition of amino acids. Proximate composition, amino acids, nutritional values of the protein, and dietary fiber fractions of SBT_LVs of four cultivars (cvs.) Ascola, Habego, Hergo, and Leikora were assessed. SBT_LVs from different years of the study had statistically different levels of crude protein, ether extract, crude ash, and nitrogen-free extract (NFE), confirming that the quality of the raw material (leaves) can be significantly modified by habitat conditions. The largest fraction of dietary fiber was neutral detergent fiber (NDF), including the sum of hemicellulose, cellulose, and lignin, followed by the acid detergent fiber fraction (ADF), consisting of lignin and cellulose. The content of essential amino acids in SBT_LV protein was high. Overall, this study confirms that SBT_LVs hold promise as a valuable resource for use as a food ingredient, functional food, and dietary supplement for both humans and animals.

Influencing factors and spatiotemporal heterogeneity of livestock greenhouse gas emission: Evidence from the Yellow River Basin of China

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO2e) in 2000 to 77.568 Mt CO2e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively.

Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh

High-resolution mapping of rice fields is crucial for understanding and managing rice cultivation in countries like Bangladesh, particularly in the face of climate change. Rice is a vital crop, cultivated in small scale farms that contributes significantly to the economy and food security in Bangladesh. Accurate mapping can facilitate improved rice production, the development of sustainable agricultural management policies, and formulation of strategies for adapting to climatic risks. To address the need for timely and accurate rice mapping, we developed a framework specifically designed for the diverse environmental conditions in Bangladesh. We utilized Sentinel-1 and Sentinel-2 time-series data to identify transplantation and peak seasons and employed the multi-Otsu automatic thresholding approach to map rice during the peak season (April-May). We also compared the performance of a random forest (RF) classifier with the multi-Otsu approach using two different data combinations: D1, which utilizes data from the transplantation and peak seasons (D1 RF) and D2, which utilizes data from the transplantation to the harvest seasons (D2 RF). Our results demonstrated that the multi-Otsu approach achieved an overall classification accuracy (OCA) ranging from 61.18% to 94.43% across all crop zones. The D2 RF showed the highest mean OCA (92.15%) among the fourteen crop zones, followed by D1 RF (89.47%) and multi-Otsu (85.27%). Although the multi-Otsu approach had relatively lower OCA, it proved effective in accurately mapping rice areas prior to harvest, eliminating the need for training samples that can be challenging to obtain during the growing season. In-season rice area maps generated through this framework are crucial for timely decision-making regarding adaptive management in response to climatic stresses and forecasting area-wide productivity. The scalability of our framework across space and time makes it particularly suitable for addressing field data scarcity challenges in countries like Bangladesh and offers the potential for future operationalization.

Nutritional Value of Banded Cricket and Mealworm Larvae

Insect farming is more ecological than traditional animal farming, as it requires less water and contributes to lower greenhouse gas emissions. In our study, banded cricket (BC) and mealworm larvae (ML) were analyzed. The proximate composition was determined according to Association of Official Analytical Chemists. The mineral content was determined by colorimetry and mass spectrometry. Fatty acid methyl esters (FAMEs) were obtained from the samples and separated using a gas chromatography apparatus, coupled with a mass spectrometer. Our research confirmed that insects are a rich source of protein, with ML containing significantly more protein than BC (74.41 and 65.66 g/100 g dry matter (DM), respectively). In terms of the content of macrominerals, ML was significantly richer than BC, especially in terms of magnesium content (8.75 g/100 g DM). In terms of the content of saturated fatty acids, BC contained almost twice as much as ML (40.05 and 24.74% of the sum of fatty acids, respectively). EPA and DHA were only detected in the fat of BC. The presented results prove that both ML and BC can be good sources of protein both in human and companion animal diets. The component that is predominantly high in insects is fat, with a favorable fatty acid profile, especially in terms of polyunsaturated fatty acids. This study contributes new knowledge on the nutritional value of edible insects. In this research, we included three different nitrogen conversion factors for crude protein content. Our results partially confirm previous studies by other authors, although they provide new information on the content of fatty acids.

Impact of cropping system diversification on productivity and resource use efficiencies of smallholder farmers in south-central Bangladesh: a multi-criteria analysis

Diversification of smallholder rice-based cropping systems has the potential to increase cropping system intensity and boost food security. However, impacts on resource use efficiencies (e.g., nutrients, energy, and labor) remain poorly understood, highlighting the need to quantify synergies and trade-offs among different sustainability indicators under on-farm conditions. In southern coastal Bangladesh, aman season rice is characterized by low inputs and low productivity. We evaluated the farm-level impacts of cropping system intensification (adding irrigated boro season rice) and diversification (adding chili, groundnut, mungbean, or lathyrus) on seven performance indicators (rice equivalent yield, energy efficiency, partial nitrogen productivity, partial potassium productivity, partial greenhouse gas footprint, benefit-cost ratio, and hired labor energy productivity) based on a comprehensive survey of 501 households. Indicators were combined into a multi-criteria performance index, and their scope for improvement was calculated by comparing an individual farmer's performance to top-performing farmers (highest 20%). Results indicate that the baseline system (single-crop aman season rice) was the least productive, while double cropped systems increased rice equivalent yield 72-217%. Despite gains in productivity, higher cropping intensity reduced resource use efficiencies due to higher inputs of fertilizer and energy, which also increased production costs, particularly for boro season rice. However, trade-offs were smaller for diversified systems including legumes, largely owing to lower N fertilizer inputs. Aman season rice had the highest multi-criteria performance index, followed by systems with mungbean and lathyrus, indicating the latter are promising options to boost food production and profitability without compromising sustainability. Large gaps between individual and top-performing farmers existed for each indicator, suggesting significant scope for improvement. By targeting indicators contributing most to the multi-criteria performance index (partial nitrogen productivity, energy efficiency, hired labor energy productivity), results suggest further sustainability gains can be achieved through future field research studies focused on optimizing management within diversified systems.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13593-022-00795-3.

Insects in Pet Food Industry-Hope or Threat?

Due to the increasing global population, the world cannot currently support the well-known techniques of food production due to their harmful effects on land use, water consumption, and greenhouse gas emissions. The key answer is a solution based on the use of edible insects. They have always been present in the diet of animals. They are characterized by a very good nutritional value (e.g., high protein content and contents of essential amino acids and fatty acids, including lauric acid), and products with them receive positive results in palatability tests. Despite the existing literature data on the benefits of the use of insects as a protein source, their acceptance by consumers and animal caregivers remains problematic. In spite of the many advantages of using insects in pet food, it is necessary to analyze the risk of adverse food reactions, including allergic reactions that may be caused by insect consumption. Other hazards relate to the contamination of insects. For example, they can be contaminated with anthropogenic factors during breeding, packaging, cooking, or feeding. These contaminants include the presence of bacteria, mold fungi, mycotoxins, and heavy metals. However, insects can be used in the pet food industry. This is supported by the evolutionary adaptation of their wild ancestors to the eating of insects in the natural environment. The chemical composition of insects also corresponds to the nutritional requirements of dogs. It should be borne in mind that diets containing insect and their effects on animals require careful analysis. The aim of this article is to discuss the nutritional value of insects and their possible applications in the nutrition of companion animals, especially dogs.

Spatially explicit database on crop-livestock management, soil, climate, greenhouse gas emissions and mitigation potential for all of Bangladesh

This data article provides spatially explicit data on greenhouse gas (GHG) emissions and mitigation potential at various administrative levels for the whole of Bangladesh. The results arising from analysis of this database are presented in research article "Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh" [1]. We collected crop and livestock management data and associated soil and climatic data from variety of primary and secondary sources outlined below in our methodology. The datafiles on crops and livestock contain model outputs for three greenhouse gases (CO2, CH4 and N2O) and their global warming potential, which are linked, to the information on crop/livestock management, soil and climatic conditions presented in the supplementary data of the associated manuscript. The datafiles on mitigation potential contain district-level annual GHG mitigation potential by 2030 and 2050 segregated by different crops/livestock types and mitigation options. This dataset is useful for Bangladesh's GHG accounting from the agricultural sector, and can be used to update its nationally determined contributions. Administrative level emissions and mitigation potential estimates segregated by crop-livestock types and mitigation options are useful to prioritize agricultural research and development interventions consistent with food security and environmental goals and to organize agricultural extension and support services to better inform farmers on food production and move towards GHG mitigation goals.