Sustainable Agriculture Research Articles

IoT- enabled crop waste mulching machine for sustainable farming: perspective of circular economy

Abstract A large amount of crop waste is generated after crop harvesting. A substantial quantity of waste on the farm is burnt to clear the field, contributing to environmental harm and global warming. The study aims to develop a technological solution for crop waste management (CWM) by designing and developing an IoT-enabled crop waste mulching machine. This initiative addresses the environmental and health issues caused by burning crop waste on farms. The research involves designing and developing an IoT-enabled mulching machine that can be attached to the back side of a tractor. The machine consists of power-transmitting elements, supports, and mechanisms to distribute mulching material evenly onto the plant bed. It incorporates advanced IoT load cell sensors, soil moisture sensors, and proximity sensors to optimize the mulching process based on soil moisture content and to prevent machinery blockages. The IoT-enabled mulching machine effectively manages crop waste by utilizing it in mulch, thus preventing the harmful practice of burning waste. This machine ensures a more efficient, safer, and environmentally friendly approach to mulching, offering significant improvements over traditional manual mulching methods. The novelty of this research lies in integrating IoT technologies within mulching machine. The mulching machine uses sensors to automate and optimize the mulching process, representing a significant technological advancement over conventional methods. The study offers practical benefits by reducing labour requirements, minimizing the risk of injuries, and ensuring a more uniform mulch application. This technology facilitates more sustainable farming practices, aligning with global sustainability goals. The study can potentially revolutionize the agricultural equipment manufacturing industry (AEMI) by shifting the focus toward environmental sustainability. It promotes replacing plastic film mulching machines with more eco-friendly crop waste mulching solutions. This technology has the potential to reduce air pollution, carbon emissions, and mitigate climate. It also enhances soil health through better mulching practices.

Microbial Indoor Air Quality Within Greenhouses and Polytunnels Is Crucial for Sustainable Horticulture (Malopolska Province, Poland Conditions)

Sustainable horticulture is crucially based on the greenhouse production of vegetables under controlled conditions. In this study, we wanted to learn how cultivated plants may impact indoor air quality and whether the workers can be exposed to bioaerosols in a similar way in these settings. The study objective was to test the hypothesis that the microbial concentrations, distribution of bioaerosol particle sizes, and composition of the airborne microbiome are specific to greenhouses, polytunnels, and open-air sites. The air samples were collected to assess the concentration of total culturable bacteria (TCB), fungi, actinomycetes, and β-haemolytic bacteria and for the identification of bacterial and fungal strains. Higher concentrations of TCB and fungi were found in the greenhouse (log 3.71 and 3.49 cfu m−3, respectively) than in polytunnels (log 2.60–2.48 and 2.51–2.31 cfu m−3, respectively) during the vegetation of cucumbers. These airborne microbes were represented by a significant contribution of the respirable fraction with a distinct contribution of fine particles in size below 4.7 µm. Cultivation of cucumbers resulted in the higher emission of airborne microorganisms in contrast with growing herbs such as oregano and basil. In total, 35 different bacteria and 12 fungal species, including pathogenic or allergenic agents, were identified within the studied sites. The workers can be exposed to increased concentrations of TCB and fungi in the greenhouse during the plant vegetation. It might be recommended to properly manage greenhouses and polytunnels, dispose of dust sources, and maintain appropriate ventilation to sustain relevant air quality.

Biochemical composition of Armenian chili pepper varieties: insights for functional food applications

Background: Capsicum annuum L. (pepper) is economically significant in many countries, including Armenia, where it helps conserve the vegetable gene pool and supports public health. Its rich biochemical composition makes it a key dietary component, particularly for its antioxidant properties, which combat free radicals. The biochemical makeup of peppers vary by genotype and maturity, leading breeders to develop varieties with both agronomic and nutritional benefits. Chili peppers are especially valued for their high carotene and ascorbic acid content, earning them the title of "multi vitamin concentrate," along with other vitamins and bioactive compounds that enhance their health benefits. Objective: This study examines the biochemical profiles of various Armenian chili pepper varieties, highlighting their nutritional value and potential in agricultural systems. By analysing these unique varieties, the research aims to advance knowledge of their health benefits and promote sustainable farming practices. Methods: The study examined six locally bred chili pepper varieties—'Artsiv', 'Punj', 'Kon', 'Deghin kakach', 'Oranj kakach', and 'Kaytsak'. Ascorbic acid, carotenoids, and phenols were measured at both the technical and biological ripening stages using spectrophotometry. Dry matter was determined by the thermogravimetric method, and sugar content by Bertrand’s method. Pungency was assessed using the Scoville heat units’ method, and statistical analysis was performed using ANOVA. Results: The study of six Armenian chili pepper varieties showed differences in fruit shape, color, ripening times, and productivity. 'Deghin kakach', 'Oranj kakach', and 'Kon' produce conical fruits that change to yellow, orange, and red, respectively, while 'Punj', 'Kaytsak', and 'Artsiv' have elongated fruits that ripen red. Early varieties like 'Punj', 'Artsiv', and 'Kaytsak' mature 11–17 days earlier. 'Oranj kakach' was the most productive (19.4 t/ha), while 'Kaytsak' had the lowest yield. 'Artsiv', 'Punj', and 'Kaytsak' were hot, while the others were moderately hot. Carotenoid content rose during ripening, ascorbic acid ranged from 115.0 to 175.6 mg/100 g, with 'Punj' highest, and total phenolics peaked in 'Deghin kakach'. Conclusion: Armenian chili pepper varieties are rich in bioactive compounds—phenols, ascorbic acid, carotenoids, and capsaicin— suitable for functional foods. During ripening, carotenoids increased by up to 583.64%, ascorbic acid by 97.4%, and phenols by 96.43%. ‘Punj’ had the highest ascorbic acid, ‘Oranj kakach’ the most carotenoids, and ‘Deghin kakach’ the most phenols, highlighting the potential of ripening to boost the health benefits of these peppers. Keywords: hot pepper, vitamin C, carotenoids, phenols, phenological stages, productivity

Comparison of the performance of classical and quantum machine‐learning methods on the detection of sugar beet Cercospora leaf disease

AbstractImage processing and machine‐learning (ML) techniques are essential for the detection of diseases and pests in plants. This study explored the application of quantum ML (QML) algorithms for the early detection of Cercospora beticola leaf disease in sugar beet, which causes significant impact on global sugar production. Using a dataset of 1065 images (739 diseased and 326 healthy), we extracted 70 ML statistical features, including 10 from the grey‐level co‐occurrence matrix (GLCM) and 60 colour‐related features. Performance evaluations of classical ML algorithms, such as random forest (RF; 91.95% accuracy) and extreme gradient boosting (91.95% accuracy), demonstrated strong results compared to quantum approaches. Notably, the quantum support vector classifier (QSVC) achieved an accuracy of 85% with perfect recall of 1.00, while the variational quantum classifier (VQC) recorded an accuracy of 88.73%. Dimensionality reduction via principal component analysis reduced features from 70 to 5, enabling effective classification with competitive results: ML (RF) 91.41%, VQC with limited‐memory Broyden–Fletcher–Goldfarb–Shanno with box constraints (L_BFGS_B) 88.73% and QSVC 85%. These findings highlight the potential of QML algorithms in improving agricultural disease identification and aiding in the advancement of more efficient, sustainable farming techniques.

Geospatially Informed Water Pricing for Sustainability: A Mixed Methods Approach to the Increasing Block Tariff Model for Groundwater Management in Arid Regions of Northwest Bangladesh

Groundwater depletion in arid regions poses a significant threat to agricultural sustainability and rural livelihoods. This study employs geospatial analysis and economic modeling to address groundwater depletion in the arid Barind region of Northwest Bangladesh, where 84% of the rural population depends on agriculture. Using remote sensing and GIS, we developed an elevation map revealing areas up to 60 m above sea level, exacerbating evaporation and aquifer dryness. Field data collected through Participatory Rural Appraisal tools showed farmers exhibiting “ignorant myopic” behavior, prioritizing short-term profits over resource conservation. To address this, an Increasing Block Tariff (IBT) water pricing model was developed, dividing water usage into three blocks based on irrigation hours: 1–275 h, 276–550 h, and 551+ h. The proposed IBT model significantly increases water prices across the three blocks: 117 BDT/hour for the first block (from current 100–110 BDT/hour), 120 BDT/hour for the second block, and 138 BDT/hour for the third block. A demand function (y = −0.1178x + 241.8) was formulated to evaluate the model’s impact. The results show potential reductions in groundwater consumption: 59 h in the first block, 26 h in the second block, and 158 h in the third block. These reductions align with the principles of integrated water resource management (IWRM): social equity, economic efficiency, and environmental integration. The model incorporates economic externalities (e.g., well lifting costs) and environmental externalities (e.g., crop pattern shifts), with total costs reaching 92,709,049 BDT for environmental factors. This research provides a framework for sustainable groundwater management in arid regions, potentially reducing overextraction while maintaining agricultural productivity. The proposed IBT model offers a locally driven solution to balance resource conservation with the livelihood needs of farming communities in the Barind tract. By combining remote sensing, GIS, and economic modeling, this research provides a framework for sustainable groundwater management in arid regions, demonstrating the power of geospatial technologies in addressing complex water resource challenges.

Soil Physico-chemical Responses to Integrated Nutrient Management in Lentil Intercropped with Bhimal (Grewia optiva) in Agroforestry vs. Open Systems

The growing concern over health risks associated with the heavy use of chemical fertilizers and pesticides in India, which have been linked to rising cancer cases, underscores the need for sustainable agricultural practices. Integrated Nutrient Management offers a promising solution to enhance soil fertility and support crop health, especially for lentil cultivation within agroforestry systems. This study, conducted at Dr. Y. S. Parmar University of Horticulture and Forestry in Nauni, Solan, Himachal Pradesh, examined the effects of INM on the soil’s physical and chemical properties when lentils were intercropped within a Grewia optiva (Bhimal) agroforestry system in the mid-hills region of Himachal Pradesh. The experiment evaluated various combinations of organic and inorganic fertilizers, including T1: Recommended Dose of Fertilizer, T2: Farmyard Manure, T3: Vermicompost, T4: Goat Manure, T5: 50% Recommended dose of fertilizer + 50% Farm yard manure, T6: 50% Recommended dose of fertilizer + 50% Vermicompost, T7: 50% Recommended dose of fertilizer + 50% Goat Manure, and T8: Control. These treatments were applied in plots both under the Bhimal-based agroforestry system (S1) and in open field conditions (S2), with three replications per treatment following a factorial randomized block design. Key physical parameters such as bulk density, particle density, porosity, and soil moisture were measured alongside chemical properties, including soil pH, electrical conductivity, organic carbon content, and the availability of nitrogen, phosphorus, and potassium. Data collected over two years was analyzed using R Statistical Software, revealing that INM significantly improved soil properties in the agroforestry system compared to the control. Notably, 100% FYM emerged as the most effective treatment, enhancing soil porosity, moisture, pH, and nutrient availability (N, P, and K). Improvements in soil structure and nutrient levels were particularly evident in the second year, positively impacting lentil growth and yield. The study highlights the potential of INM to promote sustainable, chemical-free agriculture in hilly areas, offering valuable recommendations for farmers and policymakers focused on sustainable agriculture. Specifically, 100% FYM is recommended for improving soil health and crop productivity in the mid-hill region of Himachal Pradesh, providing a model for similar agro-ecological zones aiming to reduce chemical inputs and support human health.

Violent sustainability: Blitzscale and counteraccounting in an Indian agtech start‐up

AbstractIn recent years, there has been rapid digitalization in agriculture, with India seeing a significant rise in agricultural technology (agtech) start‐ups. Many of these start‐ups promise to address the climate crisis by promoting the economic and ecological sustainability of agriculture through market‐driven business models. Using institutional ethnography and counteraccounting at an Indian agtech start‐up, this article illuminates social, economic, and ecological relationships that are obscured by one firm's accounting practices. It shows how, despite tech‐entrepreneurs intending to help farmers, violence remains built into the design and effects of rapidly scaled‐up (“blitzscaled”) sustainability programs. The article proposes violent sustainability as a concept to highlight the unintended harm caused to potential beneficiaries due to structural violence underlying tech‐entrepreneurialism and inherent design flaws in blitzscaled sustainability programs. In doing so, it challenges the normalization and monetization of recurrent failures prevalent in tech‐entrepreneurial ventures.

Economic Analysis, Yield Optimization, and Competition Dynamics of Groundnut/Cereal Fodder Intercropping Systems in Pakistan's Semi Arid Tropics

This research focuses on the intercropping management options including aspects of yield performance, nitrogen contribution to groundnut and economical considerations through the usage of intercrop Maize, Sorghum and Pearl Millet under varying cuttings treatments. Intercropping is effective in increasing land productivity and efficiency in nutrient use and provides economic returns yet the best combinations have not been well explored. Randomised complete block design was used to assess the growth characteristics of plant height, modulation and nitrogen in sole cropping and intercropping treatments in which they make cuts. For sole crop, both, maize and pearl millet produced the highest green fodder yields of 13.40 t ha⁻¹ and 19.10 t ha⁻¹, respectively, and intercropping reduced the productivity for both crops but it was statistically significant, yield recorded in Maize (one cut) groundnut = 3.10 t ha⁻¹. Both nodulation and nitrogen content were maximum in sole groundnut, but they were lower when groundnut was grown in association with other crops. Among all competitive indices, the LER was the highest on maize (LER=1.72), pearl millet and sorghum indicated that intercropping enhances land use efficiency. This was facilitated by the Monetary Advantage Index (MAI) that provided much support to maize-groundnut intercrop, which was easily identified as the most appropriate option for inter-crop revenue generation with an MAI of Rs. 17,800. These results provide evidence for the suitability of maize as the best intercrop for the enhancement of productivity and profitability in groundnut based intercropping systems. This study adds valuable input to sustainable agriculture, particularly in that it expresses the yields and profits from distinct intercrop associations as numeral digits deemed useful by both the scientific and agricultural communities.

Comparative Analysis of Tillage Practices on Soil Characteristics in Vertisol for Groundnut-based Cropping System

Tillage practices in groundnut-based Vertisol systems is essential for improving soil health and maximizing agricultural productivity. This study investigates the impact of tillage practices and cropping systems on soil physical and chemical properties in the Vertisol region of Karnataka during the 2022-23 Kharif and Rabi seasons. Conducted at the MARS, UAS, Dharwad, the experiment utilized a strip plot design, comparing minimum tillage with crop residue incorporation (M1) and conventional tillage without residue (M2) across four cropping systems. Findings revealed that minimum tillage significantly enhanced soil properties, demonstrating improved porosity (52.14%), maximum water holding capacity (55.97%) and soil aggregate stability (62.42%) while reducing bulk density (1.27 Mg m⁻³) at the surface layer. Among cropping systems, the groundnut + pigeon pea combination showed superior soil characteristics, with porosity at 50.88%, MWHC at 55.05%, and reduced bulk density of 1.31 Mg m⁻³ at 0-15 cm depth. Additionally, minimum tillage led to higher soil organic carbon (7.65 g kg⁻¹) and available NPK levels (315.8 kg ha⁻¹ N, 44.06 kg ha⁻¹ P, 324.53 kg ha⁻¹ K), particularly in the groundnut + pigeon pea system. These findings emphasize the efficacy of conservation agriculture techniques, reinforcing existing research that highlights how minimum tillage and leguminous cropping systems enhance soil health and foster sustainable farming practices. Such results are pivotal for promoting sustainable agricultural development, as they illustrate that implementing these practices can lead to significant improvements in soil vitality, crucial for boosting crop yields and ensuring ecological stability in Karnataka's Vertisol region.

The Impact of Farmers' Social Lifestyles on Agricultural Sustainability in Rural Area of Turkey

This study investigates how farmers' social lifestyles influence agricultural sustainability in rural Turkey. Through data analysis from 312 producers across five provinces, we examine how participation in social activities such as religious gatherings, café meetings, and agricultural fairs shapes farming decisions and sustainability outcomes. Using logistic regression modeling, we find that social network participation significantly impacts agricultural performance and sustainability practices. Results reveal that different types of social engagement lead to distinct patterns of innovation adoption and resource management. Coffee-house and religious gatherings influence not only sales decisions but also agronomic practices, such as adopting new technologies and innovative methods. The lack of female involvement and potential pathways for their integration are also important. This research provides crucial insights for policymakers seeking to leverage existing social networks to promote sustainable agricultural practices in rural communities.

Assessment of Different Organic Manures on Yield of Broccoli (Brassica oleracea var. Italica Plenck.) cv. KTS-1 under Bundelkhand Climatic Condition

Aims: The organic content in manure helps soil retain moisture, increases gas exchange, and introduces beneficial bacteria, loosens clayey soil, promoting root growth. Soil with a higher organic content is more resistant to erosion and produces superior crops. Using organic manure decreases farming's environmental impact. Unlike synthetic fertilizers, it recycles waste materials, nourishes the soil, and nurtures crops. Methods: This experiment was carried out during Rabi 2023-24 at the Organic Research farm Kargunwan ji, Department of Horticulture, Institute of Agricultural Sciences, Bundelkhand University Jhansi (Uttar Pradesh). Broccoli (Brassica oleracea var. italicaPlenck.) cv. KTS-1 was sown under randomized block design (RBD) with 11 treatment viz., Control, Vermicompost 100%, Cow litter 100%, Pressmud 100%, Vermicompost 75%, Cow litter 75%, Pressmud 75%, Vermicompost 50%+Cow litter 50%, Cow litter 50%+Press mud 50%, Pressmud 50%+Vermi 50%, Pressmud 33%+Cow litter 33%+Vermi 33% with 3 replication accommodating spacing (60 × 45) cm2,plot size (2.4 × 1.8) m = 4.32 m2 with total gross experimental area of (23.5 x 9.6) m = 225.06 m2. Results: Results shows thatat harvest, treatment T10 took to the minimum curd initiation at 53.10 days, compared to the control plot at 68.07 days. Similarly, days to 50% curd initiation and maturity were also shorter in T10, at 67.03 days and 80.13 days, respectively, while the control plot took (78.03 and 96.13) days. Ttreatment T10 produced the largest curd diameter (14.78 cm) and weight (321.03 g), significantly surpassing the control plot (6.37) cm diameter and (138.43) g weight. Overall, T10 yielded (321.03) q/ha, markedly higher than the control plot (138.43) q/ha, demonstrating significant improvements in broccoli yield and quality. Conclusion: The results clearly revealed that the application of organic treatments, particularly T10 (Pressmud 33% + Cow litter 3% + Vermi 33%), significantly enhanced the yield and quality of broccoli. This treatment resulted in faster curd initiation and maturity, larger curd diameter, and increased curd weight compared to the control plot. The findings indicate that the strategic use of organic manure can optimize broccoli production, suggesting a viable approach for improving crop outcomes in sustainable agriculture.

Role of Machine and Deep Learning Algorithms in Secure Intrusion Detection Systems (IDS) for IOT & Smart Cities

In this study the authors have examines various machine learning algorithms that could be used in IDS for making secure IoT and Smart Cities. The study examines various deep learning architectures of supervised, unsupervised, and semi-supervised learning methods to improve security and resource usage. Federated learning, edge computing, explainable AI, adversarial machine learning defense, and transfer learning are also explored for smart farming and IoT challenges. Machine learning has the potential to improve security and agricultural sustainability, but it must be researched and developed.

Many Little Hacks: Agroecological Plant Protection through Regenerative Potato Cropping

Abstract Typically potato farming practices are characterized by tight rotations, intensive tillage and fertilization. This leads to soil degradation, increased pest and disease pressure, and use of chemicals, thereby endangering ecosystem health and contaminating water supplies. Agroecological strategies were tested, including the strategic use of cover crops, reduced tillage, and organic fertilization by compost and transferred mulch of green manures. These practices were shown to improve soil structure, increase soil biodiversity, reduce the need for chemical inputs, and enhance crop resilience against pests and diseases. Findings underscore the effectiveness of agroecological management systems in increasing both ecological and economic sustainability in potato farming. The study argues for a change, away from individual measures and solutions and toward an interlocking ecoagricultural system and systemic thinking to reduce or avoid chemical pesticides, high fertilizer input, and tillage. Information © The Authors 2024

The Synergistic Impact of a Novel Plant Growth-Promoting Rhizobacterial Consortium and Ascophyllum nodosum Seaweed Extract on Rhizosphere Microbiome Dynamics and Growth Enhancement in Oryza sativa L. RD79

This study investigated the combined effects of novel plant growth-promoting rhizobacteria (PGPR)—Agrobacterium pusense NC2, Kosakonia oryzae WN104, and Phytobacter sp. WL65—and Ascophyllum nodosum seaweed extract (ANE) as biostimulants (PGPR-ANE) on rice growth, yield, and rhizosphere bacterial communities using the RD79 cultivar. The biostimulants significantly enhanced plant growth, shoot and root length, and seedling vigour; however, seed germination was not affected. In pot experiments, biostimulant application significantly increased the richness and evenness of bacterial communities in the rhizosphere, resulting in improvements in rice growth and yield, with increases in plant height (9.6–17.7%), panicle length (14.3–17.9%), and seeds per panicle (48.0–53.0%). Notably, biostimulant treatments also increased post-harvest soil nutrient levels, with nitrogen increasing by 7.7–19.2%, phosphorus by 43.4–161.4%, and potassium by 16.9–70.4% compared to the control. Principal coordinate analysis revealed distinct differences in bacterial composition between the tillering and harvesting stages, as well as between biostimulant treatments and the control. Beneficial bacterial families, including Xanthobacteraceae, Beijerinckiaceae, Acetobacteraceae, Acidobacteriaceae, and Hyphomicrobiaceae, increased in number from the tillering to harvesting stages, likely contributing to soil health improvements. Conversely, methanogenic bacterial families, such as Methanobacteriaceae and Methanosarcinaceae, decreased in number compared to the control. These findings highlight the dynamic responses of the rhizosphere microbiome to biostimulant treatments and underscore their potential benefits for promoting sustainable and productive agriculture.

Recent Advances in Electrocatalytic C-N Coupling for Urea Synthesis.

Urea, one of the most widely used nitrogen-containing fertilizers globally, is essential for sustainable agriculture. Improving its production is crucial for meeting the increasing demand for fertilizers. Electrocatalytic co-reduction of CO₂ and nitrogenous compounds (NO₂-/NO₃-) has emerged as a promising strategy for green and energy-efficient urea synthesis. However, challenges such as slow reaction kinetics and complex multi-step electron transfers have hindered the development of efficient urea synthesis methods. This review explores recent advances in the electrocatalytic C-N coupling process, focusing on bimetallic catalysts, metal oxide/hydroxide catalysts, and carbon-based catalysts. The review also discusses the future prospects of designing effective catalysts for electrocatalytic C-N coupling to improve urea synthesis.

Bioengineering Bacillus spp. for Sustainable Crop Production: Recent Advances and Resources for Biotechnological Applications

AbstractThe goal of sustainable agriculture is to meet the rising need for food, while minimizing adverse impacts on the environment, protecting natural resources, and ensuring agricultural output over the long term. The pressing need to increase agricultural yield through sustainable agriculture is being emphasized. Several Bacillus species have been used as commercial biopesticides since they can act against plant pathogens by potentially suppressing them. At the same time, they can act as plant growth-promoting rhizobacteria and are known for their diverse characteristics and beneficial properties, making them potential candidates for use sustainable crop production programs. Knowledge of genetic information opens the door of possibility for understanding the way these microorganisms behave. By applying biotechnological tools to Bacillus, strategies can be adopted for the purpose of increasing the yield of crops and managing pests and pathogens that infect them. In this review, we identify the genes in the most significant Bacillus spp. that contribute to plant improvement. The most important biotechnological tools and advance computational approaches are described to provide an extended vision on this topic. However, increasing the crop production through application of beneficial microbial strains requires a multifaceted approach that considers ecological, economic, and social aspects. By implementing these strategies and practices, we can work towards a sustainable and resilient agricultural system that meets the growing food demand, while preserving the environment for future generations.

Initial Evaluation of Safety and Immunomodulatory Potential of Dietary Supplementation with Mangosteen Pericarp Extract for Sustainable Meat Production in Native Crossbred Chickens

The utilization of mangosteen biomass not only solves environmental problems but also raises the value of agricultural waste. The current study aimed to evaluate the potential of mangosteen pericarp extract (MPE) for enhancing the immunity and productivity of Thai native crossbred chickens on-farm. A total of 180 three-week-old chickens were divided into negative control and supplemented groups, with 1000 mg MPE/kg of diet. The safety of MPE was further confirmed by the absence of noticeable differences in mortality and biochemical parameters during the entire study period. The MPE-supplemented group displayed significant differences in the relative transcription levels of IL-10 compared to the basal diet group (p ≤ 0.01). Preslaughter body weight, average daily gain, and carcass weight in the MPE-supplemented group were higher than those in the basal diet group (p ≤ 0.05). Furthermore, MPE supplementation improved meat quality by enhancing the nutritional composition of protein and fat (p ≤ 0.05), as well as improving water-holding capacity, lowering boiling, and lowering grilling losses (p ≤ 0.01). These findings indicate that MPE can be an effective supplement for enhancing flock immunity, growth performance, and meat quality in poultry. This contributes to more sustainable agriculture and food security within agroecosystems.

Rumen-Targeted Mining of Enzymes for Bioenergy Production.

Second-generation biofuel production, which aims to convert lignocellulose to liquid transportation fuels, could be transformative in worldwide energy portfolios. A bottleneck impeding its large-scale deployment is conversion of the target polysaccharides in lignocellulose to their unit sugars for microbial fermentation to the desired fuels. Cellulose and hemicellulose, the two major polysaccharides in lignocellulose, are complex in nature, and their interactions with pectin and lignin further increase their recalcitrance to depolymerization. This review focuses on the intricate linkages present in the feedstocks of interest and examines the potential of the enzymes evolved by microbes, in the microbe/ruminant symbiotic relationship, to depolymerize the target polysaccharides. We further provide insights to how a rational and more efficient assembly of rumen microbial enzymes can be reconstituted for lignocellulose degradation. We conclude by expounding on how gains in this area can impact the sustainability of both animal agriculture and the energy sector.

Nanocząstki krzemu w zrównoważonym rolnictwie

The increasing population, shrinking arable land, and climate change prompt the search for new solutions in agriculture. In a sustainable approach, agriculture should be based on improving the quality and quantity of yields while maintaining biodiversity and protecting the natural environment. Nanotechnology, present in many areas of our lives, offers opportunities to support the development of sustainable agriculture on many levels. Among the numerous solutions and nanomaterials, silicon, which is a natural component of the ecosystem, deserves special attention. In its nanoparticle form, it acquires new, unique properties. This article focuses on the significant role of silicon nanoparticles in organic farming, with particular emphasis on their function as nanofertilizers. The authors analyze the impact of silicon nanoparticles on plant growth and development and their potential in mitigating the negative effects of abiotic stress factors caused by drought, salinity, and exposure to metals. Additionally, the beneficial effects of silicon nanoparticles on plants growing under biotic stress conditions induced by microorganisms such as bacteria and fungi are presented. The paper includes a review of original research results conducted in recent years in this area, as well as possible mechanisms and strategies of silicon nanoparticle action at the physiological, cellular, and molecular levels. The issue of the safety of using nanoparticles in agriculture and the prospects for their further use as a factor enhancing the resistance and productivity of crops are also discussed.

Human-computer interactions with farm animals—enhancing welfare through precision livestock farming and artificial intelligence

While user-centered design approaches stemming from the human-computer interaction (HCI) field have notably improved the welfare of companion, service, and zoo animals, their application in farm animal settings remains limited. This shortfall has catalyzed the emergence of animal-computer interaction (ACI), a discipline extending technology’s reach to a multispecies user base involving both animals and humans. Despite significant strides in other sectors, the adaptation of HCI and ACI (collectively HACI) to farm animal welfare—particularly for dairy cows, swine, and poultry—lags behind. Our paper explores the potential of HACI within precision livestock farming (PLF) and artificial intelligence (AI) to enhance individual animal welfare and address the unique challenges within these settings. It underscores the necessity of transitioning from productivity-focused to animal-centered farming methods, advocating for a paradigm shift that emphasizes welfare as integral to sustainable farming practices. Emphasizing the ‘One Welfare’ approach, this discussion highlights how integrating animal-centered technologies not only benefits farm animal health, productivity, and overall well-being but also aligns with broader societal, environmental, and economic benefits, considering the pressures farmers face. This perspective is based on insights from a one-day workshop held on June 24, 2024, which focused on advancing HACI technologies for farm animal welfare.