bluuebunny/crossref_metadata_2025 huggingface dataset:
Place-based, intersectional variation in caregiving patterns and health outcomes among informal caregivers in the United States
Authors: Cohen Steven A. , Nash Caitlin C. , Greaney Mary L.
Published: August 2024

Introduction

Informal caregiving is a critical component of the healthcare system despite numerous impacts on informal caregivers’ health and well-being. Racial and gender disparities in caregiving duties and health outcomes are well documented. Place-based factors, such as neighborhood conditions and rural–urban status, are increasingly being recognized as promoting and moderating health disparities. However, the potential for place-based factors to interact with racial and gender disparities as they relate to caregiving attributes jointly and differentially is not well established. Therefore, the primary objective of this study was to jointly assess the variability in caregiver health and aspects of the caregiving experience by race/ethnicity, sex, and rural–urban status.

Methods

The study is a secondary analysis of data from the 2021 and 2022 Behavioral Risk Factor Surveillance System (BRFSS) from the Centers for Disease Control and Prevention. Multivariable logistic regression or Poisson regression models assessed differences in caregiver attributes and health measures by demographic group categorized by race/ethnicity, sex, and rural–urban status.

Results

Respondents from rural counties were significantly more likely to report poor or fair health (23.2% vs. 18.5%), have obesity (41.5% vs. 37.1%), and have a higher average number of comorbidities than urban caregivers. Overall, rural Black male caregivers were 43% more likely to report poor or fair health than White male caregivers (OR 1.43, 95% CI 1.21, 1.69). Urban female caregivers across all racial groups had a significantly higher likelihood of providing care to someone with Alzheimer’s disease than rural White males (p < 0.001). Additionally, there were nuanced patterns of caregiving attributes across race/ethnicity*sex*rural–urban status subgroups, particularly concerning caregiving intensity and length of caregiving.

Discussion

Study findings emphasize the need to develop and implement tailored approaches to mitigate caregiver burden and address the nuanced needs of a diverse population of caregivers.
An analysis of trends in the use of animal and non-animal methods in biomedical research and toxicology publications
Authors: Taylor Katy , Modi Stephanie , Bailey Jarrod
Published: August 2024

Introduction

There have been relatively few attempts to quantitatively assess if, and in which areas, the use of non-animal methods (NAMs) is increasing in biomedical research and importantly, how this compares to the use of live animals.

Methods

We conducted a bibliometric analysis of the relative publication of papers reporting the use of NAMs-only compared to those reporting the use of animals, even if they also reported the use of NAMs, over the period 2003 to 2022 across seven research areas (breast cancer, lung disease, blood cancer, heart disease, neurodegenerative diseases, diabetes and toxicology) and five regions (USA, China, France, Germany, United Kingdom).

Results

We found that the relative number of publications of research using NAMs-only has been higher than animal-based research for the last 20 years for all research areas and is growing. Research areas differed in their relative publication of NAMs-only based work, with breast cancer and lung disease having consistently the highest ratio of NAMs-only to animal-based publications and heart disease, diabetes and toxicology showing the greatest change over the time period. A key period of change was 2016–18. By 2022 the UK had the highest NAMs-only to animal-based research ratio than any other country for five of the seven research areas and China the lowest for six, accounting for publication rate. Tissue and in silico-based methods were the most common of all NAMs-only publications; lab-on-a-chip and stem cell models are increasing in their use but at much lower levels and rate of increase.

Conclusion

We found that proportionately the reliance on animals in these research areas is decreasing, which will be encouraging to those that support the replacement of animal experiments.
HRIDM: Hybrid Residual/Inception-Based Deeper Model for Arrhythmia Detection from Large Sets of 12-Lead ECG Recordings
Authors: Moqurrab Syed Atif , Rai Hari Mohan , Yoo Joon
Published: August 2024

Heart diseases such as cardiovascular and myocardial infarction are the foremost reasons of death in the world. The timely, accurate, and effective prediction of heart diseases is crucial for saving lives. Electrocardiography (ECG) is a primary non-invasive method to identify cardiac abnormalities. However, manual interpretation of ECG recordings for heart disease diagnosis is a time-consuming and inaccurate process. For the accurate and efficient detection of heart diseases from the 12-lead ECG dataset, we have proposed a hybrid residual/inception-based deeper model (HRIDM). In this study, we have utilized ECG datasets from various sources, which are multi-institutional large ECG datasets. The proposed model is trained on 12-lead ECG data from over 10,000 patients. We have compared the proposed model with several state-of-the-art (SOTA) models, such as LeNet-5, AlexNet, VGG-16, ResNet-50, Inception, and LSTM, on the same training and test datasets. To show the effectiveness of the computational efficiency of the proposed model, we have only trained over 20 epochs without GPU support and we achieved an accuracy of 50.87% on the test dataset for 27 categories of heart abnormalities. We found that our proposed model outperformed the previous studies which participated in the official PhysioNet/CinC Challenge 2020 and achieved fourth place as compared with the 41 official ranking teams. The result of this study indicates that the proposed model is an implying new method for predicting heart diseases using 12-lead ECGs.
Conceptual Design of Compliant Structures for Morphing Wingtips Using Single-Row Corrugated Panels
Authors: He Ziyi , Fan Siyun , Wang Chen , Li Songqi , Zhao Yan , Shen Xing , Zhang Jiaying
Published: August 2024

Morphing wingtips have the potential to improve aircraft performance. By connecting the wingtips and the wings with a compliant structure, a continuous aerodynamic surface can be achieved for a better aerodynamic performance. However, how to maintain the shape-changing capability while keeping a high stiffness to carry aerodynamic loads is a key problem. In this paper, based on asymmetric stiffness, a type of single-row corrugated panel is designed to satisfy the limited space around the wingtip. A finite element model of the single-row corrugated panels is established, and parameter analysis is performed to investigate the impact of the thickness characteristics of the corrugated panel on the folding angle. The corrugated panel is then optimised to find the maximum folding angle. Based on the optimisation results, corrugated panels with asymmetric and symmetric stiffness are fabricated and tested. The results demonstrate that the asymmetric stiffness corrugated panels have the capability to increase the wingtip folding angle.
A Study on the Trade Efficiency and Potential of China’s Agricultural Products Export to Association of South East Asian Nations Countries: Empirical Analysis Based on Segmented Products
Authors: Du Juan , Liu Yuan , Luo Shanna , Luo Xin
Published: August 2024

This study examines the current state of China’s agricultural exports to ASEAN countries using a segmented export structure analysis via a stochastic frontier gravity model, based on panel data from 2007 to 2020. The results indicate that: (1) China’s primary agricultural exports to ASEAN countries include plant products, food and beverages, and tobacco, with animal products mainly exported to Thailand, plant products mainly exported to Vietnam, and animal and plant fats, food, beverages, and tobacco mainly exported to Malaysia. (2) The economic scale and population size of China and ASEAN countries have differing impacts on various markets, while distance significantly negatively affects the exports of animal products, plant products, food, beverages, and tobacco. Additionally, ASEAN countries’ per capita carbon emissions positively influence the exports of these product categories. (3) The liner shipping connectivity index is significantly negatively correlated with trade inefficiency. The influences of financial freedom, trade freedom, investment freedom, and government expenditure on trade inefficiency vary across ASEAN countries. (4) China’s export efficiency for animal products, plant products, food, beverages, and tobacco has increased rapidly to Thailand and Vietnam, with Malaysia and Singapore showing high export efficiency, while that to Cambodia lags. (5) China exhibits significant export potential to Thailand, Indonesia, and Vietnam, with substantial expansion opportunities in Indonesia. Moreover, China’s export potential and opportunities in Cambodia are steadily increasing.
Development, Integration, and Field Experiment Optimization of an Autonomous Banana-Picking Robot
Authors: Chen Tianci , Zhang Shiang , Chen Jiazheng , Fu Genping , Chen Yipeng , Zhu Lixue
Published: August 2024

The high growth height and substantial weight of bananas present challenges for robots to harvest autonomously. To address the issues of high labor costs and low efficiency in manual banana harvesting, a highly autonomous and integrated banana-picking robot is proposed to achieve autonomous harvesting of banana bunches. A prototype of the banana-picking robot was developed, featuring an integrated end-effector capable of clamping and cutting tasks on the banana stalks continuously. To enhance the rapid and accurate identification of banana stalks, a target detection vision system based on the YOLOv5s deep learning network was developed. Modules for detection, positioning, communication, and execution were integrated to successfully develop a banana-picking robot system, which has been tested and optimized in multiple banana plantations. Experimental results show that this robot can continuously harvest banana bunches. The average precision of detection is 99.23%, and the location accuracy is less than 6 mm. The robot picking success rate is 91.69%, and the average time from identification to harvesting completion is 33.28 s. These results lay the foundation for the future application of banana-picking robots.
Nutrient Stress Symptom Detection in Cucumber Seedlings Using Segmented Regression and a Mask Region-Based Convolutional Neural Network Model
Authors: Islam Sumaiya , Reza Md Nasim , Ahmed Shahriar , Samsuzzaman  , Lee Kyu-Ho , Cho Yeon Jin , Noh Dong Hee , Chung Sun-Ok
Published: August 2024

The health monitoring of vegetable and fruit plants, especially during the critical seedling growth stage, is essential to protect them from various environmental stresses and prevent yield loss. Different environmental stresses may cause similar symptoms, making visual inspection alone unreliable and potentially leading to an incorrect diagnosis and delayed corrective actions. This study aimed to address these challenges by proposing a segmented regression model and a Mask R-CNN model for detecting the initiation time and symptoms of nutrient stress in cucumber seedlings within a controlled environment. Nutrient stress was induced by applying two different treatments: an indicative nutrient deficiency with an electrical conductivity (EC) of 0 dSm−1, and excess nutrients with a high-concentration nutrient solution and an EC of 6 dSm−1. Images of the seedlings were collected using an automatic image acquisition system two weeks after germination. The early initiation of nutrient stress was detected using a segmented regression analysis, which analyzed morphological and textural features extracted from the images. For the Mask R-CNN model, 800 seedling images were annotated based on the segmented regression analysis results. Nutrient-stressed seedlings were identified from the initiation day to 4.2 days after treatment application. The Mask R-CNN model, implemented using ResNet-101 for feature extraction, leveraged transfer learning to train the network with a smaller dataset, thereby reducing the processing time. This study identifies the top projected canopy area (TPCA), energy, entropy, and homogeneity as prospective indicators of nutritional deficits in cucumber seedlings. The results from the Mask R-CNN model are promising, with the best-fit image achieving an F1 score of 93.4%, a precision of 93%, and a recall of 94%. These findings demonstrate the effectiveness of the integrated statistical and machine learning (ML) methods for the early and accurate diagnosis of nutrient stress. The use of segmented regression for initial detection, followed by the Mask R-CNN for precise identification, emphasizes the potential of this approach to enhance agricultural practices. By facilitating the early detection and accurate diagnosis of nutrient stress, this approach allows for quicker and more precise treatments, which improve crop health and productivity. Future research could expand this methodology to other crop types and field conditions to enhance image processing techniques, and researchers may also integrate real-time monitoring systems.
Numerical Simulation and Analysis of the Impurity Removal Process of a Sugarcane Chopper Harvester Based on a CFD–DEM Model
Authors: Wu Tao , Li Fatang , Liu Qingting , Ren Jiahui , Huang Jibai , Qin Zhanji
Published: August 2024

The cleaning system is a critical component of the sugarcane chopper harvester, facing challenges such as high impurity rate, elevated power consumption, and an inadequate understanding of the cleaning mechanism. This study aims to simulate the process of removing extraneous matter (represented by sugarcane leaves) from the cleaning system by employing a coupling approach of computational fluid dynamics (CFD) and the discrete element method (DEM) to determine the speed of the extractor fan. Initially, a CFD model was established to analyze the airflow field within the extractor, and its accuracy was verified on a test bench for the cleaning system. Subsequently, a DEM model was developed for sugarcane billets and leaves, which was then integrated with the CFD model to form a gas–solid coupling model. The efficacy of this integrated model was confirmed through experimental measurements of impurity rate. Furthermore, a ternary quadratic regression orthogonal combination design was utilized in the gas–solid coupling simulation to assess the impacts of feed rate, leaf–stalk ratio, and extractor fan speed on impurity rate. Finally, the extractor fan speeds were obtained for various feed rates and leaf–stalk ratios under impurity rates of 5%, 6%, 7%, and 8%. This research can guide in controlling the extractor fan speed during sugarcane chopper harvester field operations and can serve as a foundation for extractor fan design.
Intensive Agriculture vs. Invertebrate Biodiversity: A Case Study of Woodland Islets in a Matrix of Arable Land
Authors: Orczewska Anna , Dulik Aleksander , Długosz Patryk , Depa Łukasz
Published: August 2024

Increasing areas of arable land, which is often heavily managed, negatively affect biological diversity in many ways, decreasing species richness and abundance. There is a substantial social demand for implementing agricultural management practices to preserve biological diversity locally. Here, we present the results of studies on the invertebrate diversity of woodland islets, which are small areas of forests surrounded by arable fields. Studies on invertebrate taxa show high values of diversity indices within such forest remnants, with a predominant presence of hymenopterans, collembolans, beetles, and spiders, which serve many ecosystem services, such as pollination or predation. A low abundance of herbivores and a high abundance of agile predators make such small woods a potential habitat for natural pest enemies. The results indicate a potential role for such woodland islets isolated from each other by a distance of ca. 1 km as an efficient substitute for extensive field management since they allow the maintenance of invertebrate diversity in the agricultural landscape.
Detection of Feeding Behavior in Lactating Sows Based on Improved You Only Look Once v5s and Image Segmentation
Authors: Liu Luo , Xu Shanpeng , Chen Jinxin , Wang Haotian , Zheng Xiang , Shen Mingxia , Liu Longshen
Published: August 2024

The production management of lactating sows is a crucial aspect of pig farm operations, as their health directly impacts the farm’s production efficiency. The feeding behavior of lactating sows can reflect their health and welfare status, and monitoring this behavior is essential for precise feeding and management. To address the issues of time-consuming and labor-intensive manual inspection of lactating sows’ feeding behavior and the reliance on breeders’ experience, we propose a method based on the improved YOLO (You Only Look Once) v5s algorithm and image segmentation for detecting the feeding behavior of lactating sows. Based on the YOLOv5s algorithm, the SE (Squeeze-and-Excitation) attention module was added to enhance the algorithm’s performance and reduce the probability of incorrect detection. Additionally, the loss function was replaced by WIoU (Weighted Intersection over Union) to accelerate the model’s convergence speed and improve detection accuracy. The improved YOLOv5s-C3SE-WIoU model is designed to recognize pre-feeding postures and feed trough conditions by detecting images of lactating sows. Compared to the original YOLOv5s, the improved model achieves an 8.9% increase in mAP@0.5 and a 4.7% increase in mAP@0.5 to 0.95. This improvement satisfies the requirements for excellent detection performance, making it suitable for deployment in large-scale pig farms. From the model detection results, the trough remnant image within the detection rectangle was extracted. This image was further processed using image processing techniques to achieve trough remnant image segmentation and infer the remnant amount. Based on the detection model and residue inference method, video data of lactating sows’ feeding behavior were processed to derive the relationship between feeding behavior, standing time, and residue amount. Using a standing duration of 2 s and a leftover-feed proportion threshold of 2% achieves the highest accuracy, enabling the identification of abnormal feeding behavior. We analyzed the pre-feeding postures and residual feed amounts of abnormal and normal groups of lactating sows. Our findings indicated that standing time was significantly lower and residual feed amount was higher in the abnormal groups compared to the normal groups. By combining standing time and residual feed amount information, accurate detection of the feeding status of lactating sows can be realized. This approach facilitates the accurate detection of abnormal feeding behaviors of lactating sows in large-scale pig farm environments.
Toward the Development of Garlic Varieties: The First Attempts
Authors: Licea-Moreno Ricardo Julián , Rodríguez-Haro Ángeles , Marín-Martínez Juan Antonio
Published: August 2024

Despite garlic (Allium sativum L.) being recognized as the second most important species in the Allium genus, a limited number of varieties are available worldwide. Aiming to develop new purple garlic varieties, a representative sample was used to determine the extent of phenotypic variability for commercially desirable characteristics. Initially, 360 bolting bulbs were selected based on their size and abundant external scales. After further assessment, 243 bulbs were discarded due to undesirable traits such as light purple color, numerous small cloves, or damage from Fusarium spp. and mites. Although garlic reproduces asexually, each bulb was considered to represent a distinct family. Thus, 117 families were planted in a randomized complete block design during the 2021–2022 growing season. Physiological, morphological, and phenological traits were assessed for each family, along with damages caused by pests and pathogens. As a result of these evaluations, 103 families were selected for a second trial the following season. Due to increased selection pressure, only 23 families remained in the program at the end of the second trial. High variability was observed for most traits, with a strong influence from family lineage. Environmental conditions significantly impacted the performance of the families, highlighting the need to evaluate them under diverse environments. The high variability within the selected sample indicates a strong potential for developing new garlic varieties.
Dispersal Capacity of Trichogramma for the Management of Duponchelia fovealis
Authors: Pratissoli Dirceu , Damascena Alixelhe Pacheco , Oliveira Regiane Cristina de , Carvalho José Romário de , de Oliveira Ana Carolina Lopes Francisco , Piffer Ana Beatriz Mamedes , Pirovani Victor Dias
Published: August 2024

The European pepper moth (Duponchelia fovealis) is predominant in the main strawberry production areas, including Brazil, as an important invasive pest and causes substantial damage to the crop. This damage is mainly attributed to the lack of effective management strategies. A promising alternative for managing this pest is implementing biological control through releasing natural enemies. This study determined the dispersal capacity of Trichogramma pretiosum for the management of D. fovealis in a strawberry crop in a low tunnel system 24, 48, and 72 h after parasitoid release. The experiments were carried out on strawberry farms in the mountainous region of Espírito Santo. Tunnels measuring 1.20 m wide by 50 m long were selected, in which artificial infestations of 30, 60, 90, and 120 eggs of D. fovealis were made on both sides of the strawberry tunnel at distances of 3, 7, 11, and 15 m, respectively, from the central point where the parasitoids were released. After the initial 24 h, new eggs were placed to replace the infested ones; the replacement was repeated at 48 and 72 h. The results indicated that, in strawberry plantations, T. pretiosum was efficient in parasitism. There was no difference between parasitism 24 and 48 h after parasitoid release, but parasitism was substantially lower after 72 h. The dispersion capacity of T. pretiosum was 14.21 linear meters, corresponding to an area of 17.05 m2. It is recommended that 93,000 T. pretiosum females be released per hectare every three days.
Utilizing Infrared Thermometry to Assess the Crop Water Stress Index of Wheat Genotypes in Arid Regions under Varying Irrigation Regimes
Authors: Mohamed Naheif E. , Mustafa Abdel-rahman A. , Bedawy Ismail M. A. , Ahmed Aliaa saad , Abdelsamie Elsayed A. , Mohamed Elsayed Said , Rebouh Nazih Y. , Shokr Mohamed S.
Published: August 2024

Researchers are depending more than ever on remote sensing techniques to monitor and assess the agricultural water status, as well as to estimate crop water usage or crop actual evapotranspiration. In the current work, normal and stressed baselines for irrigated wheat genotypes were developed in an arid part of the Sohag governorate, Egypt, using infrared thermometry in conjunction with weather parameters. The experiment was carried out in a randomized complete block design in the normal and drought stress conditions based on three replicates using ten bread wheat genotypes (G1–G10), including five accessions, under drought stress. A standard Class-A-Pan in the experimental field provided the daily evaporation measurements (mm/day), which was multiplied by a pan factor of 0.8 and 0.4 for normal and stressed conditions, respectively. The relationship between the vapor pressure deficit (VPD) and canopy-air temperature differences (Tc − Ta) was plotted under upper (fully stressed) and lower baseline (normal) equations. Accordingly, the crop water stress indexes (CWSIs) for the stressed and normal baselines for wheat genotypes were developed. Additionally, the intercept (b) and the slope (a) of the lower baseline equation were computed for different genotypes. The results indicate that, before applying irrigation water, the CWSI values were high in both growing seasons and under all irrigation regimes. After that, the CWSI values declined. G10 underwent stress treatment, which produced the greatest CWSI (0.975). Conversely, the G6 condition that received well-watered irrigation yielded the lowest result (−0.007). When compared to a well-watered one, the CWSI values indicated a trend toward rising stress. There existed an inverse link between the CWSI and grain yield (GY); that is, a lower CWSI resulted in better plant water conditions and a higher GY. Under standard conditions, the wheat’s highest GY was recorded in G2, 8.36 Ton/ha and a WCSI of 0.481. In contrast, the CWSI result for the stress treatment was 0.883, indicating a minimum GY of 5.25 Ton/ha. The Water Use Efficiency (WUE) results demonstrated that the stress irrigation regime produced a greater WUE value than the usual one. This study makes a significant contribution by investigating the techniques that would allow CWSI to be used to estimate irrigation requirements, in addition to determining the irrigation time.
Research on Acoustic Signal Identification Mechanism and Denoising Methods of Combine Harvesting Loss
Authors: Shen Yuhao , Gao Jianmin , Jin Zhipeng
Published: August 2024

Sensors are very import parts of the IoT (Internet of Things). To detect the cleaning loss of combine harvesters during operation, a new detection method based on acoustic signal was proposed. The simulation models of the impact among grain, stem and plate were established by using the ALE algorithm, and the vibration excitation characteristics of the grain and stem were investigated; the results showed that both grain and stem signal were generated by surface vibration’s excitation of the air, and the highest amplitudes of grain and stem signal were 15 kHz and 7 kHz respectively, which made it possible to distinguish grain and stem impact acoustic signals. Therefore, this paper proposed a novel method to separate the grain and stem signals by identifying the characteristic frequency area and subsequently an improved EMD denoising method based on an autocorrelation function was proposed. The critical stratum of EMD was identified based on the autocorrelation value of the eigenmode function, and the improved de-noising method was able to effectively remove the noise and the stem signal. To verify the feasibility of the improved denoising method, a field wheat harvesting experiment was conducted to acquire the actual acoustic signal of the cleaning operation. Data processing results showed that the average error of the comparison between the detected loss amount and the actual loss amount was 6.1%. This paper presents a novel approach for researching combine harvester cleaning loss detection and denoising methods.
Measuring the Influence of Key Management Decisions on the Nitrogen Nutritional Status of Annual Ryegrass-Based Forage Crops
Authors: Silva Luís , Barbosa Sofia , Lidon Fernando Cebola , Santos-Silva José , Conceição Luís Alcino
Published: August 2024

Increasing nitrogen use efficiency (NUE) by improving agricultural practices and soil knowledge, and implementing precision agriculture, is essential to reduce the overuse of fertilizers and increase nutrient retention. This study aimed to optimize N management in agriculture by establishing a critical N dilution curve (CNDC) and analyzing variations in NUE and the N nutrition index (NNI) among different crops under various treatments. Using a Bayesian model, the CNDC was determined as %Nc = 3.63 × PDM−0.71. The results showed that plant dry matter (PDM) and plant N content (PNC) varied significantly with crop type and sampling moments. Strong positive correlations are presented by PDM with N uptake (NUp) (0.89) and NNI (0.88), along with an inverse correlation with critical N concentration (−0.95). The study found that crops under irrigation conditions had higher NUp and higher NNI. This study provides valuable insights into the influence of key management decisions on the N nutritional status of annual ryegrass-based forage crops. The results highlight the critical role of accurate and conscious decision-making in improving NUE and crop yields, emphasizing the complex interactions between biomass production and N dynamics in crops. The conclusions allow significant benefits to be realized, contributing to the sustainability of agricultural systems.
Foliar Application of Bee Honey or Ginger Extract Enhanced Salvia officinalis L. Growth and Productivity by Improving Phytohormones, Antioxidants, Chlorophylls, and Nutrients
Authors: Moussa Mohamed M. , Mansour Mohamed Magdy F. , El-Sharnouby Mohamed , Hassan Fahmy A. S.
Published: August 2024

Improving the productivity of medicinal and aromatic species via eco-friendly approaches is imperative worldwide because of their therapeutic impacts. Biostimulants have been recognized among the best cultural practices in the last few decades. Among them, bee honey (BH) and ginger extract (GE) are new sources of multifunctional biostimulants that positively influence plant growth and development. However, there are currently no detailed reports on the impacts of BH or GE as promising growth and yield enhancers for medicinal and aromatic species. Also, the mechanism involved in stimulating growth and essential oil content with BH or GE is still unidentified. This work was, therefore, undertaken to analyze the impact of BH and GE on the growth, productivity, and essential oil content of sage plants (Salvia officinalis L.). Sage plants were sprayed monthly for three months with the same volume of BH (0, 5, 10, and 15 g L−1), GE (0, 5, 10, and 15 mg L−1), or tap water, which was used as a control. BH or GE application improved the plant height, branch number, herb yield, total chlorophyll content, total phenolics, and antioxidant capacity relative to the controls, more so with GE. Intriguingly, the essential oil percentage, oil yield, and oil constituents were enhanced by BH and GE. In this respect, the highest levels of biostimulants, particularly GE, were more effective. On a percentage basis, the essential oil yield per hectare was largely increased by 127.91 and 138.89% with GE (10 g L−1) in both seasons relative to the controls. The contents of IAA, GA3, and CK in THE sage leaves were substantially increased by BH and GE, and higher levels of both biostimulants and GE were more effective. The nutrient levels of N, P, K, Fe, Zn, and Mg were also elevated by BH and GE compared with the untreated plants. These results suggest that BH or GE application could be a promising biostimulant for improving the productivity of sage and provide a new understanding of their mechanisms in this aspect.
Irrigation of ‘Prata-Anã’ Banana with Partial Root-Zone Drying in a Semi-Arid Environment
Authors: Almeida Felipe Pires de , Santos Marcelo Rocha dos , Coelho Eugênio Ferreira , Donato Sérgio Luiz Rodrigues , Oliveira Polyanna Mara de , Reis João Batista Ribeiro da Silva , Carvalho Luiz Antonio Conceição de , Lima José Carlos Lopes de , Santos Dionei Lima , Cunha Fernando França da
Published: August 2024

Considering the uncertainty of rainfall and prolonged droughts in semiarid regions, optimizing water management through techniques like partial root-zone drying (PRD) is crucial for sustainable banana production. This study aimed to evaluate the ‘Prata-Anã Gorutuba’ banana under irrigation by PRD. The experimental design was randomized blocks with five irrigation strategies (PRD7 50%–50% ETc and 7-day frequency of alternation of the irrigated side—FA, PRD14 50%–50% ETc and 14-day FA, PRD21 50%–50% ETc and 21-day FA, FX 50%–50% ETc and fixed irrigation, and irrigation with 100% ETc on both sides of the plant—FULL) with five replicates. Soil water content, physiological, vegetative, yield characteristics, and water productivity were assessed over two production cycles. PRD on the dry side lowered soil water content below optimal levels for banana cultivation, increased transpiration, and decreased photosynthesis and instantaneous water use efficiency with rising temperatures, while photosynthesis increased with stomatal conductance. PRD reduced plant vigor and delayed flowering in the first cycle. Compared to full and fixed irrigation, PRD conserves water while maintaining crop yields. Water productivity was higher under PRD, with PRD14 (50% ETc and 14-day alternation) offering the best water use efficiency while maintaining yield, making it suitable for ‘Prata-Anã Gorutuba’ banana cultivation. The study recommends PRD for sustainable banana farming in regions with limited water resources, contributing to sustainable agricultural practices and better water management.
Integration of Crops, Livestock, and Solar Panels: A Review of Agrivoltaic Systems
Authors: Soto-Gómez Diego
Published: August 2024

This review article focuses on agrivoltaic production systems (AV). The transition towards renewable energy sources, driven by the need to respond to climate change, competition for land use, and the scarcity of fossil fuels, has led to the consideration of new ways to optimise land use while producing clean energy. AV systems not only generate energy but also allow agricultural and livestock yields to be maintained or even increased under PV structures, offering a sustainable production strategy that may be more acceptable to local communities than traditional PV installations. This review assesses the technical feasibility of AV systems, the environmental, economic and social benefits, as well as the challenges faced and the legal framework regulating their implementation. It is highlighted that despite the advantages in land use efficiency and dual food and energy production, there are important challenges related to the initial investment required, the need for technological adaptation, social and regulatory obstacles, or the effects of shading on production. This paper underlines the importance of further research and development of these systems to overcome technical and economic constraints and maximise their potential benefits. It is concluded that although they present significant challenges, AV management offers promising opportunities to improve land efficiency and contribute to several sustainable development goals.
Optimizing Spring Maize Growth and Yield through Balanced Irrigation and Nitrogen Application: A TOPSIS Method Approach
Authors: Liu Yongqi , Gu Jian , Ma Ningning , Li Xue , Yin Guanghua , Sun Shijun
Published: August 2024

Water and nitrogen are crucial for producing spring maize. Currently, irrigation and fertilization systems often rely on a single indicator, resulting in inefficient practices. This study aims to determine an optimal nitrogen application rate for shallow buried drip irrigation (SBDI) to balance growth characteristics, yield (Y), water use efficiency (WUE), and soil nitrogen levels. In a typical semi-arid region of Northeast China, we conducted controlled experiments from 2022 to 2023, adopting a two-factor quadratic saturation D-optimal design method to study the effects of different irrigation amounts (145.40, 271.70, 348.20, and 436.20 mm) and nitrogen fertilizer application amounts (34.80, 185.90, 277.40, and 382.80 kg·hm−2) on spring maize. The results indicate that increasing both irrigation and nitrogen application rates can enhance dry matter accumulation (DMA) from 15.17% to 32.70%. The impact of irrigation and fertilization on the net photosynthetic rate (Pn) of spring maize was greater for the irrigation applications than the nitrogen applications, particularly at 9:00 a.m. and 13:00 p.m. and slightly less so at 11:00 a.m. and 15:00 p.m. Concurrently, there were significant increases in total nitrogen (TN1 by 20.85% in the 0–20 cm soil layer; TN2 by 33.33% in the 20–40 cm soil layer) and alkali-hydrolyzed nitrogen (AHN1 by 14.65% at 0–20 cm; AHN2 by 28.86% at 20–40 cm). Y improved from 12.02% to 44.09%, and WUE increased from 20.08% to 140.07%. The optimal water and fertilizer management mode for spring maize SBDI in semi-arid areas was determined through comprehensive analysis using the TOPSIS entropy weight method. When the irrigation amount is 436.20 mm, and the nitrogen fertilizer application amount is 277.40 kg·hm−2, it can significantly promote the DMA, Y, WUE, photosynthetic characteristics, and soil nitrogen content of spring maize. This study provides a theoretical basis for the practical application of SBDI water–fertilizer coupling for spring maize.
Analysis of Total Flavonoid Variation and Other Functional Substances in RILs of Tartary Buckwheat, with Near-Infrared Model Construction for Rapid Non-Destructive Detection
Authors: Zhu Liwei , Du Qianxi , Shi Taoxiong , Huang Juan , Deng Jiao , Li Hongyou , Cai Fang , Chen Qingfu
Published: August 2024

According to the requirements of Tartary buckwheat breeding, it is necessary to develop a method for the rapid detection of functional substances in seeds. To ensure a diverse sample pool, we utilized the stable recombinant inbred lines (RILs) of Tartary buckwheat. The coefficients of variation of the total flavonoid, vitamin E (VE), and GABA contents of the RIL population were 15.06, 16.53, and 36.93, respectively. Subsequently, we established prediction models for the functional substance contents in Tartary buckwheat using near-infrared spectroscopy (NIRS) combined with chemometrics. The Kennard–Stone algorithm divided the dataset into training and test sets, employing six different methods for preprocessing spectra. The Competitive Adaptive Reweighted Sampling algorithm extracted the characteristic spectra. The best models for total flavonoid and VE were normalized using the first derivative. The calibration correlation coefficient (Rc) and prediction correlation coefficient (Rp) of the total flavonoid and VE prediction models were greater than 0.94. The optimal GABA prediction model underwent preprocessing via normalization combined with the standard normal variate, and the Rc and Rp values were greater than 0.93. The results demonstrated that the NIRS-based prediction model could satisfy the requirements for the rapid determination of total flavonoids, VE, and GABA in Tartary buckwheat seeds.
Microbiology Combined with the Root Metabolome Reveals the Responses of Root Microorganisms to Maize Cultivars under Different Forms of Nitrogen Supply
Authors: Tian Guan , Ren Wei , Xu Junping , Liu Xiaoyang , Liang Jiaxing , Mi Guohua , Gong Xiaoping , Chen Fanjun
Published: August 2024

Plant–microbe interactions are key to nutrient-use efficiency. Root microbes are influenced by rhizosphere soil and plant cultivars. The impact of cultivar-by-nitrogen (N) interactions on the maize-root microbiome remains unclear, yet it is crucial for understanding N use efficiency in maize. This study evaluated the effects of maize cultivars and N forms, along with their interactions, on the diversity and composition of root bacteria and fungi. Additionally, we examined correlations between soil microbes and root metabolites. The maize cultivar Zhengdan 958 (ZD958) showed a positive response to the mixture of nitrate and ammonium N, resulting in increased in biomass, grain yield, shoot N content, grain N content, and root area. In contrast, the cultivar Denghai605 (DH605) did not exhibit a similar response. The diversity and composition of root bacteria and fungi differed between ZD958 and DH605. The N form primarily affected the community structure of rhizospheric fungi in ZD958 and rhizospheric bacteria in DH605, rather than endophytic microbes. A mixed N supply increased the relative abundance of Basidiomycota, which was positively correlated with ZD958 yield. For DH605, a mixed N treatment enhanced nitrification functions involving Bacteroidetes and Proteobacteria, while it reduced the effects of ammonium N supply. The dominant rhizospheric microbes in DH605 showed a stronger response to changes in root metabolites compared to those in ZD958. A mixed N supply increased the content of palmitoleic acid in ZD958 root exudates, facilitating the recruitment of beneficial rhizospheric microbes, which promotes maize growth. In DH605, a mixed N supply decreased the concentration of sphinganine, which is significantly correlated with Acidobacteria (negatively), Proteobacteria (negatively), Bacteroidetes (positively), and TM7 (positively). Our findings suggest that different maize cultivars respond differently to N forms, causing distinct rhizospheric microbial effects, and that root metabolites send metabolic signals to regulate and recruit key bacterial and fungal communities.
Hepatic Metabolomic Responses to Low-Temperature Stress in the Invasive Turtle, Trachemys scripta elegans
Authors: Tang Huo-Bin , Guo Qiao-Hong , Yang Jia-Meng , Zhang Jin-Hui , Lu Hong-Liang
Published: August 2024

Investigating the physiological and biochemical changes of ectothermic species before entering hibernation would contribute to the understanding of how they adapt to low-temperature environments. Here, red-eared slider turtle (Trachemys scripta elegans) hatchlings were maintained under different thermal treatments (24 °C, slowly decreasing temperatures from 24 °C to 14 °C, and to 4 °C). Hepatic metabolite alterations were measured to assess the metabolic impacts of low-temperature stress in this species. Of these differentially changed metabolites, some (e.g., raffinose, spermidine, allocholic acid, taurohyocholate, 2-ketobutyric acid, acetylcysteine) were shown to decrease, while others (e.g., stearolic acid, D-mannose) increased in low-temperature treatments. Our results indicated that short-term low-temperature stress might have limited impacts on lipid and energy metabolism in this species. The changes in other metabolites (e.g., allocholic acid, taurohyocholate, spermine, acetylcysteine) might be associated with a low food intake (and thus reduced digestive performance) and weakened immune ability of low-temperature-exposed animals.
Evaluation of the Effectiveness of Sex Determination in the Great Cormorant (Phalacrocorax carbo) Based on External Measurements
Authors: Meissner Włodzimierz , Goc Michał , Zaniewicz Grzegorz
Published: August 2024

The possibility of sex identification of birds has substantial importance for studies on different aspects of bird ecology and behaviour. Using discriminant functions is becoming increasingly popular in studies of bird species that are monomorphic in plumage characteristics because they are cheap, hardly invasive and may be applied to data collected in the past. In this paper, we provide a discriminant function to sex great cormorants using external measurements. Males were larger than females in all linear body measurements, but there were no significant differences between adults and juveniles. Thus, data on juveniles and adults within a sex was combined. Discriminant equations with the most commonly used linear measurements, wing length and bill length, were provided. If identifying birds with discriminant function values D2 < −1.256 as females and those with D2 > 0.916 as males, 99% of birds will be correctly sexed. The method presented here makes it possible to account for sex-specific patterns in ecological studies of the great cormorant and may be applied to data collected in the past. The cross-application of discriminant functions developed for other populations of the great cormorant produces a 5.4% and 7.5% misclassification rate for birds from northern Poland using discriminant equations developed for populations in Greece and the Netherlands, respectively.
The Genetic Identification of Numerous Apicomplexan Sarcocystis Species in Intestines of Common Buzzard (Buteo buteo)
Authors: Šukytė Tautvilė , Juozaitytė-Ngugu Evelina , Švažas Saulius , Butkauskas Dalius , Prakas Petras
Published: August 2024

The common Buzzard (Buteo buteo) was previously shown to transmit two Sarcocystis species (S. glareoli and S. microti) forming cysts in the brains of rodents. Due to a lack of research, the richness of Sarcocystis species spread by these birds of prey is expected to be much higher. A total of 30 samples of the small intestine of the Common Buzzard were collected in Lithuania and subjected to Sarcocystis species identification based on nested PCR of 28S rRNA and ITS1, following the sequencing of amplified DNA fragments. Six known Sarcocystis spp., S. cornixi, S. glareoli, S. halieti, S. kutkienae, S. turdusi, and S. wobeseri, along with three genetically distinct species (Sarcocystis sp. Rod3, Sarcocystis sp. Rod4, and Sarcocystis sp. Rod5), were identified. Phylogenetically, these three potentially new species clustered with Sarcocystis spp. characterised by a rodents-birds life cycle. Sarcocystis spp. employing rodents and birds as their intermediate hosts were detected in 66.7% and 50.0% of samples, respectively. These findings are consistent with the diet preferences of Common Buzzards. Notably, co-infections with two or more species were observed in a half of the samples. Altogether, the obtained results indicate that the Common Buzzard could serve as definitive host of various Sarcocystis species.
Gut Microbiota Profiling as a Promising Tool to Detect Equine Inflammatory Bowel Disease (IBD)
Authors: Sävilammi Tiina , Alakangas Rinna-Riikka , Häyrynen Tuomas , Uusi-Heikkilä Silva
Published: August 2024

Gastrointestinal disorders are common and debilitating in horses, but their diagnosis is often difficult and invasive. Fecal samples offer a non-invasive alternative to assessing the gastrointestinal health of horses by providing information about the gut microbiota and inflammation. In this study, we used 16S sequencing to compare the fecal bacterial diversity and composition of 27 healthy horses and 49 horses diagnosed with inflammatory bowel disease (IBD). We also measured fecal calprotectin concentration, a marker of intestinal inflammation, in healthy horses and horses with IBD. We found that microbiota composition differed between healthy horses and horses with IBD, although less than five percent of the variation in microbiota composition was explained by individual health status and age. Several differentially abundant bacterial taxa associated with IBD, age, or body condition were depleted from the most dominant Firmicutes phylum and enriched with the Bacteroidota phylum. An artificial neural network model predicted the probability of IBD among the test samples with 100% accuracy. Our study is the first to demonstrate the association between gut microbiota composition and chronic forms of IBD in horses and highlights the potential of using fecal samples as a non-invasive source of biomarkers for equine IBD.