Agriculture Communications最新文献

{"title":"Micro-encapsulation of oat oil using OSA starch with varying crystal structure and particle size: A study on the encapsulation properties and in vitro release behavior","authors":"Nuo Wang ,&nbsp;Yongqiang Liang ,&nbsp;Junjuan Wang ,&nbsp;Liang Zou ,&nbsp;Xiaoyan Zhao ,&nbsp;Dan Wang ,&nbsp;Yuanyuan Zhao ,&nbsp;Zhiwen Ge ,&nbsp;Lizhen Zhang ,&nbsp;Peiyou Qin","doi":"10.1016/j.agrcom.2025.100072","DOIUrl":"10.1016/j.agrcom.2025.100072","url":null,"abstract":"<div><div>This study assessed the effect of octenyl succinic anhydride (OSA)-modified quinoa, rice, maize, potato and pea starches (Q-OSA, R-OSA, M-OSA, Pt-OSA, P-OSA, respectively) with different crystal structures and particle sizes on the morphological, physicochemical, encapsulation and oil release properties of spray-dried oat oil microcapsules. The microcapsules showed an intact particle morphology and successful encapsulation of oat oil by the wall materials. Microcapsules with small granular starch as the wall material formed spherical aggregates after spray drying. OSA modification mainly occurred in the amorphous region of the starch and thus did not change the starch crystal pattern, but it led to a decrease in the relative crystallinity (RC) of the starch. OSA modification enhanced the emulsifying capacity of starch, whereas it decreased their thermal stability (<em>p</em> ​&lt; ​0.05). Q-OSA, with A-type starch and the smallest particle size (1.48 ​μm), showed the highest degree of substitution (DS, 0.0181), the best emulsification properties (EAI, 1.336 ​m²/g), and the greatest encapsulation efficiency (EE, 90.77%). Conversely, P-OSA, with C-type starch and the second largest particle size (26.63 ​μm), smaller than Pt-OSA (B-type, 41.15 ​μm), exhibited the lowest DS (0.0091) and EE (79.66%). OSA modification reduced the oil release of microcapsules in the gastric stage, thereby achieving the targeted release of oat oil at the intestinal stage. In particular, Q-OSA was the most effective in protecting oat oil against pepsin and the strong acidic environment. This study provides guidance on the use of OSA-modified small granular starch (e.g. quinoa starch) for encapsulation and delivery systems.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100072"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes of gene content in four crop species during domestication and breeding","authors":"Jakob Petereit ,&nbsp;Philipp E. Bayer ,&nbsp;Cassandria G. Tay Fernandez ,&nbsp;Jacqueline Batley ,&nbsp;David Edwards","doi":"10.1016/j.agrcom.2025.100077","DOIUrl":"10.1016/j.agrcom.2025.100077","url":null,"abstract":"","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100077"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of near-infrared spectroscopy and comparative principal component analysis for flour adulteration identification","authors":"Jinchao Qu ,&nbsp;Chu Zhang ,&nbsp;Shichen Gao ,&nbsp;Hongwu Tian ,&nbsp;Daming Dong","doi":"10.1016/j.agrcom.2025.100073","DOIUrl":"10.1016/j.agrcom.2025.100073","url":null,"abstract":"<div><div>Flour, as a critical component of the dietary structure, its quality and safety assurance is of great significance. The combination of near-infrared (NIR) spectroscopy and chemometrics was proposed to identify the adulterated flour in three different brands. This study obtained the adulterated samples with different concentrations of talcum powder, and measured 20 spectral data corresponding to each concentration. Comparative Principal Component Analysis (cPCA) has a constraint effect on the background dataset and can reduce the interference of background factors. The results showed that the cPCA algorithm successfully eliminated brand-related factors when identifying adulterated flour, and achieved adulterated discrimination with a concentration as low as 0.3%. This study presents a practical approach for identifying flour adulteration, effectively tackling the challenge of background factors on feature extraction in data dimensionality reduction models. By addressing this issue, it paves the way for developing more accurate and reliable adulteration detection models.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100073"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving freshness prediction in frozen fish burgers: A comparative study of propolis additives using ANN and RSM models","authors":"Fatemeh Koushki ,&nbsp;Mohsen Mokhtarian ,&nbsp;Mohsen Dalvi-Isfahan ,&nbsp;Hongwei Xiao ,&nbsp;Weipeng Zhang","doi":"10.1016/j.agrcom.2025.100078","DOIUrl":"10.1016/j.agrcom.2025.100078","url":null,"abstract":"<div><div>The freshness of fish burgers (FBs) declines during frozen storage. Here, we assessed FB freshness using quality control indicators (QCIs), including peroxide value (PV), total volatile basic nitrogen (TVB-N), and total viable count (TVC). Two predictive models were compared, one based on response surface methodology (RSM) and the other on an artificial neural network (ANN). Their accuracy was evaluated using frozen FBs that incorporated different concentrations of freeze-dried propolis (FDP; 0%–0.4%) and stored for various durations (0, 30, 60, and 90 days). Both FDP and storage time (ST) had significant effects (<em>p</em> ​&lt; ​0.01) on the quality control indicators (QCIs) of frozen FBs, with ST having a more significant effect than FDP on the QCI changes. A numerical optimization process determined that the optimal values of ST and FDP were approximately 27 days and 0.30 ​g/[100 ​g of fish paste], respectively. The coefficient of determination (R²) values for the QCIs of frozen FBs in the ANN model were 0.9657 for PV, 0.9753 for TVB-N, and 0.9872 for TVC. These values were slightly lower in the RSM model, 0.9717 for PV, 0.9603 for TVB-N, and 0.9861 for TVC. Overall, the ANN model with a 2-13-3 topology (13 neurons in the first hidden layer) showed greater potential for prediction of FB quality during frozen storage and was found to be the more efficient method.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100078"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of photoperiod on gonad development in female Pacific abalone (Haliotis discus hannai)","authors":"Qi Luo ,&nbsp;Yuhang Zhao ,&nbsp;Mo Zhang ,&nbsp;Huiyang Huang ,&nbsp;Caihuan Ke ,&nbsp;Xiaolong Gao","doi":"10.1016/j.agrcom.2025.100076","DOIUrl":"10.1016/j.agrcom.2025.100076","url":null,"abstract":"<div><div>Photoperiod has an impact on the growth and reproduction of marine species. This study assessed whether photoperiod affected the gonad development of Pacific abalone (<em>Haliotis discus hannai</em>), a commercially valuable marine mollusk. Abalone was cultured under three different photoperiodic conditions, 12L:12D (NL group), 18L:6D (LL group), and 24L:0D (WL group) while keeping other conditions constant. There were no significant differences in the survival rates of the three groups. However, compared to the other two groups, the 18L:6D photoperiod indicated a significantly higher gonad index (<em>p</em> ​&lt; ​0.05). The concentrations of 17β-estradiol (E2) and testosterone (T) were also significantly higher in the LL group (<em>p</em> ​&lt; ​0.05). Metabolomics analysis revealed that prostaglandins (PGs), trenbolone acetate (TBA), adenylosuccinic acid, and adenosine 5′-monophosphate were key metabolic indicators essential for fostering gonad development. Quantitative analysis of fatty acid revealed 39 fatty acids in the LL group and lower in the NL group, with arachidonic acid (ARA) being the highest in the LL group. Furthermore, it was found that the metabolite (PG) and genes (<em>PTGR1, COI</em>) involved in the ARA metabolic pathway were significantly highly expressed (<em>p</em> ​&lt; ​0.05) in the LL group, indicating that gonad development in female abalone depended on the ARA metabolic pathway. This study provides a novel understanding of the metabolic pathways involved in the photoperiodic regulation of gonad development in abalone. Furthermore, it enhances the knowledge of abalone reproductive biology and offers scientific data for developing a key technology to regulate rapid and synchronized gonad development in abalone.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100076"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drought adaptation and economic impacts on smallholder rice farmers","authors":"Prabhakaran T. Raghu ,&nbsp;Prakashan Chellattan Veettil ,&nbsp;Sukanya Das","doi":"10.1016/j.agrcom.2025.100075","DOIUrl":"10.1016/j.agrcom.2025.100075","url":null,"abstract":"<div><div>Frequent droughts pose a significant threat to sustainable agricultural development, particularly in vulnerable regions. This study investigated the adoption and impacts of <em>Sahbhagi Dhan</em>, a drought-tolerant rice variety, among marginal and tribal farmers who heavily relied on rice farming for their livelihoods. Based on household survey data from 2710 households collected in 2017, the findings revealed that 37.7% of the sample households adopted <em>Sahbhagi Dhan</em> between 2013 and 2016. Farmers who adopted this variety achieved higher yields and incomes compared to those cultivating other rice varieties. Notably, during drought years, yields losses of <em>Sahbhagi Dhan</em> were limited to only 13.6% compared to yields under normal conditions, demonstrating its resilience. The adoption of <em>Sahbhagi Dhan</em> also contributed to a significant reduction in rice-fallow areas by improving land use efficiency during challenging climatic conditions. However, seed unavailability emerged as a major barrier, leading to the discontinuation of cultivation among farmers. To enhance food security and build drought resilience, it is essential to ensure the availability of climate-resilient varieties like <em>Sahbhagi Dhan</em>. Additionally, providing timely and relevant information can encourage adoption among non-adopters and support farmers who discontinued its use.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100075"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of bruised apples using structured light stripe combination image and stem/calyx feature enhancement strategy coupled with deep learning models","authors":"Junyi Zhang ,&nbsp;Liping Chen ,&nbsp;Ruiyao Shi ,&nbsp;Jiangbo Li","doi":"10.1016/j.agrcom.2025.100074","DOIUrl":"10.1016/j.agrcom.2025.100074","url":null,"abstract":"<div><div>This study presented a novel approach that integrated visible structured-illumination reflectance imaging (SIRI) with deep learning techniques to concurrently identify the stem, calyx, and bruise in apple. Structured light images of apple samples were acquired at five frequencies (0.15, 0.20, 0.25, 0.30, and 0.50 cycles mm⁻¹) at four time points (0, 6, 12, and 24 ​h) using a developed SIRI. A three-step phase-shifting method was then applied to demodulate the images to obtain the direct component (DC), alternating component (AC), and the ratio (RT) images. Independent stripe images were extracted and skeletonized, and superimposed onto the original AC and RT images to generate a composite image with enhanced stem/calyx features. Three deep learning models (Faster R–CNN, YOLO-v5s, and YOLO-v8n) were used to recognize apple stem/calyx and bruise regions. The study showed that the composite image with an optimal frequency of 0.30 cycles mm⁻¹ can improve recognition accuracy. Among the three models, the YOLO-v8n achieved the highest classification accuracy (99.12%) for detecting bruised apples.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100074"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CAD1 enhances antioxidant activity to facilitate cold storage by regulating flavonoid synthesis in cucumber","authors":"Changxuan Xia ,&nbsp;Shanshan Yin ,&nbsp;Jian Zhang ,&nbsp;Huitong Teng ,&nbsp;Ying Li ,&nbsp;Aijun Mao ,&nbsp;Changlong Wen","doi":"10.1016/j.agrcom.2025.100071","DOIUrl":"10.1016/j.agrcom.2025.100071","url":null,"abstract":"<div><div>Improving antioxidant activity to preserve nutritional quality and enhance environmental resilience is a primary goal in vegetable breeding. Cucumber is known to have relatively low antioxidant activity among commonly consumed vegetables, yet the specific genetic factors underlying this trait remain largely unexplored. In this study, a significantly divergence in the antioxidant activity of cucumber inbred lines was revealed by Ferric Ion Reducing Antioxidant Power (FRAP) assay. A gene responsible for this divergence, designated as <em><u>C</u></em><em>vergence <u>1</u></em> (<em>CAD1</em>), was map-based cloned through Bulked Segregant Analysis (BSA) sequencing and molecular marker-assisted selection from a F₂ population. Subsequently, gene editing and overexpression analysis demonstrated that <em>CAD1</em> is essential for antioxidant activity. Furthermore, qRT-PCR and phylogenetic tree analysis showed that <em>CAD1</em> encodes a fruit-specific expressed MYB transcription factor. Comprehensive untargeted metabolomics analysis and Electrophoretic Mobility Shift Assay <strong>(</strong>EMSA) revealed that <em>CAD1</em> transcriptionally activates genes involved in flavonoid synthesis<em>,</em> thereby promoting flavonoid production and boosting the antioxidant activity of cucumber. Finally, cold treatment showed that <em>CAD1</em> improves cold storage resilience, which is directly activated by <em>CsCBF2</em>. In summary, this study provides valuable insights and data for breeding cucumbers with enhanced antioxidant activity.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100071"},"PeriodicalIF":0.0,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protected cultivation can mitigate carbon emissions for tomato production","authors":"Hairong Gao ,&nbsp;Shaokai Wang ,&nbsp;Dandan Shen ,&nbsp;Wenshuang Li ,&nbsp;Yan Zhang ,&nbsp;Jingyi Deng ,&nbsp;Jiapeng Jiao ,&nbsp;Pinge Huang ,&nbsp;Qianli Ma ,&nbsp;Yuan Huang ,&nbsp;Fangting Yuan ,&nbsp;Xin Wang ,&nbsp;Junhong Zhang ,&nbsp;Wenyue Liao ,&nbsp;Mengjie Li ,&nbsp;Yan Yan ,&nbsp;Qiang Li ,&nbsp;Yunjiang Cheng","doi":"10.1016/j.agrcom.2024.100065","DOIUrl":"10.1016/j.agrcom.2024.100065","url":null,"abstract":"<div><div>Protected cultivation enables the production of vegetables and fruits throughout the year without compromising of farming field for grain production. However, it is generally associated with high resource consumption, including building materials, consumables, and energy, raising severe concerns about its future sustainability, especially the intensity of its carbon emissions, which is less well-understood. This study focused on the carbon emissions of two typical protected cultivation constructions for tomato cultivation in China, using life cycle assessment (LCA). Tomato production generated 354.4 and 173.1 kg CO₂-eq/ton carbon emissions in a typical solar greenhouse in northern China and a typical naturally ventilated polyhouse in southern China, which represented 41.9% and 21.7% reduction, respectively, compared to field production in the same area. Further analysis of protected cultivation inputs revealed that agricultural consumables are the main contributors to carbon emissions. Among them, fertilizers were the dominant contributor to carbon emissions, accounting for 73.0% and 67.5% of the total carbon emissions for solar greenhouses and polyhouses, respectively. Based on this finding, a sensitivity analysis revealed the potential of two advanced fertilizer management practices to reduce carbon emissions. Drip irrigation and slow-release fertilizers in protected cultivation can reduce carbon emissions by 16.5–17.7% and 12.9–13.8%, respectively, compared to traditional chemical fertilizers. In addition, the analysis of environmental effects suggested that protected tomato production can significantly reduce environmental impact. Overall, this research highlighted that protected cultivation can substantially mitigate carbon emissions, demonstrating its high efficiency toward low-carbon agriculture.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100065"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143163104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing field soil moisture content monitoring using laboratory-based soil spectral measurements and radiative transfer models","authors":"Jibo Yue ,&nbsp;Ting Li ,&nbsp;Haikuan Feng ,&nbsp;Yuanyuan Fu ,&nbsp;Yang Liu ,&nbsp;Jia Tian ,&nbsp;Hao Yang ,&nbsp;Guijun Yang","doi":"10.1016/j.agrcom.2024.100060","DOIUrl":"10.1016/j.agrcom.2024.100060","url":null,"abstract":"<div><div>Accurate information on the soil moisture content in croplands is essential for monitoring crop growth conditions. This study aimed to enhance soil moisture monitoring by employing laboratory-based soil spectral measurements and radiative transfer models. This study comprised three main components: (1) Utilizing laboratory-measured soil spectra to investigate the influence of soil moisture content on soil spectral properties (n ​= ​178), and describing the impact of canopy coverage on the mixed spectra of wheat and soil in croplands using a radiative transfer model (RTM) (n ​= ​144, 180); (2) employing a deep learning model trained on extensive simulated datasets to estimate soil moisture beneath the canopy from wheat‒soil mixed spectra (n ​= ​200); and (3) comparing the performance of deep learning model with statistical regression techniques based on soil moisture spectral index (SI) for estimating wheat fractional vegetation cover (FVC) and relative soil moisture content (RMC) under medium to low canopy coverage. The conclusions of this study were as follows: (1) Compared with the conventional statistical regression approaches, the deep learning model exhibited superior accuracy in estimating RMC across all levels of normalized difference vegetation index (NDVI). (2) By combining laboratory soil spectral measurements with an RTM, a pretrained dataset can be created. When combined with transfer learning techniques (FVC: <em>R</em>² ​= ​0.782, RMSE ​= ​0.107, and RMC: <em>R</em>² ​= ​0.825, RMSE ​= ​0.130), this approach enhanced the accuracy of estimating wheat FVC and RMC. Future research should expand experiments to include additional regions and crop types to verify the accuracy and generalizability of this method for estimating FVC and RMC under various remote sensing conditions.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100060"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}