Agricultural Research最新文献

{"title":"Enabling Smart Agriculture: An IoT-Based Framework for Real-Time Monitoring and Analysis of Agricultural Data","authors":"Faruk Enes Oguz,&nbsp;Mahmut Nedim Ekersular,&nbsp;Kubilay Muhammed Sunnetci,&nbsp;Ahmet Alkan","doi":"10.1007/s40003-024-00705-x","DOIUrl":"10.1007/s40003-024-00705-x","url":null,"abstract":"<div><p>With the progress in sensor and cloud technologies in contemporary times, a range of intelligent agriculture applications has gained considerable prominence. It is predicted that these developments can continue to pique the interest of researchers in the future. On the other hand, it is seen that IoT (Internet of Things)-based models are used in various fields. Herein, the primary objectives of this study are to enable farmers to remotely monitor and manage field conditions through sensor technology and IoT integration. In addition, these technological advancements make it possible to take the required measurements. Farmers can optimize their agricultural practices based on the analysis of the data obtained for this application. Thus, the aim is to manage the agricultural process more effectively and efficiently. In this study, an IoT-based framework is proposed for agricultural data monitoring. Light, temperature–pressure, smoke, humidity, and soil dryness values can be measured from GY-30, BME280, MQ-2, DHT11, and YL-69, respectively. An ESP-32S development board is used to collect data from sensors, and this board is coded using Arduino IDE. Subsequently, using ESP-32S, it is sent to the ThingSpeak cloud service provided by MATLAB via a Wi-Fi connection. Thus, these data can be easily transferred to MATLAB. We create a user-friendly Graphical User Interface application so that the data can be monitored and analyzed in MATLAB as well as ThingSpeak. This application allows users to monitor the data flow in real time and can easily provide the requested values such as maximum, minimum, mean, standard deviation, and current with the help of a button. In addition, the proposed system sends an e-mail to the user when soil dryness and smoke values exceed a certain threshold value. The results obtained in the study indicate that the proposed model can save time and labor in addition to providing reliable and fast data flow.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"13 3","pages":"574 - 585"},"PeriodicalIF":1.4,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140425333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sorghum Yield Using Rectangular Versus Spherical zaï Pits and Integrated Soil Fertility Management in the Sahelian and Sudano-Sahelian Zones of Burkina Faso","authors":"Abdoulaye Dabre,&nbsp;Patrice Savadogo,&nbsp;Lassina Sanou,&nbsp;Hassan Bismarck Nacro","doi":"10.1007/s40003-023-00690-7","DOIUrl":"10.1007/s40003-023-00690-7","url":null,"abstract":"<div><p>Poor farming practices have contributed to the degradation of the majority of soils in Burkina Faso. This has led to the formation of bare soils and new clearings. These soils are generally reclaimed by <i>zaï</i>, an ancestral water and soil conservation practice that needs further improvement to ensure food security. The following study consisted of giving a rectangular shape to the usually spherical <i>zaï</i> pits in order to measure sorghum yield’s parameters in a factorial design: type of amendments (compost + NPK and compost + urea + Burkina phosphate); length (35 and 45 cm) and depth of the pits (10 and 20 cm) with 4 replications. Using the sites of Kiembara (Sahelian zone) and Arbollé (Southern Sudan-Sahelian zone), sorghum growth, biomass, grain yield, harvest index and threshing rate were measured. Overall, highlight the importance of rainwater harvesting using <i>zaï</i> pits and the use of manure in combination with mineral fertilizer supplements in improving soil fertility and enhancing crop yields. There is good evidence that grain yield was significantly improved under rectangular <i>zaï</i> with 45-cm-long pits (2032.7 kg.ha⁻¹ in Kiembara, 1561.7 kg.ha⁻¹ in Arbollé) than under ordinary <i>zaï</i> (1053.6 kg.ha⁻¹ in Kiembara; 990.2 kg.ha⁻¹ at Arbollé). This yield improved further with the application of compost combined with Burkina phosphate and urea under the rectangular <i>zaï</i> of 45-cm-long and 20-cm deep pits, 2333.9 kg.ha⁻¹ in Kiembara and 1967.7 kg.ha⁻¹ in Arbollé. Under ordinary <i>zaï</i>, the same inputs resulted in a grain yield of around 1034.5 kg.ha⁻¹ in Kiembara and 916 kg.ha⁻¹ in Arbollé. Hence, rectangular <i>zaï</i> was better than ordinary <i>zaï</i> in increasing the agronomic parameters of sorghum, especially in the Sahelian agroclimatic zone, providing good water conditions to produce enough useful cobs and therefore a solution to reduce food insecurity.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"13 2","pages":"253 - 265"},"PeriodicalIF":1.4,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140427265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Distribution of Dry Matter and Leaf Area of Faba Bean (Vicia faba) Using Nonlinear Regression Models","authors":"Najibullah Ebrahimi,&nbsp;Ahmad Reza Salihy,&nbsp;Sabqatullah Alipour,&nbsp;Sayed Hamidullah Mozafari,&nbsp;Jawad Aliyar,&nbsp;Ibrahim Darwish","doi":"10.1007/s40003-024-00700-2","DOIUrl":"10.1007/s40003-024-00700-2","url":null,"abstract":"<div><p>Growth analysis is a valuable method for quantitatively investigating the growth and development of products. To analyze plant growth during the growing season, access to accurate and regular plant information is needed, which is obtained by measuring leaf surface and dry matter accumulation. The use of nonlinear regression models is expanding due to having parameters with physiological meaning in growth analysis. Of these models, there are beta, logistic, Gomperts, Richards, linear, cut and symmetric linear models. Therefore, this study was conducted on bean plant of the variety “Barakt” under factorial experiment in the form of basic randomized complete block design with four crop densities in four replications under rainfed conditions at the research farm of Gorgan University of Agricultural Sciences and Natural Resources in 2014–2015, located in the west of Gorgan, with a latitude of 37° and 45 min north and a longitude of 54° and 30 min east and an altitude of 120 m above sea level. In this study, the nonlinear beta and logistic regression models were fitted to leaf surface data, and beta, Gompertz and logistic models were fitted to bean dry weight. The AICc criterion analysis showed that the beta model had a better fit than the logistic model for leaf area. According to this model under various crop densities, LAI_max was between 2.30 and 5.30 g per square meter, <i>t</i>_m was from 131.90 to 144.20 days after planting, and <i>t</i>_e was between 158.7 and 163.50 days. Also, the analysis of the AICc criterion for dry matter accumulation showed that the beta model was better in fitting the dry matter accumulation than Gomperts and logistic models. According to this model, <i>W</i>_max varied between 1.725 and 1484.3 g per square meter, <i>t</i>_m between 138.30 and 146.40 days after planting, and <i>t</i>_e between 162.60 and 179.0 days in different densities.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"13 2","pages":"381 - 389"},"PeriodicalIF":1.4,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140428810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meteorological Factor-Based Tomato Early Blight Prediction Using Hyperparameter Tuning of Intelligent Classifiers","authors":"Ayushi Gupta,&nbsp;Anuradha Chug,&nbsp;Amit Prakash Singh","doi":"10.1007/s40003-023-00691-6","DOIUrl":"10.1007/s40003-023-00691-6","url":null,"abstract":"<div><p>Early blight is a severe disease which affects several plant species, including tomato plants. Weather parameters such as temperature, leaf wetness, soil moisture, and relative humidity play a vital role in the growth of diseases in plants. The current study analyses the effect of weather parameters on the development of early blight disease in tomato plants by utilizing traditional machine learning techniques. A real-time dataset TomEBD, comprising five weather parameters, has been employed. Three resampling techniques—Synthetic Minority Oversampling Technique(SMOTE), K-Means SMOTE(KM-SMOTE) and Support Vector Machine SMOTE(SVM-SMOTE)—have been used to balance the dataset. Five different machine learning classifiers—k-Nearest Neighbor(kNN), Support Vector Machine(SVM), Random Forest(RF), Artificial Neural Network(ANN), and Kernel Extreme Learning Machine(KELM)—have been used to classify a plant as healthy or diseased based on meteorological factors. The five classifiers are used on the imbalanced and three balanced datasets, resulting in 20 models. Hyperparameter tuning of all five classifiers has been done for optimization. The results indicate that out of the 20 models evaluated, the proposed model KELM-KM - KELM classifier on KM-SMOTE balanced data outperforms all others with a mean accuracy of 85.82%. A comparison with the existing studies shows that KELM-KM outperforms the state of the art without involving any complex feature extraction techniques. Therefore, it can be used to alarm the farmers for fungicide spray on diseased plants in conducive environments.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"13 2","pages":"232 - 242"},"PeriodicalIF":1.4,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40003-023-00691-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140431569","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":"The Influence of Plant Growth Modulators on Physiological Yield and Quality Traits of Sesame (Sesamum indicum) Cultivars Under Rainfed Conditions","authors":"E. Sonia,&nbsp;P. Ratnakumar,&nbsp;Brij B. Pandey,&nbsp;K. Ramesh,&nbsp;S. Narendra Reddy,&nbsp;V. Hemalatha,&nbsp;A. L. Sravanthi,&nbsp;P. S. John Daniel,&nbsp;Ch. L. N. Manikanta,&nbsp;K. T. Ramya,&nbsp;P. L. Anusha,&nbsp;Y. Praduman,&nbsp;D. Padmaja","doi":"10.1007/s40003-024-00704-y","DOIUrl":"10.1007/s40003-024-00704-y","url":null,"abstract":"<div><p>Sesame is an important oilseed crop, and the crop yields frequently fluctuate as the crop is largely grown in rainfed and low-fertile lands. Limited water availability negatively affects many physiological processes and the final productivity of sesame. Limited work has been carried out in the past to understand the role of plant growth regulators (PGRs) in modulating sesame growth and development for optimum productivity. A field study was conducted under rainfed conditions to evaluate the response of foliar application of different PGRs such as hormonal-based gibberellic acid (20 ppm); chemical-based thiourea (500 ppm); chemical-constituting structural component-based ortho-silicic acid (380 ppm); and control (water-sprayed) on sesame cultivars: Swetha til, GT-10, TKG-22, and JCSDT-26. The PGRs foliar application was done at the vegetative (25–30 days after sowing), 50% flowering (40–45 days after sowing), and seed development (70–75 days after sowing) stages of the crop. The results revealed that application of different PGRs positively influenced the plant’s growth, physiological, yield and quality traits; however, most effective results were obtained with gibberellic acid (20 ppm), followed by ortho-silicic acid (380 ppm), and thiourea (500 ppm) improved the morphological, yield, and yield-attributing traits. The interaction between PGRs and varieties was found significant and among the sesame cultivars, swetha til followed by JCSDT-29 was found most promising. The application of PGRs has significantly improved the plant height, leaf area, number of branches, capsules, seeds/capsules, seed yield oil content, and fatty acid content compared to the control by gibberellic acid, followed by ortho-silicic acid and thiourea. The interaction between PGRs and varieties was found to be significant, and cultivar Swetha til, a white-colored cultivar performed most superiorly among the different tested cultivars in terms of growth, physiology, yield as well and quality traits when treated with GA3 at 20 ppm. The seed yield was enhanced by 25–26%, 11–12%, and 6–7% with the application of gibberellic acid, ortho-silicic acid, and thiourea, respectively, over control. Considering the findings, it can be concluded that the application of PGRs (thiourea, ortho-silicic acid, and gibberellic acid) significantly enhanced the growth, physiology, yield, and quality of sesame under rainfed conditions; however, GA₃ at 20 ppm was found most effective and may not only enhance the optimum productivity but also effective in improving the quality traits of sesame.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"13 3","pages":"436 - 449"},"PeriodicalIF":1.4,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140431016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Local Agroecological Practices and Chemical Inputs used in Mint Farming Systems, Regions of Fez-Meknes and Casablanca-Settat, Morocco","authors":"Wijdane Rhioui, Jamila Al Figuigui, Rachid Lahlali, Haïtam Lahmamsi, Salah-Eddine Laasli, Asmae Benabderrahmane, Saadia Belmalha","doi":"10.1007/s40003-023-00694-3","DOIUrl":"https://doi.org/10.1007/s40003-023-00694-3","url":null,"abstract":"","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"16 7","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Did Covid-19 Impacted Market Arrivals and Prices of Major Food Commodities in India: Evidence from Extended Time Series Analysis","authors":"Dinesh Chand Meena, Purushottam Sharma, MD. Ejaz Anwer","doi":"10.1007/s40003-023-00695-2","DOIUrl":"https://doi.org/10.1007/s40003-023-00695-2","url":null,"abstract":"","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"11 2","pages":"1-12"},"PeriodicalIF":1.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139854703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Assessment of Rhizobium tropici and Azospirillum brasilense Co-Inoculation in Common Bean","authors":"Matheus Messias,&nbsp;Enderson Petrônio de Brito Ferreira,&nbsp;Osmira Fátima da Silva,&nbsp;Alcido Elenor Wander","doi":"10.1007/s40003-023-00692-5","DOIUrl":"10.1007/s40003-023-00692-5","url":null,"abstract":"<div><p>The common bean cropping system has a high cost, mainly due to using nitrogen fertilisers. An alternative for a replacement to reduce production costs is the co-inoculation technique of <i>Rhizobium tropici</i> and <i>Azospirillum brasilense</i>. This study aimed to evaluate the economic viability of co-inoculation of common beans via sowing furrow. Data from five field experiments conducted in three locations in three seasons were used. The treatments consisted of absolute control (without inoculation and fertilisation), nitrogen fertilisation, simple inoculation with <i>R. tropici</i> and co-inoculation with <i>R. tropici</i> and different doses of <i>A. brasilense</i> applied in the sowing furrow. The economic analysis was carried out based on market prices and indexes, depending on the grain production of the different treatments. Treatment with nitrogen fertiliser (80 kg ha⁻¹ of N) resulted in higher production costs, with an average value of USD 1,889 ha⁻¹. Co-inoculation with two doses of <i>R. tropici</i> and four doses of <i>A. brasilense</i> provided the highest mean gross revenue values, net income and benefit-cost-ratio. Co-inoculation with two doses of <i>R. tropici</i> and four doses of <i>A. brasilense</i> resulted in a benefit-cost-ratio of 8 to 11% greater than simple inoculation with <i>Rhizobium tropici</i>, nitrogen treatment and commercial inoculant. Co-inoculation with <i>R. tropici</i> and <i>A. brasilense</i>, in addition to providing high yields, also provides high profitability, proving to be a technology that can contribute to the reduction/replacement of the use of nitrogen fertilisers and reduction of environmental impacts without compromising yield and profitability of common beans.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"13 2","pages":"216 - 224"},"PeriodicalIF":1.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40003-023-00692-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139855391","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":"Did Covid-19 Impacted Market Arrivals and Prices of Major Food Commodities in India: Evidence from Extended Time Series Analysis","authors":"Dinesh Chand Meena,&nbsp;Purushottam Sharma,&nbsp;Md. Ejaz Anwer","doi":"10.1007/s40003-023-00695-2","DOIUrl":"10.1007/s40003-023-00695-2","url":null,"abstract":"<div><p>The COVID-19 pandemic and subsequent lockdown policy significantly impacted all sectors of the economy, including agriculture. It disrupted the market’s normal functions in multiple ways; hence, this study was conducted using extended time series data to estimate the impact of the nationwide lockdown on market arrivals, price margin, and wholesale and retail prices of major food commodities. The study employed the multiple policy interventions interrupted time series analysis (ITSA) model to estimate pre-and post-intervention price trends change following lockdowns in 2020 and 2021. The results indicated that most agricultural commodities witnessed a substantial decrease in market arrivals, and there were heterogeneous effects on price margins across commodities and lockdown periods. ITSA results reveal that wholesale and retail prices for wheat and rice decreased significantly due to record crop harvests in 2019–20 and free distribution through Government welfare programs (PMGKAY). In contrast, the wholesale and retail price of pulses dal and mustard oil increased significantly during the lockdown period of 2020 and 2021. Overall, the Government managed the lockdown in 2021 better than in 2020, enabling access to essential goods and services, transportation and other conveniences. Furthermore, the study suggests policies to enhance the supply chain’s responsiveness and resilience to future pandemics and natural disasters, given the lessons learned from the COVID-19 lockdown.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"13 2","pages":"340 - 351"},"PeriodicalIF":1.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139794828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Assessment of Rhizobium tropici and Azospirillum brasilense Co-Inoculation in Common Bean","authors":"Matheus Messias, Enderson Petrônio de Brito Ferreira, Osmira Fátima da Silva, Alcido Elenor Wander","doi":"10.1007/s40003-023-00692-5","DOIUrl":"https://doi.org/10.1007/s40003-023-00692-5","url":null,"abstract":"","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"29 13","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139795722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}