Agricultural Systems最新文献

{"title":"Estimating environmental efficiency in dairy production using by-production technology","authors":"Yashree Mehta ,&nbsp;Marion Reichenbach ,&nbsp;Bernhard Brümmer ,&nbsp;Eva Schlecht","doi":"10.1016/j.agsy.2024.104200","DOIUrl":"10.1016/j.agsy.2024.104200","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Milk production in developing countries is characterized by low per animal yield and disproportionately high GHG emissions. Specific policy recommendations are necessary to improve the technical as well as environmental efficiency of dairy production, especially for small farms. However, limited financial resources owned by producers lead to high transaction costs of introducing change. Both, concentrate feed and roughage, that is dry nonconcentrates, are used in milk production. These inputs are also responsible for methane emissions through enteric fermentation. Especially cellulose-rich dry nonconcentrates are fueling methane emissions through enteric fermentation.</div></div><div><h3>OBJECTIVE</h3><div>Based on a systems approach including nutritional foundations, we estimated technical and environmental efficiency of dairy producers in the rural-urban interface of Bengaluru, India. We studied the shortfall in milk production and excess methane emissions for each dairy farm and their drivers.</div></div><div><h3>METHODS</h3><div>Using panel data of 245 dairy producers, we fitted the production frontier for estimating technical efficiency and treated the emission generating technology like a cost frontier for estimating environmental efficiency – using stochastic frontier analysis. This study uses the parametric application of by-production technology.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>High heterogeneity in enteric methane emissions at low levels of milk yield are related to excessive feeding of dry nonconcentrates by producers. Plotting excess methane emissions beyond the fitted frontier against the share of concentrates in the total feed ration indicated that a global low is reached at around 40 % concentrates in the cows' diet. Therefore, farmers should intensify production by increasing the share of concentrate feed in dairy cattle rations to this level. Also, we suggest promoting the construction of cattle sheds and increasing the proportion of cows with high milk production potential in the herd to improve environmental efficiency.</div></div><div><h3>SIGNIFICANCE</h3><div>With economic growth as well as an increase in population, the demand for dairy products in developing countries will increase and lead to an expansion of dairy production. GHG emissions such as methane from livestock rearing will have to be managed and adequate policy measures will have to be implemented to reduce their share in global GHG emissions. By integrating animal nutrition perspectives and environmental efficiency from economics into a systems approach, we propose specific recommendations for public policy in terms of the target group of producers and the correct proportion of concentrate feed and dry nonconcentrates in total feed rations for dairy cattle in India. This will ensure that producers reach their full potential in milk production and environmental sustainability.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104200"},"PeriodicalIF":6.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Yield prediction through UAV-based multispectral imaging and deep learning in rice breeding trials","authors":"Hongkui Zhou ,&nbsp;Fudeng Huang ,&nbsp;Weidong Lou ,&nbsp;Qing Gu ,&nbsp;Ziran Ye ,&nbsp;Hao Hu ,&nbsp;Xiaobin Zhang","doi":"10.1016/j.agsy.2024.104214","DOIUrl":"10.1016/j.agsy.2024.104214","url":null,"abstract":"<div><h3>Context</h3><div>Predicting crop yields with high precision and timeliness is essential for crop breeding, enabling the optimization of planting strategies and efficients resource allocation while ensuring food security. Current research in this field typically does not address the problem of yield prediction in the diverse context of breeding experiments involving numerous varieties. However, evaluating the performance of prediction models across multiple varieties is vital for further model refining and enhancing model robustness and adaptability.</div></div><div><h3>Objective</h3><div>This study aims to evaluate the performance of feature- and image-based yield prediction models for yields with multiple varieties to compare their capabilities and determine an appropriate timing for early yield prediction.</div></div><div><h3>Methods</h3><div>This study combines unmanned aerial vehicle (UAV)-based multispectral remote sensing imagery with machine learning and deep learning-based algorithms to develop rice yield prediction models across multiple varieties. The performances of both feature- and image-based models are evaluated. The feature-based models considered in this study include random forest (RF), deep neural network (DNN), and long short-term memory (LSTM) algorithms, and the image-based models are convolutional neural network (CNN) architectures, including both two-dimensional (2D) and three-dimensional (3D) CNN models. To assess the performance of the multi-variety crop yield prediction models thoroughly, this study considers two sampling scenarios: stratified sampling and group sampling.</div></div><div><h3>Results and conclusions</h3><div>The results show that the image-based deep learning models outperform the feature-based machine learning models, which indicates their superior robustness in multi-variety scenarios and highlights their significant potential of directly extracting spatiotemporal features from images for yield prediction. The results indicate that the multi-temporal 2D CNN model (i.e., the CNN-M2D model) can achieve the best yield prediction performance among all models, achieving RRMSE = 8.13 % and R² = 0.73. The prediction results also demonstrate good consistency with the observed data, indicating an efficient capturing of spatial pattern variations in yield across different varieties. Based on the results, with the crops progressing along the growth stages, the accuracy of the yield prediction models improves gradually, achieving the best prediction performance during the flowering to grain-filling stage. Finally, according to the results, the optimal lead time for predicting rice yield is approximately one month before harvest.</div></div><div><h3>Significance</h3><div>Our study can provide a reference for the research community in yield prediction and high-yield variety selection in breeding trials.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104214"},"PeriodicalIF":6.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stakeholder perspectives on ecosystem services in agricultural landscapes: A case study in the North China Plain","authors":"Jiali Cheng ,&nbsp;Andries Richter ,&nbsp;Wen-Feng Cong ,&nbsp;Zhan Xu ,&nbsp;Zhengyuan Liang ,&nbsp;Chaochun Zhang ,&nbsp;Fusuo Zhang ,&nbsp;Wopke van der Werf ,&nbsp;Jeroen C.J. Groot","doi":"10.1016/j.agsy.2024.104187","DOIUrl":"10.1016/j.agsy.2024.104187","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Intensive agriculture is under pressure from changing demands from society, prompting the need to redesign agricultural landscapes to provide multiple ecosystem services (ESs). However, implementation of changed practices requires positive engagement from stakeholders. Therefore, their perspective on ecosystem services needs to be known.</div></div><div><h3>OBJECTIVE</h3><div>This study investigates stakeholders' perspectives on multiple ESs in Quzhou County, an area in the North China Plain used for intensified cereal production. We aim to elucidate perspectives within and across diverse stakeholder groups (farmers, companies, citizens, academics, village and township heads, and county government staff).</div></div><div><h3>METHODS</h3><div>Employing the Q methodology, we identified differences in perspectives within stakeholder groups and we compared the similarities and differences of those perspectives across stakeholder groups. We also investigated how farmers' personal and household characteristics were related to the perspectives they held.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Significant differences in preference emerged among stakeholder groups. Academics assigned higher importance to regulating and supporting services than other stakeholder groups and companies assigned less importance to cultural services. We identified 18 distinct perspectives across seven stakeholder groups. These perspectives showed a combination of preferences for at least two different ES categories. Most of the perspectives prioritize provisioning services whereas only few perspectives prioritize supporting services.</div></div><div><h3>SIGNIFICANCE</h3><div>This study exemplifies a bottom-up approach for systematically analyzing stakeholder perspectives on the relative importance of ESs derived from agricultural landscapes. The revealed differences and complexity of stakeholder perspectives can inform decision-making on the redesign of agricultural landscapes with stakeholder engagement. Recognizing areas of consensus and conflict can guide efforts to promote agroecologically sound practices and policies.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104187"},"PeriodicalIF":6.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equationing Arabica coffee: Adaptation, calibration, and application of an agrometeorological model for yield estimation","authors":"Cleverson Henrique de Freitas ,&nbsp;Rubens Duarte Coelho ,&nbsp;Jéfferson de Oliveira Costa ,&nbsp;Paulo Cesar Sentelhas","doi":"10.1016/j.agsy.2024.104181","DOIUrl":"10.1016/j.agsy.2024.104181","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;CONTEXT&lt;/h3&gt;&lt;div&gt;Coffee cultivation is important to Brazil's economy, positioning the country as a global leader in production and export. Given the complex environmental and management factors affecting yields, particularly due to climate change, there is a pressing need from farmers and dealers for more precise crop estimation models.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;This study aimed to refine and calibrate an agrometeorological model, originally developed by Santos and Camargo (2006) and later adapted by Verhage et al. (2017a), to estimate Arabica coffee yield in the main producing regions of Minas Gerais and São Paulo. Additionally, sensitivity analysis was also performed to identify the most influential model parameters and variables.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;Yield data from 28 coffee-producing locations (2003−2020) and meteorological data alongside irrigation use were employed. Following calibration and adaptation, a sensitivity analysis was conducted to determine the model's response to variations in coffee plant parameters and environmental conditions. Local sensitivity analysis (LSA) focused on meteorological variables, while global sensitivity analysis (GSA) addressed coffee-related parameters.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS AND CONCLUSIONS&lt;/h3&gt;&lt;div&gt;The adaptations proposed to the original model led to a significant refinement in the yield estimates, emphasizing the complex interactions between climatic variables and agricultural management practices. Key adaptations include the estimation of potential yield (Yp), the incorporation of temporal curves for root growth, leaf area index, available water capacity, and crop coefficient, as well as a water balance that accounts for irrigation and its effect on attenuating high canopy temperatures. Calibration improved the model's accuracy and precision, with the RMSE decreasing from 13.66 (819.6 kg ha&lt;sup&gt;−1&lt;/sup&gt;; 1 bag ha&lt;sup&gt;−1&lt;/sup&gt; = 60 kg ha&lt;sup&gt;−1&lt;/sup&gt;) to 8.65 (519.0 kg ha&lt;sup&gt;−1&lt;/sup&gt;) bags ha&lt;sup&gt;−1&lt;/sup&gt;, R&lt;sup&gt;2&lt;/sup&gt; improving from 0.62 to 0.65, d-index from 0.79 to 0.88, and NSE from 0.09 to 0.64. During the evaluation phase, with independent data, RMSE was 7.76 bags ha&lt;sup&gt;−1&lt;/sup&gt; (465.6 kg ha&lt;sup&gt;−1&lt;/sup&gt;), d-index 0.85, and R&lt;sup&gt;2&lt;/sup&gt; 0.55. Sensitivity analysis emphasized the importance of mean temperature and solar radiation on Yp, as well as the impact of irrigation practices and water deficit management under rainfed conditions. Additionally, factors specific to the coffee plant itself directly affect its yield.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;SIGNIFICANCE&lt;/h3&gt;&lt;div&gt;The findings underscore the importance of a multifactorial and adaptive approach to coffee cultivation, addressing the complexities and challenges posed by varying climatic conditions. This work offers valuable insights into optimizing coffee production, presenting the model as a tool for developing more resilient cultivation strategies and enhancing the sustainability of Brazilian Arabica coffee","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104181"},"PeriodicalIF":6.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land suitability modeling integrating geospatial data and artificial intelligence","authors":"Huezer Viganô Sperandio ,&nbsp;Marcelino Santos de Morais ,&nbsp;Luciano Cavalcante de Jesus França ,&nbsp;Danielle Piuzana Mucida ,&nbsp;Reynaldo Campos Santana ,&nbsp;Ricardo Siqueira da Silva ,&nbsp;Cristiano Reis Rodrigues ,&nbsp;Bruno Lopes de Faria ,&nbsp;Maria Luiza de Azevedo ,&nbsp;Eric Bastos Gorgens","doi":"10.1016/j.agsy.2024.104197","DOIUrl":"10.1016/j.agsy.2024.104197","url":null,"abstract":"<div><h3>Context</h3><div>Sustainable agricultural practices are critical in a world grappling with climate change and pressure on natural resources. Unplanned agricultural expansion often harms ecosystems and the services they provide. Balancing food production with environmental protection demands sophisticated tools like spatial analysis and artificial intelligence to inform land-use decisions.</div></div><div><h3>Objective</h3><div>This study introduces an AI-driven process to assess land suitability for agrosilvopastoral systems, going beyond traditional methods by incorporating a broader spectrum of landscape characteristics. Our approach integrates climate, water resources, soil properties, morphological features, and accessibility to enhance the accuracy of suitability mapping.</div></div><div><h3>Methods</h3><div>We constructed a data cube comprising 100 geospatial layers representing diverse landscape attributes. Field observations from two watersheds in Minas Gerais, Brazil, were used to train and validate a Random Forest classification model. We evaluated the model's accuracy and quantified the influence of each attribute group on suitability determination.</div></div><div><h3>Results</h3><div>Integrating climate, water, edaphic, and morphological attributes significantly improved the model's accuracy and provided a more nuanced understanding of agrosilvopastoral suitability compared to using only soil class, lithology, and slope. Climate and edaphic variables emerged as key drivers of suitability. This approach identified a more constrained, yet potentially more sustainable, distribution of suitable land.</div></div><div><h3>Significance</h3><div>Our findings highlight the need to transition from conventional land suitability assessments towards more holistic, data-driven approaches that consider the complex interplay of environmental factors. This model offers a valuable tool for guiding sustainable land-use planning, potentially mitigating environmental impacts while optimizing agrosilvopastoral production.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104197"},"PeriodicalIF":6.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk tolerance and climate concerns predict transformative agricultural land use change","authors":"Meredith T. Niles ,&nbsp;Philip Stahlmann-Brown ,&nbsp;Dennis Wesselbaum","doi":"10.1016/j.agsy.2024.104195","DOIUrl":"10.1016/j.agsy.2024.104195","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Research and policy continue to highlight the potential importance of transformative adaptations (involving wholly new systems, processes, or locations for activities) for climate and other future changes, including in agriculture. Despite this, there are few examples of transformative changes in action and insufficient understanding about the drivers that enable or facilitate transformative change.</div></div><div><h3>OBJECTIVE</h3><div>We assess the extent to which farmers have implemented transformative or incremental land use changes on their farms over the previous ten years and their likelihood to implement both types of changes in the future, with a particular emphasis on respondents' patience (i.e. low discount rates) and risk preferences, which we expect to have differing effects on change type.</div></div><div><h3>METHODS</h3><div>We utilize data from a large-scale, Internet-based survey of farmers, foresters, and growers from across New Zealand. Participants were recruited through industry bodies and government databases, and the final sample includes 4458 respondents representing all major activities in New Zealand's primary sector and all 65 districts in the country. The sample is broadly representative by both demographics and industry.</div></div><div><h3>RESULTS AND CONCLUSION</h3><div>We find that transformative land use changes are indeed rare - only 15 % of farmers had implemented transformative land use changes in the past, and only 11 % intended to implement them in the future. Furthermore, transformative land use changes are more common in some industries than others, with the arable sector having the highest levels of transformative change; in contrast, incremental change is common across all sectors. Surprisingly, individual patience was not generally associated with actual or intended adaptations, but risk tolerance was a strong predictor of change. Furthermore, risk-tolerant individuals who also expressed climate change belief were significantly more likely to have already implemented transformative change.</div></div><div><h3>SIGNIFICANCE</h3><div>Given that transformative changes involve high risk and are often costly, these results highlight the importance of societal investment to foster transformative changes where needed, as many individuals – especially marginalized or under resourced producers – will have minimal capacity for their implementation. This work identifies the industries and characteristics of producers that may need the greatest investment to implement transformative changes to respond to a host of rapidly changing agricultural conditions.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104195"},"PeriodicalIF":6.1,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated assessment of farm-level mitigation measures for gaseous emissions","authors":"Oyinlola Rafiat Ogunpaimo ,&nbsp;Cathal Buckley ,&nbsp;Stephen Hynes ,&nbsp;Stephen O'Neill","doi":"10.1016/j.agsy.2024.104188","DOIUrl":"10.1016/j.agsy.2024.104188","url":null,"abstract":"<div><h3>Context</h3><div>Some gaseous emissions continue to pose a serious threat to human health and the environment locally, regionally and globally. This has resulted in several studies advocating for the implementation of mitigation measures to reduce the emissions of harmful gases.</div></div><div><h3>Objective</h3><div>While the vast majority of studies focus on a single type of gas, much less attention has been paid to the complementary or conflicting effects of mitigation measures across multiple harmful gaseous emissions dimensions.</div></div><div><h3>Methods</h3><div>To address this research gap, this study uses Irish farm-level data to assess the holistic costs and benefits of a suite of mitigation measures that have the potential to abate greenhouse gases, ammonia or both. A cost-benefit analysis framework is employed to assess the impact of the mitigation measures across five different farm system types.</div></div><div><h3>Results and conclusions</h3><div>Results indicate that the relative effectiveness of the mitigation measure varies depending on the gaseous emission dimension being examined.</div></div><div><h3>Significance</h3><div>Analyses that fail to account for such synergistic and antagonistic relationship impacts may lead to flawed policy decisions.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104188"},"PeriodicalIF":6.1,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agroecological performance of smallholder dairy cattle systems in the Peruvian Amazon","authors":"D.M. Pizarro ,&nbsp;M.G. Erickson ,&nbsp;C.A. Gómez-Bravo ,&nbsp;V.D. Picasso ,&nbsp;D. Lucantoni ,&nbsp;A. Mottet ,&nbsp;M.A. Wattiaux","doi":"10.1016/j.agsy.2024.104199","DOIUrl":"10.1016/j.agsy.2024.104199","url":null,"abstract":"<div><h3>CONTEXT</h3><div>In Peru, silvopastoral systems have been included as a national measure to address deforestation and mitigate carbon emissions. Limited studies have assessed the sustainability of mixed livestock-crop systems using tools that address multiple Sustainable Development Goals (SDG).</div></div><div><h3>OBJECTIVE</h3><div>We assessed the sustainability of smallholder dairy farms in the Peruvian Amazon as affected by system type (silvopastoral or conventional) and herd size (medium or large) using the Tool for Agroecological Performance Evaluation (TAPE). Furthermore, we explored the linkages among TAPE indicators including the 10 Elements of Agroecology (EA), an overall evaluation scale (Characterization of Agroecological Transition; CAET), and 11 SDG-linked Core Criteria of Performance (CCP).</div></div><div><h3>METHODS</h3><div>Twenty-two farmers of the San Martin region were surveyed. Data were subjected to analysis of variance, Pearson correlations, and fitted to linear and quadratic functions.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Silvopastoral systems showed a greater agroecological transition than conventional systems (69.0 vs. 60.2; CAET mean) regardless of herd size.</div><div>Results suggested that EA and CCP were essentially independent of each other if linearity was assumed. However, concave quadratic relationships were detected between the CAET and 4 CCP: <em>Farm Income</em>, <em>Agricultural Net Income, Dietary Diversity,</em> and <em>Women's Empowerment</em>. For these CCP, depressed values for farms with intermediate CAET (60 to 69) suggested that they neither reap the full benefits of agroecological practices found mainly in silvopastoral farms (CAET &gt;70) nor the full benefits of conventional practices (CAET &lt;60)<em>.</em></div></div><div><h3>SIGNIFICANCE</h3><div>The implementation of agroecological practices in smallholder systems may support positive economic and social sustainability outcomes.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104199"},"PeriodicalIF":6.1,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review of food-waste based hydroponic fertilisers","authors":"Oscar Wang,&nbsp;Rosalind Deaker,&nbsp;Floris Van Ogtrop","doi":"10.1016/j.agsy.2024.104179","DOIUrl":"10.1016/j.agsy.2024.104179","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;CONTEXT&lt;/h3&gt;&lt;div&gt;This review article seeks to evaluate existing research in hydroponic systems which utilise a fertiliser solution derived from food-waste, also known as “Food-waste based hydroponic fertilisers” (FWBHF). FWBHF research is rooted in addressing increasing concerns surrounding food security, addressing both non-productive waste streams and sustainable production of hydroponic fertilisers. In 2018, the world was predicted to have wasted 931 million tonnes of food, 17 % of the total food produced throughout the year (&lt;em&gt;FAO, 2021&lt;/em&gt;). Meanwhile, existing hydroponic systems rely on synthetic fertilisers which are constituted from unsustainable processes, such as Haber-Bosch systems or mining for phosphate rocks. These practices contribute heavily to greenhouse gas emissions or rely on destructive exploitation of finite reserves, which researchers believe will increase in price as accessible reserves are exhausted (Liu et al., 2020&lt;em&gt;;&lt;/em&gt; Cordell et al., 2011). With increasing population in urban areas, the demand of produce imported from regional areas grows alongside the density of waste generation. Thus, exploring methods to re-utilise urban food-waste in urban horticultural systems may help in improving food security, reducing waste, and providing a local source of fresh produce for consumers.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVES&lt;/h3&gt;&lt;div&gt;The objectives of this review article are to : i) Utilise PRISMA protocol to collect and synthesize existing literature related to food-waste based hydroponic systems, ii) Identify major challenges found across literature which inhibit yield outcomes in food-waste based hydroponic systems, iii) Explore potential improvements using conventional or non-conventional methods, including chemical, physical, and biological modifications to existing systems, iv) Suggest a standardized reporting framework for future research in this area.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;Using the PRISMA protocol, 6840 papers were identified with key words: “Food-waste AND hydroponic AND fertiliser,” “Organic AND hydroponic AND fertiliser,” and “Organic AND Hydroponics.” 308 papers were selected based on the relevance of their title and abstract. After considering quality, overlaps, and relevance, 37 papers were chosen to be part of this systematic review. Literature was chosen based on its contents utilising any form of processing to prepare waste generated from the food-waste industry for use in a hydroponic system. These papers utilised waste generated at i) Farm, ii) Industry, and iii) Consumer, levels as well as a range of novel methods such as fermentation, steaming, or composting. This review studies how both feedstock composition and processing methodologies play a role in determining the efficacy of a food-waste based hydroponic fertiliser.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS AND DISCUSSION&lt;/h3&gt;&lt;div&gt;It was found that while feedstock plays a larger role in the final nutritional composition, categorisation by me","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104179"},"PeriodicalIF":6.1,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AquaCrop model to optimize water supply for a sustainable processing tomato cultivation in the Mediterranean area: A multi-objective approach","authors":"P. Garofalo ,&nbsp;M. Riccardi ,&nbsp;P. Di Tommasi ,&nbsp;A. Tedeschi ,&nbsp;M. Rinaldi ,&nbsp;F. De Lorenzi","doi":"10.1016/j.agsy.2024.104198","DOIUrl":"10.1016/j.agsy.2024.104198","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;CONTEXT&lt;/h3&gt;&lt;div&gt;Efficient irrigation management must consider multiple aspects of cropping systems, such as productivity, water use efficiency, and economic viability. Crop simulation models like AquaCrop are essential tools for analyzing crop responses under different irrigation scenarios. Organizing the model's outputs into standardized parameters allows for a multi-objective evaluation, which can be consolidated into a single index for optimizing irrigation strategies.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;This study aims to formalize the response of processing tomato cropping systems in Southern Italy to various irrigation regimes and develop a framework to identify optimal irrigation volumes for production, water use efficiency, and economic returns.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;AquaCrop was used to assess the effects of different seasonal water supplies on dry yield, water use efficiency, and irrigation water use efficiency. Sustainability was evaluated via the blue water footprint and drainage, while economic sustainability was measured through net income and irrigation economic efficiency. A multi-objective evaluation framework was built, developed to consolidate performance indices into a single multi-aggregated index (&lt;em&gt;I&lt;/em&gt;&lt;sub&gt;&lt;em&gt;mobj&lt;/em&gt;&lt;/sub&gt;&lt;em&gt;).&lt;/em&gt; The AquaCrop model was calibrated and validated using field data, with high accuracy in simulating canopy cover, biomass, and dry yield (&lt;em&gt;NRMSE&lt;/em&gt; &lt; 30 %, &lt;em&gt;r&lt;/em&gt; &gt; 0.90, and &lt;em&gt;d&lt;/em&gt; &gt; 0.97). Polynomial regression was used to model the relationships between irrigation volumes and cropping system variables. Each variable was assigned a truth value (&lt;em&gt;TW&lt;/em&gt;&lt;sub&gt;&lt;em&gt;i&lt;/em&gt;&lt;/sub&gt;), derived from regression coefficients, statistical significance, and model fit. These values were normalized using a sigmoid function and consolidated into the &lt;em&gt;I&lt;/em&gt;&lt;sub&gt;&lt;em&gt;mobj&lt;/em&gt;&lt;/sub&gt; index, providing an overall measure of irrigation performance.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS AND CONCLUSIONS&lt;/h3&gt;&lt;div&gt;AquaCrop accurately simulated canopy cover, biomass, and dry yield. Multi-objective analysis showed yield and profitability were most sensitive to irrigation changes, followed by drainage, blue water footprint, and water use efficiency. The 500 mm irrigation regime yielded the highest productivity and profitability but negatively impacted water use efficiency and environmental sustainability. Irrigation volumes above 500 mm worsened all water-related variables, while volumes of 400 mm reduced profitability but improved the sustainability. The &lt;em&gt;I&lt;/em&gt;&lt;sub&gt;&lt;em&gt;mobj&lt;/em&gt;&lt;/sub&gt; index identified that irrigation between 300 mm and 400 mm provided the best trade-off across all evaluated variables.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;SIGNIFICANCE&lt;/h3&gt;&lt;div&gt;This study highlights the value of integrating crop productivity, economic viability, and sustainability into irrigation management. The proposed framework, combined with AquaCrop, offers a holistic tool for optimizing irrigati","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"223 ","pages":"Article 104198"},"PeriodicalIF":6.1,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}