Pub Date : 2017-07-01DOI: 10.1017/S2040470017001145
A. Bernardi, G. M. Bettiol, Giulia Guillen Mazzuco, S. N. Esteves, P. P. Oliveira, J. Pezzopane
Material and Methods The 6-ha field experiment was carried out at Embrapa Cattle Southeast in São Carlos, SP, Brazil (21°57'S, 47°50'W, 860 m alt) during the growing season of 2013/2014. The ICLFS is planted with Eucalyptus urograndis (GG100) planted in single rows with 15m-distance and 2m between plants. Pasture is Urochloa brizantha cv. Piatã. Annually 1/3 of area is renewed with the corn sown together with the Piatã grass. Soil fertility parameters (P, K + , cation exchange capacity – CEC, basis saturation-V% and soil organic matter SOM) were evaluated at 1.5; 3.0; and 7.5m distance from the trees and 0-20 cm depth, before and after annual crop corn growth.
材料与方法在2013/2014年生长季，在巴西SP州 o Carlos的Embrapa牛东南(21°57'S, 47°50'W, 860 m高程)进行了6 ha的田间试验。ICLFS种植桉树(GG100)，单行种植，植株间距15米，植株之间2米。牧场是尿草草。Piata。每年有三分之一的土地更新，播种玉米和Piatã草。土壤肥力参数(P、K +、阳离子交换量- CEC、碱基饱和度- v %和土壤有机质SOM)在1.5时进行评价;3.0;与树木距离7.5m，深度0-20 cm，一年生作物玉米生长前后。
{"title":"Spatial variability of soil fertility in an integrated crop livestock forest system.","authors":"A. Bernardi, G. M. Bettiol, Giulia Guillen Mazzuco, S. N. Esteves, P. P. Oliveira, J. Pezzopane","doi":"10.1017/S2040470017001145","DOIUrl":"https://doi.org/10.1017/S2040470017001145","url":null,"abstract":"Material and Methods The 6-ha field experiment was carried out at Embrapa Cattle Southeast in São Carlos, SP, Brazil (21°57'S, 47°50'W, 860 m alt) during the growing season of 2013/2014. The ICLFS is planted with Eucalyptus urograndis (GG100) planted in single rows with 15m-distance and 2m between plants. Pasture is Urochloa brizantha cv. Piatã. Annually 1/3 of area is renewed with the corn sown together with the Piatã grass. Soil fertility parameters (P, K + , cation exchange capacity – CEC, basis saturation-V% and soil organic matter SOM) were evaluated at 1.5; 3.0; and 7.5m distance from the trees and 0-20 cm depth, before and after annual crop corn growth.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"13 1","pages":"590-593"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78785941","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}
Pub Date : 2017-07-01DOI: 10.1017/S2040470017000139
I. Campos, L. González, J. Villodre, María Calera, Jaime Campoy, Nuria Jiménez, C. Plaza, A. Calera
Biomass production is a diagnosis tool for the evaluation of the effect of climate, crop genomic and management. The differences in biomass accumulation are necessary for the assessment of the fertilization necessities in the strategies for variable nitrogen doses. Remote sensing-based data provide a direct observation of the differences in canopy development across time and space and can be integrated into the physiological basis of crop growth models to provide estimates of biomass production at fine scales. The proposed approach was applied in a wheat field in Albacete, Spain and the results were compared with measurements of aboveground biomass and yield maps obtained by a combined-mounted grain yield monitor.
{"title":"Mapping within-field biomass variability: a remote sensing-based approach","authors":"I. Campos, L. González, J. Villodre, María Calera, Jaime Campoy, Nuria Jiménez, C. Plaza, A. Calera","doi":"10.1017/S2040470017000139","DOIUrl":"https://doi.org/10.1017/S2040470017000139","url":null,"abstract":"Biomass production is a diagnosis tool for the evaluation of the effect of climate, crop genomic and management. The differences in biomass accumulation are necessary for the assessment of the fertilization necessities in the strategies for variable nitrogen doses. Remote sensing-based data provide a direct observation of the differences in canopy development across time and space and can be integrated into the physiological basis of crop growth models to provide estimates of biomass production at fine scales. The proposed approach was applied in a wheat field in Albacete, Spain and the results were compared with measurements of aboveground biomass and yield maps obtained by a combined-mounted grain yield monitor.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"18 1","pages":"764-769"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85092733","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}
Pub Date : 2017-07-01DOI: 10.1017/S2040470017001133
A. Colaço, R. Trevisan, J. Molin, J. R. Rosell-Polo, A. Escolà
LiDAR (Light detection and ranging) technology is an alternative to current manual methods of canopy geometry estimations in orange trees. The objective of this work was to compare different types of canopy volume estimations of orange trees, some inspired on manual methods and others based on a LiDAR sensor. A point cloud was generated for 25 individual trees using a laser scanning system. The convex-hull and the alpha-shape surface reconstruction algorithms were tested. LiDAR derived models are able to represent orange trees more accurately than traditional methods. However, results differ significantly from the current manual method. In addition, different 3D modeling algorithms resulted in different canopy volume estimations. Therefore, a new standard method should be developed and established.
{"title":"Orange tree canopy volume estimation by manual and LiDAR-based methods","authors":"A. Colaço, R. Trevisan, J. Molin, J. R. Rosell-Polo, A. Escolà","doi":"10.1017/S2040470017001133","DOIUrl":"https://doi.org/10.1017/S2040470017001133","url":null,"abstract":"LiDAR (Light detection and ranging) technology is an alternative to current manual methods of canopy geometry estimations in orange trees. The objective of this work was to compare different types of canopy volume estimations of orange trees, some inspired on manual methods and others based on a LiDAR sensor. A point cloud was generated for 25 individual trees using a laser scanning system. The convex-hull and the alpha-shape surface reconstruction algorithms were tested. LiDAR derived models are able to represent orange trees more accurately than traditional methods. However, results differ significantly from the current manual method. In addition, different 3D modeling algorithms resulted in different canopy volume estimations. Therefore, a new standard method should be developed and established.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"9 1","pages":"477-480"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72760180","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}
Pub Date : 2017-07-01DOI: 10.1017/S2040470017001108
M. Zhang, R. R. Zhang, G. Xu, L. P. Chen
{"title":"Design and development of a navigation system for agricultural aerial spraying","authors":"M. Zhang, R. R. Zhang, G. Xu, L. P. Chen","doi":"10.1017/S2040470017001108","DOIUrl":"https://doi.org/10.1017/S2040470017001108","url":null,"abstract":"","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"734 1","pages":"870-875"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76798767","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}
Pub Date : 2017-07-01DOI: 10.1017/S2040470017001236
B. Harel, P. Kurtser, Y. Parmet, Y. Edan
{"title":"Sweet pepper maturity evaluation","authors":"B. Harel, P. Kurtser, Y. Parmet, Y. Edan","doi":"10.1017/S2040470017001236","DOIUrl":"https://doi.org/10.1017/S2040470017001236","url":null,"abstract":"","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"43 1","pages":"167-171"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82257664","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}
Pub Date : 2017-07-01DOI: 10.1017/S2040470017000644
Yuval Shahar, C. Blacker, R. Kavanagh, P. James, J. Taylor
{"title":"Implementation of Ag Data Agricultural Services for Precision Agriculture","authors":"Yuval Shahar, C. Blacker, R. Kavanagh, P. James, J. Taylor","doi":"10.1017/S2040470017000644","DOIUrl":"https://doi.org/10.1017/S2040470017000644","url":null,"abstract":"","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"577 1","pages":"656-661"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85701940","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}
Pub Date : 2017-07-01DOI: 10.1017/S2040470017000863
P. Berry, H. Holmes, C. Blacker
A ‘chessboard’ field experiment set up to investigate how the yield response to nitrogen (N) fertiliser varied spatially within a field in the UK indicated that the optimum N rate varied substantially by up to 100 kg N/ha within the three hectare experimental area. Variation in N optima was negatively related to the soil N supply. However, soil N supply, yield potential and apparent fertiliser recovery rate were inter-related which meant that the influence of each element on N optima was complex. Spectral reflectance indices related well to crop N uptake and could be used to help estimate soil N supply.
在英国进行的一项“棋盘”田间试验旨在研究氮肥对产量的空间变化反应，结果表明，在3公顷的试验区内，最佳施氮量的变化幅度高达100 kg N/ha。最佳氮素变化与土壤氮素供给呈负相关。然而，土壤氮供应、产量潜力和肥料表观回收率是相互关联的，这意味着各元素对氮素优化的影响是复杂的。光谱反射指数与作物氮素吸收密切相关，可用于估算土壤氮素供应。
{"title":"Development of methods for remotely sensing grass growth to enable precision application of nitrogen fertilizer","authors":"P. Berry, H. Holmes, C. Blacker","doi":"10.1017/S2040470017000863","DOIUrl":"https://doi.org/10.1017/S2040470017000863","url":null,"abstract":"A ‘chessboard’ field experiment set up to investigate how the yield response to nitrogen (N) fertiliser varied spatially within a field in the UK indicated that the optimum N rate varied substantially by up to 100 kg N/ha within the three hectare experimental area. Variation in N optima was negatively related to the soil N supply. However, soil N supply, yield potential and apparent fertiliser recovery rate were inter-related which meant that the influence of each element on N optima was complex. Spectral reflectance indices related well to crop N uptake and could be used to help estimate soil N supply.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"76 1","pages":"758-763"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90987238","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}
Pub Date : 2017-07-01DOI: 10.1017/S2040470017000310
B. Benet, R. Lenain, V. Rousseau
A sensor fusion method was developed in order to track crop rows, considering various vegetation levels, for various crops. This application consisted to use a laser sensor, an inertial measurement unit and a color camera, in a fusion mode, to get a set of points corresponding to crop rows and eliminate noise like grass or leaves in environment, in real time. After applying a method such as Hough or Least Square (LS) technique for obtaining the geometric data of the crop line, automatic control operations were applied to realize the crop row tracking operation, with the desired lateral deviation parameter, taking into account the robot angular deviation and the temporal aspect, to realize the task with accuracy and without oscillations. The results showed the robustness of fusion method, to get a stable autonomous navigation for crop row tracking, particularly in the vineyards, with many perturbations such as bumps, hole and mud, and speeds between 1 and 2 m s⁻¹. The mean lateral error between desired and obtained trajectory varied between 0.10 and 0.40 m, depending of speed and perturbations.
为了在考虑不同植被水平的情况下，对不同作物进行行跟踪，提出了一种传感器融合方法。该应用程序包括使用激光传感器、惯性测量单元和彩色摄像机，在融合模式下，获得一组与作物行对应的点，并实时消除环境中的草或树叶等噪声。在采用霍夫或最小二乘(LS)等方法获取作物行几何数据后，采用自动控制操作实现作物行跟踪操作，在考虑机器人角度偏差和时间方面的情况下，以期望的横向偏差参数实现作物行跟踪操作，以实现精确无振荡的任务。结果表明，融合方法的鲁棒性，可以获得稳定的自主导航，用于作物行跟踪，特别是在葡萄园中，有许多扰动，如颠簸，洞和泥，速度在1到2 m s⁻¹之间。期望和获得的轨迹之间的平均横向误差在0.10和0.40 m之间变化，取决于速度和扰动。
{"title":"Development of a sensor fusion method for crop row tracking operations","authors":"B. Benet, R. Lenain, V. Rousseau","doi":"10.1017/S2040470017000310","DOIUrl":"https://doi.org/10.1017/S2040470017000310","url":null,"abstract":"A sensor fusion method was developed in order to track crop rows, considering various vegetation levels, for various crops. This application consisted to use a laser sensor, an inertial measurement unit and a color camera, in a fusion mode, to get a set of points corresponding to crop rows and eliminate noise like grass or leaves in environment, in real time. After applying a method such as Hough or Least Square (LS) technique for obtaining the geometric data of the crop line, automatic control operations were applied to realize the crop row tracking operation, with the desired lateral deviation parameter, taking into account the robot angular deviation and the temporal aspect, to realize the task with accuracy and without oscillations. The results showed the robustness of fusion method, to get a stable autonomous navigation for crop row tracking, particularly in the vineyards, with many perturbations such as bumps, hole and mud, and speeds between 1 and 2 m s⁻¹. The mean lateral error between desired and obtained trajectory varied between 0.10 and 0.40 m, depending of speed and perturbations.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"69 1","pages":"583-589"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88123288","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}
Pub Date : 2017-07-01DOI: 10.1017/S2040470017001005
B. Martin, C. Dillon, T. Mark, T. Davis
A whole farm economic analysis was performed to maximize net returns utilizing variable maturity groups of corn and soybeans over different soil types. Demand for drying and storage equipment throughout harvest was generated based on profit-maximizing combinations of grain types, their respective maturity groups, and yield potential over different topsoil depths. Two marketing strategies were considered: cash and futures contract sales. It was found that drying equipment became a limiting factor in the proposed system. This prevented storage facilities from reaching full capacity and additional grain from capturing value in the futures market.
{"title":"A Whole Farm Analysis of the Implications of Variable Maturity Groups on Harvest Logistics and Net Returns","authors":"B. Martin, C. Dillon, T. Mark, T. Davis","doi":"10.1017/S2040470017001005","DOIUrl":"https://doi.org/10.1017/S2040470017001005","url":null,"abstract":"A whole farm economic analysis was performed to maximize net returns utilizing variable maturity groups of corn and soybeans over different soil types. Demand for drying and storage equipment throughout harvest was generated based on profit-maximizing combinations of grain types, their respective maturity groups, and yield potential over different topsoil depths. Two marketing strategies were considered: cash and futures contract sales. It was found that drying equipment became a limiting factor in the proposed system. This prevented storage facilities from reaching full capacity and additional grain from capturing value in the futures market.","PeriodicalId":7228,"journal":{"name":"Advances in Animal Biosciences","volume":"22 1","pages":"668-671"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81419541","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}
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