scholarly journals Applying a digital method for measuring leaf area index of tomato plants

2019 ◽  
Author(s):  
Mostafa Mahmoud Mohamed Abdelkader ◽  
Mikhail Puchkov ◽  
Elena Loktionova
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Digital Method ◽  
Area Index ◽  
Tomato Plants

scholarly journals DESENVOLVIMENTO DO TOMATEIRO INDUSTRIAL EM RESPOSTA A DIFERENTES NÍVEIS DE IRRIGAÇÃO

Irriga ◽  
2020 ◽  
Vol 25 (3) ◽  
pp. 432-448
Author(s):  
Cícero José da Silva ◽  
José Antônio Frizzone ◽  
César Antônio da Silva ◽  
Nadson de Carvalho Pontes ◽  
Luiz Felipe Mariano da Silva ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Development ◽  
Tomato Plant ◽  
Dry Mass ◽  
Area Index ◽  
Tomato Plants ◽  
Subsurface Drip ◽  
Irrigation Levels ◽  
E Mail

DESENVOLVIMENTO DO TOMATEIRO INDUSTRIAL EM RESPOSTA A DIFERENTES NÍVEIS DE IRRIGAÇÃO     Cícero José da Silva1; José Antônio Frizzone2; César Antônio da Silva3; Nadson de Carvalho Pontes4; Luiz Felipe Mariano da Silva5 E Ênio Eduardo Basílio6   1Professor do Curso Bacharelado em Agronomia, Instituto Federal Goiano – Campus Morrinhos – GO, BR 153, Km 633, Zonal Rural, CEP;75650-000, Morrinhos – GO, Brasil. E-mail: [email protected] 2Professor Aposentado Colaborador Senior, Departamento de Engenharia de Biossitemas, Escola Superior de Agricultura “Luiz de Queiroz” – Universidade de São Paulo, Avenida Pádua Dias, N 11, Caixa Postal 9, CEP: 13418-900, Piracicaba – SP, Brasil. E-mail: [email protected] 3Professor do Curso Bacharelado em Agronomia, Instituto Federal Goiano – Campus Morrinhos – GO, BR 153, Km 633, Zonal Rural, CEP;75650-000, Morrinhos – GO, Brasil. E-mail: [email protected] 4Professor do Curso Bacharelado em Agronomia, Instituto Federal Goiano – Campus Morrinhos – GO, BR 153, Km 633, Zonal Rural, CEP;75650-000, Morrinhos – GO, Brasil. E-mail: [email protected] 5Estudante de Iniciação Científica do Curso Bacharelado em Agronomia, Instituto Federal Goiano – Campus Morrinhos – GO, BR 153, Km 633, Zonal Rural, CEP;75650-000, Morrinhos – GO, Brasil. E-mail: [email protected] 6Técnico Administrativo, Mestre em Olericultura, Instituto Federal Goiano – Campus Morrinhos – GO, BR 153, Km 633, Zonal Rural, CEP;75650-000, Morrinhos – GO, Brasil. E-mail: [email protected]     1 RESUMO   O objetivo desta pesquisa foi avaliar o desenvolvimento de plantas de tomateiros submetidas a diferentes níveis de reposição da irrigação, aplicados via sistema gotejamento subsuperficial durante duas safras. O experimento foi conduzido no delineamento em blocos ao acaso, com quatro repetições. Foram avaliados cinco níveis de irrigação: 50, 75, 100, 125 e 150% da evapotranspiração da cultura (%ETc) medida com lisímetros de pesagem, sobre o desenvolvimento de plantas de tomateiro. Cada parcela experimental foi composta por três fileiras de plantas de 5,5 m de comprimento, espaçadas a 1,10 m entre si e 0,30 m entre plantas. As avaliações de área foliar, índice de área foliar, massa seca de raiz, caule, folhas, flores, frutos e total foram realizadas aos 45, 65 e 85 dias após o transplante das mudas. Irrigações deficitárias e em excesso prejudicaram o desenvolvimento vegetativo das plantas de tomateiro. Os maiores valores de área foliar, índice de área foliar e massa seca total das plantas de tomateiro foram estimados com níveis de irrigação que variaram de 96 a 112% da ETc, variando de acordo com o ano de avaliação e a fase de desenvolvimento do tomateiro. Irrigações deficitárias e excessivas prejudicaram a floração e frutificação do tomateiro híbrido BRS Sena.             Palavras-chave: Solanum lycopersicom L.; gotejamento enterrado; manejo da irrigação; massa seca.             Silva, c. j. da; FRIZZONE, J. A.; SILVA, C. A. da; pontes, n. de C.; SILVA, L. F. M. da; BASÍLIO, Ê. E. Industrial tomato plant development in response to different irrigation levels    2 ABSTRACT   This research aimed to evaluate tomato plant development submitted to different irrigation replacement levels, irrigated via subsurface drip system for two harvests. The experiment was conducted under a randomized complete block design with four replications. Five irrigation levels were evaluated: 50, 75, 100, 125 and 150% of crop evapotranspiration (% ETc) measured with weighing lysimeters over the tomato plants development. Each experimental plot was composed of three plants rows with 5.5 m long, spaced 1.10 m apart and 0.30 m between plants. Leaf area, leaf area index, root dry matter, stem, leaves, flowers, fruits and total were evaluated at 45, 65 and 85 days after seedlings transplanting. Deficit and excess irrigation impaired the vegetative development of tomato plants. The highest values of leaf area, leaf area index and plants total dry mass were estimated with irrigation levels ranging from 96 to 112% of ETc, depending on the evaluation harvest year and the crop development phase. Deficit and excessive irrigation affected the flowering and fruiting of the hybrid tomato BRS Sena.   Keywords: Solanum lycopersicom L; subsurface drip irrigation; irrigation manegement; dry mass.

Assessment of an automated digital method to estimate leaf area index (LAI) in cherry trees

2016 ◽  
Vol 44 (4) ◽  
pp. 247-261 ◽  
Author(s):  
Marcos Carrasco-Benavides ◽  
Marco Mora ◽  
Gonzalo Maldonado ◽  
Jeissy Olguín-Cáceres ◽  
Eduardo von Bennewitz ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Digital Method ◽  
Area Index ◽  
Cherry Trees

scholarly journals A new method for estimating the leaf area index of cucumber and tomato plants

2003 ◽  
Vol 21 (4) ◽  
pp. 666-669 ◽  
Author(s):  
Flávio Favaro Blanco ◽  
Marcos Vinícius Folegatti
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Area Measurement ◽  
Quadratic Model ◽  
Regression Equations ◽  
Area Index ◽  
Tomato Plants ◽  
Potted Plants ◽  
Growing Period ◽  
Area Distribution

Non-destructive methods of leaf area measurement are useful for small plant populations, such as experiments with potted plants, and allow the measurement of the same plant several times during the growing period. A methodology was developed to estimate the leaf area index (LAI) of cucumber and tomato plants through the evaluation of the leaf area distribution pattern (LADP) of the plants and the relative height of the leaves in the plants. Plant and leaf height, as well as the length and width of all leaves were measured and the area of some leaves was determined by a digital area meter. The obtained regression equations were used to estimate the leaf area for all relative heights along the plant. The LADP adjusted to a quadratic model for both crops and LAI were estimated by measuring the length and width of the leaves located at the relative heights representing the mean leaf area of the plants. The LAI estimations presented high precision and accuracy when the proposed methodology was used resulting in time and effort savings and being useful for both crops.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

Hyperspectral characteristics and leaf area index monitoring of rice (Oryza sativa L.) under carbon dioxide concentration enrichment

2021 ◽  
Vol 54 (3) ◽  
pp. 231-243
Author(s):  
Chao Liu ◽  
Zhenghua Hu ◽  
Rui Kong ◽  
Lingfei Yu ◽  
Yuanyuan Wang ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Oryza Sativa ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Oryza Sativa L ◽  
Carbon Dioxide Concentration ◽  
Area Index
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