coffee yield
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2021 ◽  
Vol 13 (24) ◽  
pp. 13823
Author(s):  
Lenka Ehrenbergerová ◽  
Marie Klimková ◽  
Yessika Garcia Cano ◽  
Hana Habrová ◽  
Samuel Lvončík ◽  
...  

Shade is a natural condition for coffee plants; however, unshaded plantations currently predominate in Asia. The benefits of shading increase as the environment becomes less favorable for coffee cultivation, e.g., because of climate change. It is necessary to determine the effects of shade on the yield of Coffea canephora and on the soil water availability. Therefore, three coffee plantations (of 3, 6, and 9 ha) in the province of Mondulkiri, Cambodia, were selected to evaluate the effect of shade on Coffea canephora yields, coffee bush trunk changes, and soil moisture. Our study shows that shade-grown coffee delivers the same yields as coffee that is grown without shading in terms of coffee bean weight or size (comparing average values and bean variability), the total weight of coffee fruits per coffee shrub and the total weight of 100 fruits (fresh and dry). Additionally, fruit ripeness was not influenced by shade in terms of variability nor in terms of a possible delay in ripening. There was no difference in the coffee stem diameter changes between shaded and sunny sites, although the soil moisture was shown to be higher throughout the shaded sites.


2021 ◽  
Author(s):  
Natacha Motisi ◽  
Julien Papaïx ◽  
Sylvain Poggi

Coffee berry disease (CBD) can cause significant coffee yield losses along with major income losses for African smallholders. Although these farmers cannot afford to purchase pesticides to control the disease, agroecological solutions have rarely been investigated, and how epidemiological mechanisms are linked to the environment of the coffee tree and the plot remains unclear. Agroforestry systems are a promising agroecological option, but the effect of shade on CBD regulation is the subject of debate, and the use of plant species diversity remains uncertain. Here, we address how shade affects epidemiological mechanisms by modifying the microclimate. For this purpose, we developed a mechanistic susceptible-exposed-infectious-removed (SEIR) model, and used a Bayesian framework to infer the epidemiological parameters against microclimatic covariates. We show that shade has opposing effects on different epidemiological mechanisms. Specifically, shade can limit disease dynamics by reducing disease transmission while simultaneously promoting disease dynamics by reducing the latent period of the pathogen. However, in full sun, efficient disease transmission compensates for long latent periods. As a result, the balances between microclimatic variables can counterbalance the epidemiological rates, which can dramatically alter the fate of epidemics in shade versus full sun conditions. We propose research avenues to help design cost- and environmentally effective management strategies for CBD that are notably based on the functional traits of shade trees that could hamper CBD dispersal.


2021 ◽  
Vol 1 ◽  
pp. 100010
Author(s):  
Brenon Diennevan Souza Barbosa ◽  
Gabriel Araújo e Silva Ferraz ◽  
Lucas Costa ◽  
Yiannis Ampatzidis ◽  
Vinay Vijayakumar ◽  
...  

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 309-316
Author(s):  
M. JAYAKUMAR ◽  
M. RAJAVEL

Climate plays important role in production of coffee. Adequate quantum and timely receipt of blossom rainfall for flowering and subsequent backing showers influence the berry set and yield of coffee. Harvesting of Arabica coffee in Kerala State with humid tropical climate in India is done by December-January and harvesting of Robusta coffee is taken up during January-February. In this paper, attempt was made to develop agrometeorological models to forecast the yield of these two varieties coffee by utilising monthly climate variables from January to December. Long term data from 1991-92 to 2012-13 on coffee yield and weather data from 1991-2012 recorded at Regional Coffee Research Station, Chundale located in Wayanad district of Kerala State was used to develop agrometeorological model. Statistical regression model between climate indices and yield of Arabica and Robusta coffee was developed and the model was validated using crop and climate data for 2013 and 2014. The model demonstrated that climate indices based agrometeological model is able to forecast the yield of coffee in Kerala.  


2021 ◽  
Vol 24 ◽  
pp. 100613
Author(s):  
Pedro Arthur de Azevedo Silva ◽  
Marcelo de Carvalho Alves ◽  
Fábio Moreira da Silva ◽  
Vanessa Castro Figueiredo

2021 ◽  
Vol 22 (11) ◽  
Author(s):  
Intan Widya Pangestika ◽  
Ari Susilowati ◽  
Edi Purwanto

Abstract. Authors. 2021. Genetic diversity of Coffea canephora Pierre ex A. Froehner in Temanggung District, Indonesia based on molecular marker RAPD. Biodiversitas 22: 4775-4783. Temanggung District in Central Java Province, Indonesia is one of robusta coffee production centers. The condition of coffee plantations in Temanggung shows variations in some morphological traits. Variations in coffee phenotypes are considered less profitable for farmers because they produce yields of undesirable quality in the global market. This study aimed to evaluate the genetic diversity of robusta coffee in Temanggung. The coffee plants were derived from six villages located at two levels of altitude. The morphological traits were observed from canopy width, trunk diameter, plant height, cherry volume, and bean volume, while the biochemical compositions were determined by caffeine content and brew’s pH value. The molecular assays were performed using PCR-RAPD with ten primers and species identification was based on the ITS rDNA. Our finding showed a variation in all morphological characters and biochemical compositions based on the LSD test 5%. The molecular marker RAPD revealed the genetic diversity by showing the DNA polymorphism levels of 95%, with the genetic similarity coefficient ranged from 0.35 to 0.86. The species identification also demonstrated that our robusta coffee was 97.11-99.70% similar to robusta coffee MK615737.1 from Philippines and robusta coffee DQ153593.1 from Cameroon. Thus, genetic diversity on six populations of robusta coffee was found, along with its variations on phenotypes which might lead the coffee yield quality to become uneven.


2021 ◽  
Author(s):  
Murugan Muthusamy ◽  
M Alagupalamuthirsolai ◽  
K Ashokkumar ◽  
A Anandhi ◽  
R Ravi ◽  
...  

Abstract In this study, we investigated climatic parameters as well as predicted future change in precipitation and atmospheric temperature levels based on RCP4.5/8.5 scenarios in all cardamom-coffee hot spots of southern India. Our results showed that larger precipitation levels and pattern occurred in Cardamom hills (Kerala) followed by lower Puleny hills in Tamil Nadu. The least variation in precipitation levels has noticed for temperate upper Puleny hills and Kodagu hills in Karnataka. RCP4.5/8.5 scenario analysis showed greater variability in precipitation up to 180% increase and 90% decrease for all hot sports. The scenario analysis also predicted extreme variation in temperature levels ranging from 0.5–8.5ºC increase for the entire study region. A significant change in the coffee yield and quality has been recorded over the last 30 years. Increased yield trends in coffee were noticed for Cardamom hills (CH) and Kodagu hills, but significantly lower coffee production was observed for lower Pulney hills. The mixed response of yield variability in coffee has been primarily attributed to the ongoing changing climatic factors. Ecophysiological studies of coffee, cardamom and black pepper have proved that coffee would adapt well to a future challenging climatic condition, closely followed by cardamom and black pepper. Since all the coffee-cardamom hot spots in southern India undergoes considerable change in precipitation levels and pattern, necessary precautions, including water and irrigation management strategies, must be given utmost priority to increase the crop yield sustainability of these delicate cardamom-coffee hot spots in India.


Author(s):  
Diego Pons ◽  
Ángel G. Muñoz ◽  
Ligia M. Meléndez ◽  
Mario Chocooj ◽  
Rosario Gómez ◽  
...  

AbstractThe provision of climate services has the potential to generate adaptive capacity and help coffee farmers become or remain profitable by integrating climate information in a risk-management framework. Yet, in order to achieve this goal, it is necessary to identify the local demand for climate information, the relationships between coffee yield and climate variables, farmers’ perceptions, and to examine the potential actions that can be realistically put in place by farmers at the local level. In this study, we assessed the climate information demands from coffee farmers and their perception on the climate impacts to coffee yield in the Samalá watershed in Guatemala. After co-identifying the related candidate climate predictors, we propose an objective, flexible forecast system for coffee yield based on precipitation. The system, known as NextGen, analyzes multiple historical climate drivers to identify candidate predictors, and provides both deterministic and probabilistic forecasts for the target season. To illustrate the approach, a NextGen implementation is conducted in the Samalá watershed in southwestern Guatemala. The results suggest that accumulated June-July-August precipitation provides the highest predictive skill associated with coffee yield for this region. In addition to a formal cross-validated skill assessment, retrospective forecasts for the period 1989-2009 were compared to agriculturalists’ perception on the climate impacts to coffee yield at the farm level. We conclude with examples of how demand-based climate service provision in this location can inform adaptation strategies like optimum shade, pest control, and fertilization schemes months in advance. These potential adaptation strategies were validated by local agricultural technicians at the study site.


2021 ◽  
Author(s):  
Renan J. Parecido ◽  
Rogério P. Soratto ◽  
Marcos J. Perdoná ◽  
Fernando V. C. Guidorizzi ◽  
Guilherme G. Gomes ◽  
...  
Keyword(s):  

Author(s):  
João Antonio Lorençone ◽  
Lucas Eduardo de Oliveira APARECIDO ◽  
Pedro Antonio LORENÇONE ◽  
José Reinaldo Da Silva Cabral de MORAES

Objetivou-se prever da produtividade do café com modelos regressivos usando dados meteorológicos em diferentes tipos de solo. O trabalho foi realizado em 15 localidades produtoras de C.arabica do Paraná. Os dados climáticos foram coletados por meio da plataforma NASA/POWER de 1989 e 2020 e os dados de produtividade do Coffea Arabica (sacas/ha) foram obtidos pela CONAB de 2003 a 2018. Para o calcula da evapotranspiração de referência (ETo) foi utilizado o método de Penman e Monteith, e o balanço hídrico climatológico (BH) de Thornthwaite e Mather (1955). Na modelagem dos dados, foi utilizado a regressão linear múltipla, em que a produtividade do C.arabica foi a variável dependente e as variáveis independentes foram temperatura do ar, precipitação, radiação solar, déficit hídrico, excedente hídrico e armazenamento de água no solo. Modelos de regressão linear múltipla são capazes de prever a produtividade do cafeeiro arábica no estado do Paraná com dois a três meses de antecedência a colheita. O elemento meteorológico que mais influencia o cafeeiro é a temperatura máxima do ar, principalmente durante a formação do fruto (março). Temperaturas máximas do ar em março de 31.01°C reduzem a produção do cafeeiro. Os modelos podem ser usados para previsão da produtividade do cafeeiro arábica auxiliando no planejamento dos cafeicultores da região do norte do Paraná.


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