scholarly journals Performance of Three Sorghum Cultivars under Excessive Rainfall and Waterlogged Conditions in the Sudano-Sahelian Zone of West Africa: A Case Study at the Climate-Smart Village of Cinzana in Mali

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2655
Author(s):  
Manuel Müller ◽  
Siaka Dembélé ◽  
Robert Zougmoré ◽  
Thomas Gaiser ◽  
Samuel Partey
Keyword(s):  
Above Ground Biomass ◽  
Ground Biomass ◽  
Local Cultivar ◽  
Stress Symptoms ◽  
Recent Climate ◽  
Biomass Yields ◽  
Precipitation Variation ◽  
Seasonal Droughts ◽  
Hybrid Cultivar ◽  
Increasing Precipitation

Recent climate analyses show trends for increasing precipitation variability with increasing precipitation sums in Mali. The increasing occurrence of temporary intra-seasonal droughts and waterlogging longer than a week demands climate-smart solutions. Research has focused on water deficits since the 1980s. However, besides droughts, waterlogging can restrict productivity of sensitive cash and staple crops as cotton and corn. The year 2019 offered the historically unique opportunity to monitor waterlogging effects with 1088 mm precipitation in the rural commune Cinzanawith an isohyet of 681 mm. Impacts of two extreme downpours on three sorghum cultivars were monitored in a farmers-field experiment with three replications. All sorghum cultivars performed well in 2019 with significantly higher grain and above ground biomass yields than in the reference year 2007, with well distributed rainfall in Cinzana. “Jakumbè” (CSM63E) produced significantly higher grain yields than the hybrid cultivar “PR3009B” bred for high harvest index. The local cultivar “Gnofing” selected by local farmers produced significantly higher above ground biomass. All cultivars tolerated without severe stress symptoms 20 days waterlogging and 72 h inundation. Further waterlogging resilience research of other crops and other sorghum cultivars is needed to strengthen food security in Mali with expected increasing precipitation variation in the future.

scholarly journals Above-Ground Biomass Yields at Different Densities of Honey Mesquite

1997 ◽  
Vol 50 (5) ◽  
pp. 550 ◽  
Author(s):  
John D. Laxson ◽  
Walter H. Schacht ◽  
M. Keith Owens
Keyword(s):  
Above Ground Biomass ◽  
Ground Biomass ◽  
Biomass Yields ◽  
Honey Mesquite

scholarly journals Influence of rhizome mass on the crop establishment and dry matter yield of Miscanthus×giganteus over ten seasons

2019 ◽  
Vol 64 (1) ◽  
pp. 21-35
Author(s):  
Zeljko Dzeletovic ◽  
Gordana Andrejic ◽  
Aleksandar Simic ◽  
Hakan Geren
Keyword(s):  
Biomass Yield ◽  
Planting Density ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Miscanthus Giganteus ◽  
Medium Mass ◽  
Biomass Yields ◽  
Low Mass ◽  
Number Of Stems ◽  
High Yields

The aim of the present investigation was to assess the influence of rhizome mass on the success of plantation establishment and biomass yield of the bioenergy crop M. ? giganteus during 10 years of cultivation. The experiment included three treatments with different rhizome masses: 10-20 g (very low); 25- 35 g (low), and 40-60 g (medium mass). Planting density was 2 rhizomes m-2. The plants were harvested by mowing of the whole above-ground biomass each year in February. Out of the total number of planted rhizomes, the lowest emergence was noticed in very low mass rhizomes. In the first season, the greatest number of stems and crop height were encountered under the treatment with the highest rhizome mass. In the second season, crop heights were almost equal in all treatments. During the first two seasons, the highest biomass yields were recorded under the treatments with the highest rhizome masses. Although the analyzed parameters were highest with the rhizomes of 40-60g during the crop establishing stage, starting from the third season of cultivation, high yields of above-ground biomass may be obtained also with lower mass rhizomes. Having the highest biomass yield (25.85?7.36 Mg DM ha-1), the crop established with rhizomes of 25-35 g clearly stood out.

scholarly journals Influences of nitrogen fertilization and climate regime on the above-ground biomass yields of miscanthus and switchgrass: A meta-analysis

2019 ◽  
Vol 108 ◽  
pp. 303-311 ◽  
Author(s):  
Huaihai Chen ◽  
Zhongmin Dai ◽  
Henriette I. Jager ◽  
Stan D. Wullschleger ◽  
Jianming Xu ◽  
...  
Keyword(s):  
Nitrogen Fertilization ◽  
Meta Analysis ◽  
Above Ground Biomass ◽  
Climate Regime ◽  
Ground Biomass ◽  
Biomass Yields

scholarly journals The Effects of Potassium Fertilization and Irrigation on the Yield and Health Status of Jerusalem Artichoke (Helianthus tuberosus L.)

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 234 ◽  
Author(s):  
Bożena Bogucka ◽  
Agnieszka Pszczółkowska ◽  
Adam Okorski ◽  
Krzysztof Jankowski
Keyword(s):  
Health Status ◽  
Dry Matter ◽  
Jerusalem Artichoke ◽  
Helianthus Tuberosus ◽  
Dry Matter Yield ◽  
Above Ground Biomass ◽  
Potassium Fertilizer ◽  
Ground Biomass ◽  
Biomass Yields ◽  
Fusarium Fungi

The objective of this study was to determine the effects of potassium fertilization (applied to soil at 150, 250, and 350 kg K2O ha−1) and irrigation on the yield (fresh matter yield and dry matter yield of above-ground biomass and tubers) and the health status of tubers and leaves of three Jerusalem artichoke—JA (Helianthus tuberosus L.) cultivars (Topstar, Violette de Rennes, Waldspindel). The Topstar cultivar was characterized by the highest total tuber yield (60.53 Mg FM ha−1) and the highest above-ground biomass yield (65.74 Mg FM ha−1). An increase in the rate of potassium fertilizer to 350 kg K2O ha−1 did not affect total tuber yields. The greatest increase in above-ground biomass yields was observed in response to the potassium fertilizer rate of 150 kg K2O ha −1 (64.40 Mg FM ha−1). Irrigation increased tuber yields by 59% and above-ground biomass yields by 42% on average. Phytopathological analyses revealed that JA leaves were most frequently colonized by fungi of the genera Alternaria, Fusarium, and Epicoccum. Alternaria and Fusarium fungi were more prevalent in non-irrigated than in irrigated plots. A higher number of fungal pathogens was isolated from the leaves of cv. Violette de Rennes grown in a non-irrigated plot fertilized with 250 kg K2O ha−1. Tubers were most heavily colonized by fungi of the genera Penicillium, Fusarium, Alternaria, Botrytis, and Rhizopus. Fungal species of the genus Fusarium were isolated from tubers in all irrigated treatments, and they were less frequently identified in non-irrigated plots. Only the tubers of cv. Topstar grown in non-irrigated plots and supplied with 150 kg K2O ha−1 were free of Fusarium fungi. The number of cultures of pathogenic species isolated from Jerusalem artichoke tubers had a minor negative impact on fresh and dry matter yield.

ESTIMATION OF ABOVE GROUND BIOMASS OF THE THREE SITES (GRAZED SITE, PROTECTED SITE AND SEED SOWN SITE) FOR COMPARING THEIR PRODUCTIVITY IN KASHMIR VALLEY

2017 ◽  
Vol 23 (2) ◽  
Author(s):  
AFSHAN ANJUM BABA ◽  
SYED NASEEM UL-ZAFAR GEELANI ◽  
ISHRAT SALEEM ◽  
MOHIT HUSAIN ◽  
PERVEZ AHMAD KHAN ◽  
...  
Keyword(s):  
Protected Areas ◽  
Aboveground Biomass ◽  
Plant Biomass ◽  
Summer Season ◽  
Above Ground Biomass ◽  
Spring Season ◽  
Kashmir Valley ◽  
Ground Biomass ◽  
Maximum Value ◽  
Protected Site

The plant biomass for protected areas was maximum in summer (1221.56 g/m2) and minimum in winter (290.62 g/m2) as against grazed areas having maximum value 590.81 g/m2 in autumn and minimum 183.75 g/m2 in winter. Study revealed that at Protected site (Kanidajan) the above ground biomass ranged was from a minimum (1.11 t ha-1) in the spring season to a maximum (4.58 t ha-1) in the summer season while at Grazed site (Yousmarag), the aboveground biomass varied from a minimum (0.54 t ha-1) in the spring season to a maximum of 1.48 t ha-1 in summer seasonandat Seed sown site (Badipora), the lowest value of aboveground biomass obtained was 4.46 t ha-1 in spring while as the highest (7.98 t ha-1) was obtained in summer.

scholarly journals The climatic imprint of bimodal distributions in vegetation cover for western Africa

2016 ◽  
Vol 13 (11) ◽  
pp. 3343-3357 ◽  
Author(s):  
Zun Yin ◽  
Stefan C. Dekker ◽  
Bart J. J. M. van den Hurk ◽  
Henk A. Dijkstra
Keyword(s):  
Land Cover ◽  
Congo Basin ◽  
Shortwave Radiation ◽  
Mean Annual Precipitation ◽  
Above Ground Biomass ◽  
Precipitation Regime ◽  
Ground Biomass ◽  
Western Africa ◽  
Precipitation Regimes ◽  
Woody Cover

Abstract. Observed bimodal distributions of woody cover in western Africa provide evidence that alternative ecosystem states may exist under the same precipitation regimes. In this study, we show that bimodality can also be observed in mean annual shortwave radiation and above-ground biomass, which might closely relate to woody cover due to vegetation–climate interactions. Thus we expect that use of radiation and above-ground biomass enables us to distinguish the two modes of woody cover. However, through conditional histogram analysis, we find that the bimodality of woody cover still can exist under conditions of low mean annual shortwave radiation and low above-ground biomass. It suggests that this specific condition might play a key role in critical transitions between the two modes, while under other conditions no bimodality was found. Based on a land cover map in which anthropogenic land use was removed, six climatic indicators that represent water, energy, climate seasonality and water–radiation coupling are analysed to investigate the coexistence of these indicators with specific land cover types. From this analysis we find that the mean annual precipitation is not sufficient to predict potential land cover change. Indicators of climate seasonality are strongly related to the observed land cover type. However, these indicators cannot predict a stable forest state under the observed climatic conditions, in contrast to observed forest states. A new indicator (the normalized difference of precipitation) successfully expresses the stability of the precipitation regime and can improve the prediction accuracy of forest states. Next we evaluate land cover predictions based on different combinations of climatic indicators. Regions with high potential of land cover transitions are revealed. The results suggest that the tropical forest in the Congo basin may be unstable and shows the possibility of decreasing significantly. An increase in the area covered by savanna and grass is possible, which coincides with the observed regreening of the Sahara.

Above-ground biomass estimation of Indian tropical forests using X band Pol-InSAR and Random Forest

2021 ◽  
Vol 21 ◽  
pp. 100462
Author(s):  
Sadhana Yadav ◽  
Hitendra Padalia ◽  
Sanjiv K. Sinha ◽  
Ritika Srinet ◽  
Prakash Chauhan
Keyword(s):  
Random Forest ◽  
Tropical Forests ◽  
Biomass Estimation ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
X Band

scholarly journals Comparison of Capability of SAR and Optical Data in Mapping Forest above Ground Biomass Based on Machine Learning

2020 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Negar Tavasoli ◽  
Hossein Arefi
Keyword(s):  
Machine Learning ◽  
Carbon Stock ◽  
Vegetation Indices ◽  
Forest Biomass ◽  
Principal Component ◽  
Optical Data ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Texture Characteristics ◽  
Sentinel 2

Assessment of forest above ground biomass (AGB) is critical for managing forest and understanding the role of forest as source of carbon fluxes. Recently, satellite remote sensing products offer the chance to map forest biomass and carbon stock. The present study focuses on comparing the potential use of combination of ALOSPALSAR and Sentinel-1 SAR data, with Sentinel-2 optical data to estimate above ground biomass and carbon stock using Genetic-Random forest machine learning (GA-RF) algorithm. Polarimetric decompositions, texture characteristics and backscatter coefficients of ALOSPALSAR and Sentinel-1, and vegetation indices, tasseled cap, texture parameters and principal component analysis (PCA) of Sentinel-2 based on measured AGB samples were used to estimate biomass. The overall coefficient (R2) of AGB modelling using combination of ALOSPALSAR and Sentinel-1 data, and Sentinel-2 data were respectively 0.70 and 0.62. The result showed that Combining ALOSPALSAR and Sentinel-1 data to predict AGB by using GA-RF model performed better than Sentinel-2 data.

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