scholarly journals Deep-drainage control and yield: the trade-off between trees and crops in agroforestry systems in the medium to low rainfall areas of Australia

2005 ◽  
Vol 56 (10) ◽  
pp. 1011 ◽  
Author(s):  
Y. M. Oliver ◽  
E. C. Lefroy ◽  
R. Stirzaker ◽  
C. L. Davies
Keyword(s):  
Water Management ◽  
Crop Yield ◽  
Farming System ◽  
Agroforestry Systems ◽  
Tree Age ◽  
Strongly Correlated ◽  
Deep Drainage ◽  
Gross Margin ◽  
Area Index ◽  
Trade Off

In the dryland cropping areas of southern Australia, at risk from dryland salinity, tree belts can improve water management by taking up water unused by crops, with the risk that crop yield will be reduced through competition. As there are few direct markets for tree products grown in the medium to low rainfall areas, the design of agroforestry systems becomes important in reducing the trade-off in crop yield. This study examined some factors that influence the trade-off between crop yield and deep-drainage control in order to develop design guidelines for medium to low rainfall agroforestry. Twenty-one sites in the grain-growing region of Western Australia and southern New South Wales were surveyed over 2 years for crop yields, tree leaf area index, and estimated recharge, providing data from 32 tree–crop interfaces on the relative influence of environmental factors and farming system characteristics on the trade-off between water management and crop yield. The factors most strongly correlated with higher yields were water-gaining sites, orientation that provided shelter from southerly to north-westerly (S, SW, W, NW) winds, and tree age (<10 years). The factors most strongly correlated with the area of cropped land protected against deep drainage were tree age (>10 years), lighter soil types, and low rainfall (<400 mm). Economic analysis of the trade-off required to produce a particular deep-drainage reduction target produced 3 groups of sites: (1) those where trees resulted in a gross margin increase of $15/ha and an estimated deep-drainage reduction of 52% (n = 3), (2) those with a gross margin loss of $49/ha and estimated deep-drainage reduction of 47% (n = 11), and (3) those with a gross margin loss of $163/ha and a deep-drainage reduction of 37% (n = 18). None of the 3 sites in the first group were in the most favourable class in both years, highlighting the vulnerability of a relatively fixed farming system to climate variability.

The case for and against perennial forages in the Australian sheep–wheat zone: modelling livestock production, business risk and environmental interactions

2014 ◽  
Vol 54 (12) ◽  
pp. 2029 ◽  
Author(s):  
Andrew D. Moore
Keyword(s):  
Financial Risk ◽  
Wind Erosion ◽  
Climatic Factors ◽  
Continuous Cropping ◽  
Deep Drainage ◽  
Gross Margin ◽  
Trade Off ◽  
Erosion Risk ◽  
Trade Offs ◽  
Nitrogen Inputs

Perennial forages have been proposed as a means of ameliorating both the summer–autumn feed gap and the risks posed by soil salinity and erosion in mixed farming areas of southern Australia. Whole-farm simulation analyses using the APSIM and GRAZPLAN models at nine locations across southern Australia have evaluated the likely trade-offs among expected profitability, financial risk, soil erosion risk, deep drainage and soil carbon change as annual pastures are converted to perennial pastures based on a C3 grass, a C4 grass or lucerne. Differences between perennial and annual feedbases in total pasture growth (median –11%, range –47% to +20%) and metabolisable energy supply from pasture (median +1%, range –48% to +52%) were diverse across locations and perennial species. At some locations, improvements in the pasture feedbase were counter-balanced by lower livestock intakes from crop stubbles. The modelled farming system with the highest profit included some perennial pasture at seven of the nine locations, but no one pasture species or land-use system predominated across all locations or producer risk attitudes. Local characteristics of the soils and farming systems are as important as broad climatic factors in determining how substituting perennial for annual pastures alters the trade-off between profitability and wind erosion risk. Further expanding permanent pastures into land currently used for crops only unequivocally reduced wind erosion risk at the four locations with Mediterranean climates. Lucerne grown in long rotations provided the best trade-off between mean gross margin and financial risk at Merriwagga and Temora. Permanent C3 or C4 perennial grass pastures separated from continuous cropping may simultaneously increase profits and reduce business and erosion risk at low-rainfall locations with Mediterranean climates, as long as they can be managed to persist. Managing pastures for greater nitrogen inputs could be considered as an erosion-abatement strategy.

Impact of Drainage Water Management on Crop Yield

2013 ◽  
Author(s):  
Matt Helmers ◽  
Xiaobo Zhou ◽  
Carl Pederson ◽  
Greg Brenneman
Keyword(s):  
Water Management ◽  
Crop Yield ◽  
Drainage Water ◽  
Drainage Water Management

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.

Economic performance of organic vs conventional vegetables production in Gaza strip

2014 ◽  
Vol 2 (2) ◽  
pp. 9-18
Author(s):  
Ahmed Abu Shaban
Keyword(s):  
Organic Farming ◽  
Gaza Strip ◽  
Farming System ◽  
Organic Production ◽  
Economic Feasibility ◽  
Production Costs ◽  
Economic Potential ◽  
Vegetable Crops ◽  
Gross Margin ◽  
Lower Production

Organic farming has achieved significant growth in developing countries. However, it is still in some areas such as Gaza strip at embryonic stage. Introduction and promotion of organic farming would need more information about economic feasibility of shifting from the existing conventional farms to organic farming system. This is the main aim of this study. Data was collected from 100 randomly selected farmers in southern area of Gaza strip using standard questionnaire. Additional focus group discussions were conducted for further qualitative analyses. Data was also collected from the organic farm of Safe Agriculture Association where vegetables are organically produced and marketed. Gross margin and comparative analyses were used to describe cost structure of conventional and organic production and to assess economic potentialities to shift to organic farming. Results varied among vegetable crops as some crops showed very high economic potential to shift to organic farming while other crops did not. Major reasons for crops with good potential were higher yield under organic farming, premium market prices and lower production costs. Major reasons for lower economic potential to shift were the significant lower yield and higher production costs. The study recommends further technical research to explore organic production techniques that allows for higher yield and lower production cost. The study also recommends further market research to investigate consumers' preferences and willingness to pay for organic products.

Crop Yield Modelling Applying Leaf Area Index Estimated from Sentinel-2 and Proba-V Data at JECAM site in Poland

2018 ◽  
Author(s):  
Katarzyna Dabrowska-Zielinska ◽  
Maciej Bartold ◽  
Radoslaw Gurdak ◽  
Martyna Gatkowska ◽  
Wojciech Kiryla ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Area Index ◽  
Sentinel 2

No tillage affects the phosphorus status, isotopic composition and crop yield of Phaseolus vulgaris in a rain-fed farming system

2010 ◽  
Vol 91 (2) ◽  
pp. 268-272 ◽  
Author(s):  
María del Mar Alguacil ◽  
Antonio Roldán ◽  
Jaime R Salinas-García ◽  
José Ignacio Querejeta
Keyword(s):  
Phaseolus Vulgaris ◽  
Isotopic Composition ◽  
Crop Yield ◽  
Farming System ◽  
No Tillage ◽  
Phosphorus Status

scholarly journals High organic inputs explain shallow and deep SOC storage in a long-term agroforestry system – Combining experimental and modeling approaches

2017 ◽  
Author(s):  
Rémi Cardinael ◽  
Bertrand Guenet ◽  
Tiphaine Chevallier ◽  
Christian Dupraz ◽  
Thomas Cozzi ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Priming Effect ◽  
Crop Residues ◽  
Triticum Turgidum ◽  
Juglans Regia ◽  
Farming System ◽  
Agroforestry System ◽  
Agroforestry Systems ◽  
Root Senescence ◽  
Soc Stocks

Abstract. Agroforestry is an increasingly popular farming system enabling agricultural diversification and providing several ecosystem services. In agroforestry systems, soil organic carbon (SOC) stocks are generally increased, but it is difficult to disentangle the different factors responsible for this storage. Organic carbon (OC) inputs to the soil may be larger, but SOC decomposition rates may be modified owing to microclimate, physical protection, or priming effect from roots, especially at depth. We used an 18-year-old silvoarable system associating hybrid walnut trees (Juglans regia × nigra) and durum wheat (Triticum turgidum L. subsp. durum), and an adjacent agricultural control plot to quantify all OC inputs to the soil – leaf litter, tree fine root senescence, crop residues, and tree row herbaceous vegetation –, and measure SOC stocks down 2 m depth at varying distances from the trees. We then proposed a model that simulates SOC dynamics in agroforestry accounting for both the whole soil profile and the lateral spatial heterogeneity. OC inputs to soil were increased by about 40 % (&amp;plus;1.11 t C ha−1 yr−1) down to 2 m depth in the agroforestry plot compared to the control, resulting in an additional SOC stock of 6.3 t C ha−1 down to 1 m depth. The model described properly the measured SOC stocks and distribution with depth. It showed that the increased inputs of fresh biomass to soil explained the observed additional SOC storage in the agroforestry plot. Moreover, modeling revealed a strong priming effect that would reduce the potential SOC storage due to higher organic inputs in the agroforestry system by 75 to 90 %. This result questions the potential of soils to store large amounts of carbon, especially at depth. Deep-rooted trees modify OC inputs to soil, a process that deserves further studies given its potential effects on SOC dynamics.

scholarly journals Relationships of NDVI, Biomass, and Leaf Area Index (LAI) for six key plant species in Barrow, Alaska

2015 ◽  
Author(s):  
Santonu Goswami ◽  
John Gamon ◽  
Sergio Vargas ◽  
Craig Tweedie
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Species ◽  
Vegetation Index ◽  
Plant Biomass ◽  
Plant Cover ◽  
Strongly Correlated ◽  
Area Index ◽  
Spectral Bands ◽  
Biomass Plant

Here we investigate relationships between NDVI, Biomass, and Leaf Area Index (LAI) for six key plant species near Barrow, Alaska. We explore how key plant species differ in biomass, leaf area index (LAI) and how can vegetation spectral indices be used to estimate biomass and LAI for key plant species. A vegetation index (VI) or a spectral vegetation index (SVI) is a quantitative predictor of plant biomass or vegetative vigor, usually formed from combinations of several spectral bands, whose values are added, divided, or multiplied in order to yield a single value that indicates the amount or vigor of vegetation. For six key plant species, NDVI was strongly correlated with biomass (R2 = 0.83) and LAI (R2 = 0.70) but showed evidence of saturation above a biomass of 100 g/m2 and an LAI of 2 m2/m2. Extrapolation of a biomass-plant cover model to a multi-decadal time series of plant cover observations suggested that Carex aquatilis and Eriophorum angustifolium decreased in biomass while Arctophila fulva and Dupontia fisheri increased 1972-2008.

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