Managing production constraints to the reliability of chickpea (Cicer arietinum L.) within marginal areas of the northern grains region of Australia

2007 ◽  
Vol 58 (5) ◽  
pp. 396 ◽  
Author(s):  
J. P. M. Whish ◽  
P. Castor ◽  
P. S. Carberry
Keyword(s):  
Crop Yields ◽  
Management Strategies ◽  
Sowing Date ◽  
Grain Legume ◽  
Wheat Crop ◽  
Available Water ◽  
Marginal Areas ◽  
Plant Available Water ◽  
Management Approaches ◽  
Rotation Crop

The poor reliability of chickpea yield produced in the marginal (<600 mm rainfall) areas of the northern cropping zone is a constraint to the wide adoption of the crop. Chickpea is a valuable rotation crop and is currently the only viable winter grain legume suitable to this region. This paper uses results from in-crop monitoring and crop simulation, to identify practical management strategies to improve the reliability of chickpea crops in this region. APSIM-Chickpea successfully simulated the commercial yields of chickpea crops monitored during the study. Soil water at sowing and sowing date were identified as key determinants of yield. A ‘rule of thumb’ was derived, which showed that crops sown with a starting plant-available water of ~100 mm at sowing had an 80% probability of producing a better than break-even yield for the majority of the region and this was independent of the soil’s plant-available water capacity or crop sowing date. The probability of accumulating 100 mm of stored water in this western region is 90% following harvest of a May–sown wheat crop. Increased plant population improved crop yields in 60% of years, but this only translated to improved returns in ~50% of those years. The use of these simple management approaches will improve the reliability of chickpea production and ensure that these marginal areas have the option of a viable winter grain legume in their rotations.

scholarly journals A Model to Predict Plant-available Water Content of Soils at Different Land Units in Bengkulu, Indonesia

2020 ◽  
Vol 3 (1) ◽  
pp. 10-14
Author(s):  
Bandi Hermawan ◽  
Hasanudin Hasaanudin ◽  
Indra Agustian ◽  
Bambang Gonggo Murcitro
Keyword(s):  
Organic Carbon ◽  
Water Content ◽  
Soil Water ◽  
Management Strategies ◽  
Physical Property ◽  
Minimum Condition ◽  
Undisturbed Soil ◽  
Available Water ◽  
Available Water Content ◽  
Plant Available Water

Soil water availability to the plants is a very important physical property of soil that controls water and nutrient absorption by the plant.  It is defined as the difference between the maximum amount of water the soil can hold and the minimum condition that the plant can no longer extract water from the soil.  However, soil factors that control the plant available water content (PAWC) in the soil have not been fully understood.  The present study aims to analyze the relations between particle-size distributions and organic carbon with the available water of the soil and to develop a model of predicting PAWC.  Five soil profiles at different land units were described up to the depth of 100 cm.  Ten undisturbed soil samples were taken using the stainless-made core sampler from 10 cm increments for the soil water holding capacity analysis.  A similar number of disturbed samples were also provided from the same depths for soil texture and organic carbon analysis.  Results showed that the variance in PAWC could be explained by sand and clay fractions (R2>0.35) but not by silt and organic carbon contents.  Therefore, we were able to develop a model for the prediction of available water content in the soil from the sand and clay parameters.  The model will help decision-makers be able to propose conservation and management strategies for PAWC in agricultural practices as well as for the soil moisture retention at civil works.

scholarly journals Measuring and Modeling the Water Balance in Low-Rainfall Cropping Systems

2017 ◽  
Vol 60 (6) ◽  
pp. 2097-2110 ◽  
Author(s):  
Anthony M. Whitbread ◽  
Munir P. Hoffmann ◽  
C. William Davoren ◽  
Damian Mowat ◽  
Jeffrey A. Baldock
Keyword(s):  
Risk Management ◽  
Water Balance ◽  
Soil Water ◽  
Cropping Systems ◽  
Management Strategies ◽  
Climate Risk ◽  
Management Options ◽  
Crop Models ◽  
Available Water ◽  
Plant Available Water

Abstract. In low-rainfall cropping systems, understanding the water balance, and in particular the storage of soil water in the rooting zone for use by crops, is considered critical for devising risk management strategies for grain-based farming. Crop-soil modeling remains a cost-effective option for understanding the interactions between rainfall, soil, and crop growth, from which management options can be derived. The objective of this study was to assess the error in the prediction of soil water content at key decision points in the season against continuous, multi-layer soil water measurements made with frequency domain reflectometry (FDR) probes in long-term experiments in the Mallee region of South Australia and New South Wales. Field estimates of the crop lower limit or drained upper limit were found to be more reliable than laboratory-based estimates, despite the fact that plant-available water capacity (PAWC) did not substantially differ between the methods. Using the Agricultural Production Systems sIMulator (APSIM) to simulate plant-available water over three-year rotations, predicted soil water was within 7 mm (PAWC 64 to 99 mm) of the measured data across all sowing events and rotations. Simulated (n = 46) wheat grain production resulted in a root mean square error (RMSE) of 492 kg ha-1, which is only marginally smaller than that of other field studies that derived soil water limits with less detailed methods. This study shows that using field-derived data of soil water limits and soil-specific settings for parameterization of other properties that determine soil evaporation and water redistribution enables APSIM to be widely applied for managing climate risk in low-rainfall environments. Keywords: APSIM, Climate risk management, Crop models, Decision support, Soil moisture.

scholarly journals FAO AquaCrop model for determining optimum wheat sowing date in Tarai region of Uttarakhand

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 189-192
Author(s):  
NEHA PAREEK ◽  
SUMANA ROY ◽  
A.S. NAIN ◽  
SMITA GUPTA ◽  
GAURAVKUMAR CHATURVEDI
Keyword(s):  
Crop Yields ◽  
Wheat Yield ◽  
Field Research ◽  
Sowing Date ◽  
Yield Potential ◽  
Research Centre ◽  
Wheat Crop ◽  
Sowing Time ◽  
Sowing Dates ◽  
Aquacrop Model

The ideal sowing period is critical for maximizing the crop's yield potential under specific agroclimatic conditions (Nain, 2016; Patra et al., 2017). It influences the phenological stages of the crop's development and, as a result, the efficient conversion of biomass into economic yield. During rabi 2013-14, a field research was done at GBPUA&T's Borlaug Crop Research Centre to determine the best sowing dates for wheat crops employing Aquacrop model. Aquacrop model has been calibrated against vegetative and economic yield forthree sowing dates, viz., 3rd December, 18th December and 3rd January (Pareek et al., 2017). After calibrating the Aquacrop model, a set of conservative variables was obtained (Pareek et al., 2017). Afterward, the calibrated Aquacrop model was used to validate wheat yield and biomass for three years in a row, namely 2010-11, 2011-12 and 2012-13. The model subsequently used to simulate yield under different sowing dates. For all of the tested years, the simulation findings of the Aquacrop model reflected the observed crop yields and biomass of wheat. The model was used to simulate the optimum sowing week based on varying sowing dates and produced grain yield for a period of 10 years (Malik et al., 2013). The average and assured yield of wheat was worked out based on probability analysis (60, 75 and 90%). The optimum sowing time for Tarai region of Uttarakhand was suggested as first week of November followed by second week of November (Nain, 2016). In no case wheat should be sown during third week of November and beyond due to poor assured yield and average yield (Nain, 2016). The finding of the studies will help to increase productivity and production of wheat crop in Tarai region of Uttarakhand.  

scholarly journals Detection and Analysis of Degree of Maize Lodging Using UAV-RGB Image Multi-Feature Factors and Various Classification Methods

2021 ◽  
Vol 10 (5) ◽  
pp. 309
Author(s):  
Zixu Wang ◽  
Chenwei Nie ◽  
Hongwu Wang ◽  
Yong Ao ◽  
Xiuliang Jin ◽  
...  
Keyword(s):  
Crop Production ◽  
Accurate Determination ◽  
Management Strategies ◽  
Canopy Structure ◽  
Object Oriented ◽  
Texture Features ◽  
Sowing Date ◽  
Kappa Coefficient ◽  
Surface Model ◽  
Field Management

Maize (Zea mays L.), one of the most important agricultural crops in the world, which can be devastated by lodging, which can strike maize during its growing season. Maize lodging affects not only the yield but also the quality of its kernels. The identification of lodging is helpful to evaluate losses due to natural disasters, to screen lodging-resistant crop varieties, and to optimize field-management strategies. The accurate detection of crop lodging is inseparable from the accurate determination of the degree of lodging, which helps improve field management in the crop-production process. An approach was developed that fuses supervised and object-oriented classifications on spectrum, texture, and canopy structure data to determine the degree of lodging with high precision. The results showed that, combined with the original image, the change of the digital surface model, and texture features, the overall accuracy of the object-oriented classification method using random forest classifier was the best, which was 86.96% (kappa coefficient was 0.79). The best pixel-level supervised classification of the degree of maize lodging was 78.26% (kappa coefficient was 0.6). Based on the spatial distribution of degree of lodging as a function of crop variety, sowing date, densities, and different nitrogen treatments, this work determines how feature factors affect the degree of lodging. These results allow us to rapidly determine the degree of lodging of field maize, determine the optimal sowing date, optimal density and optimal fertilization method in field production.

scholarly journals Biological control agents in the integrated nematode management of potato in Egypt

2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Mahfouz M. M. Abd-Elgawad
Keyword(s):  
Biological Control ◽  
Crop Yields ◽  
Integrated Management ◽  
Management Strategies ◽  
Economic Value ◽  
Potato Production ◽  
Parasitic Nematodes ◽  
Main Body ◽  
Biological Control Agents ◽  
Economic Significance

Abstract Background Potato represents Egypt’s largest vegetable export crop. Many plant-parasitic nematodes (PPNs) are globally inflicting damage to potato plants. In Egypt, their economic significance considerably varies according to PPN distribution, population levels, and pathogenicity. Main body This review article highlights the biology, ecology, and economic value of the PPN control viewpoint. The integration of biological control agents (BCAs), as sound and safe potato production practice, with other phytosanitary measures to manage PPNs is presented for sustainable agriculture. A few cases of BCA integration with such other options as synergistic/additive PPN management measures to upgrade crop yields are reviewed. Yet, various attributes of BCAs should better be grasped so that they can fit in at the emerging and/or existing integrated management strategies of potato pests. Conclusion A few inexpensive biocontrol products, for PPNs control on potato, versus their corresponding costly chemical nematicides are gathered and listed for consideration. Hence, raising awareness of farmers for making these biologicals familiar and easy to use will promote their wider application while offering safe and increased potato yield.

scholarly journals Impacts of extreme precipitation and seasonal changes in precipitation on plants

2014 ◽  
Vol 11 (11) ◽  
pp. 3083-3093 ◽  
Author(s):  
M. J. B. Zeppel ◽  
J. V. Wilks ◽  
J. D. Lewis
Keyword(s):  
Extreme Precipitation ◽  
Seasonal Changes ◽  
Net Primary Productivity ◽  
Hydrological Cycle ◽  
Aridity Index ◽  
Summer Precipitation ◽  
Negative Effects ◽  
Available Water ◽  
Key Factor ◽  
Plant Available Water

Abstract. The global hydrological cycle is predicted to become more intense in future climates, with both larger precipitation events and longer times between events in some regions. Redistribution of precipitation may occur both within and across seasons, and the resulting wide fluctuations in soil water content (SWC) may dramatically affect plants. Though these responses remain poorly understood, recent research in this emerging field suggests the effects of redistributed precipitation may differ from predictions based on previous drought studies. We review available studies on both extreme precipitation (redistribution within seasons) and seasonal changes in precipitation (redistribution across seasons) on grasslands and forests. Extreme precipitation differentially affected above-ground net primary productivity (ANPP), depending on whether extreme precipitation led to increased or decreased SWC, which differed based on the current precipitation and aridity index of the site. Specifically, studies to date reported that extreme precipitation decreased ANPP in mesic sites, but, conversely, increased ANPP in xeric sites, suggesting that plant-available water is a key factor driving responses to extreme precipitation. Similarly, the effects of seasonal changes in precipitation on ANPP, phenology, and leaf and fruit development varied with the effect on SWC. Reductions in spring or summer generally had negative effects on plants, associated with reduced SWC, while subsequent reductions in autumn or winter had little effect on SWC or plants. Similarly, increased summer precipitation had a more dramatic impact on plants than winter increases in precipitation. The patterns of response suggest xeric biomes may respond positively to extreme precipitation, while comparatively mesic biomes may be more likely to be negatively affected. Moreover, seasonal changes in precipitation during warm or dry seasons may have larger effects than changes during cool or wet seasons. Accordingly, responses to redistributed precipitation will involve a complex interplay between plant-available water, plant functional type and resultant influences on plant phenology, growth and water relations. These results highlight the need for experiments across a range of soil types and plant functional types, critical for predicting future vegetation responses to future climates.

Sign in / Sign up

Export Citation Format

Share Document