Selection of crop cultivars suited to the location combined with astute management can reduce crop yield penalties in pasture cropping systems

2014 ◽  
Vol 65 (10) ◽  
pp. 1022 ◽  
Author(s):  
Dean T. Thomas ◽  
Roger A. Lawes ◽  
Katrien Descheemaeker ◽  
Andrew D. Moore

Pasture cropping is an emerging farming-systems practice of southern Australia, in which winter grain crops are sown into an established stand of a winter-dormant, summer-growing perennial pasture. There is a pressing need to define times, locations and climates that are suitable for pasture cropping. To evaluate effects of management interventions, agro-environment, and possible interactions on crop and pasture productivity associated with pasture cropping, an AusFarm® simulation model was built to describe a pasture-cropping system based on annual crop and subtropical grass. The model was parameterised using data from field research on pasture cropping with barley cv. Buloke and a C4 subtropical grass, Gatton panic (Panicum maximum cv. Gatton), conducted at Moora, Western Australia. The simulation was run over 50 years using the historical climate data of five southern Australian locations (Cunderdin, Jerdacuttup, Mingenew, and Moora in Western Australia, and Karoonda in South Australia). Two wheat cultivars and one barley crop were considered for each location, to examine the impact of crop phenology on this farming system. Jerdacuttup and Moora favoured pasture cropping, with average barley-yield penalties of 10 and 12%. These locations were characterised by colder growing seasons, more plant-available water at anthesis, and more winter–spring rain. The cereal crops did not rely on stored soil moisture, growing instead on incident rain. The winter–spring growth of the Gatton panic pasture was highest at Mingenew. This generated a high yield penalty, 38% loss under pasture cropping, compared with the other locations. Changing the efficacy of a herbicide application to the pasture when the crop was sown had a strong effect on yield. Yield penalties at Moora and Mingenew reduced to 7 and 29%, respectively, when the proportion of live biomass killed by the herbicide was doubled. Utilisation of soil moisture by the Gatton panic pasture during summer and early autumn had little effect on subsequent grain yield, whereas reduced pasture growth during the winter–spring growing period had a substantial effect on crop yield. Pasture cropping can therefore succeed in agro-climatic regions where crops can be grown on incident rain and pasture growth is suppressed through low temperature or herbicide. Perennial pasture growth should be minimised during the crop growing period through the management of crop sowing date, nitrogen fertiliser application and C4 grass suppression to minimise the effect on stored soil water at crop anthesis.

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Mohammadreza Mohammadi ◽  
John Finnan ◽  
Chris Baker ◽  
Mark Sterling

This paper examines the impact that climate change may have on the lodging of oats in the Republic of Ireland and the UK. Through the consideration of a novel lodging model representing the motion of an oat plant due to the interaction of wind and rain and integrating future predictions of wind and rainfall due to climate change, appropriate conclusions have been made. In order to provide meteorological data for the lodging model, wind and rainfall inputs are analysed using 30 years’ time series corresponding to peak lodging months (June and July) from 38 meteorological stations in the United Kingdom and the Irish Republic, which enables the relevant probability density functions (PDFs) to be established. Moreover, climate data for the next six decades in the British Isles produced by UK climate change projections (UKCP18) are analysed, and future wind and rainfall PDFs are obtained. It is observed that the predicted changes likely to occur during the key growing period (June to July) in the next 30 years are in keeping with variations, which can occur due to different husbandry treatments/plant varieties. In addition, the utility of a double exponential function for representing the rainfall probability has been observed with appropriate values for the constants given.


2013 ◽  
pp. 17-23
Author(s):  
Enikő Bene

Production year 2012 has been characterised by climatic extremities. The weather of this year can be considered very contradictory in terms of maize production. The droughty conditions of the winter and spring months had a negative effect on both germination and starting vigour. The favourable weather of May-July created ideal conditions for intensive growth and generative processes; however the lack of precipitation in August and September had a damaging effect on the development of yield composing elements and grain saturation processes as well. Under such circumstances, the sowing date models caused significant differences in the yield and quality of the hybrids belonging to different growth periods. The growing period of the maize hybrids has been shortened as a result of the unfavourable climatic conditions. Based on the trial results, it is verifiable that short growing period hybrids can be securely sown in draughty years even with a later sowing date, however using a later sowing date in the case of longer growth period hybrids may result even in a yield loss of 2–3 t ha-1. In the case of early and average sowing dates, with given yearly conditions the hybrids of the observed FAO 370-390 hybrid group provided the best result (12.40 t ha-1, 10.99 t ha-1), while in the case of the third, late sowing date the yield dominance of the FAO 290-350 hybrid group is the most significant (10.08 t ha-1). The analysis of the yield composing elements found that the P9578 hybrid has the highest shelling ratio, while its cob is the shortest. The P9494 hybrid has a high yield and the highest thousand grain weight, while the DKC 4983 has the longest cob and its thousand grain weight is above 300 g. The results confirm the fact that DKC 4590 has the highest yield potential and starch content, while in terms of oil and protein content the Szegedi 386 and NK Octet hybrids are the most important.


2020 ◽  
Vol 12 (20) ◽  
pp. 3439
Author(s):  
Mendy van der Vliet ◽  
Robin van der Schalie ◽  
Nemesio Rodriguez-Fernandez ◽  
Andreas Colliander ◽  
Richard de Jeu ◽  
...  

Reliable soil moisture retrievals from passive microwave satellite sensors are limited during certain conditions, e.g., snow coverage, radio-frequency interference, and dense vegetation. In these cases, the retrievals can be masked using flagging algorithms. Currently available single- and multi-sensor soil moisture products utilize different flagging approaches. However, a clear overview and comparison of these approaches and their impact on soil moisture data are still lacking. For long-term climate records such as the soil moisture products of the European Space Agency (ESA) Climate Change Initiative (CCI), the effect of any flagging inconsistency resulting from combining multiple sensor datasets is not yet understood. Therefore, the first objective of this study is to review the data flagging system that is used within multi-sensor ESA CCI soil moisture products as well as the flagging systems of two other soil moisture datasets from sensors that are also used for the ESA CCI soil moisture products: The level 3 Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active/Passive (SMAP). The SMOS and SMAP soil moisture flagging systems differ substantially in number and type of conditions considered, critical flags, and data source dependencies. The impact on the data availability of the different flagging systems were compared for the SMOS and SMAP soil moisture datasets. Major differences in data availability were observed globally, especially for northern high latitudes, mountainous regions, and equatorial latitudes (up to 37%, 33%, and 32% respectively) with large seasonal variability. These results highlight the importance of a consistent and well-performing approach that is applicable to all individual products used in long-term soil moisture data records. Consequently, the second objective of the present study is to design a consistent and model-independent flagging strategy to improve soil moisture climate records such as the ESA CCI products. As snow cover, ice, and frozen conditions were demonstrated to have the biggest impact on data availability, a uniform satellite driven flagging strategy was designed for these conditions and evaluated against two ground observation networks. The new flagging strategy demonstrated to be a robust flagging alternative when compared to the individual flagging strategies adopted by the SMOS and SMAP soil moisture datasets with a similar performance, but with the applicability to the entire ESA CCI time record without the use of modelled approximations.


2015 ◽  
Vol 16 (2) ◽  
pp. 904-916 ◽  
Author(s):  
Husayn El Sharif ◽  
Jingfeng Wang ◽  
Aris P. Georgakakos

Abstract Agricultural models, such as the Decision Support System for Agrotechnology Transfer cropping system model (DSSAT-CSM), have been developed for predicting crop yield at field and regional scales and to provide useful information for water resources management. A potentially valuable input to agricultural models is soil moisture. Presently, no observations of soil moisture exist covering the entire United States at adequate time (daily) and space (~10 km or less) resolutions desired for crop yield assessments. Data products from NASA’s upcoming Soil Moisture Active Passive (SMAP) mission will fill the gap. The objective of this study is to demonstrate the usefulness of the SMAP soil moisture data in modeling and forecasting crop yields and irrigation amount. A simple, efficient data assimilation algorithm is presented in which the agricultural crop model DSSAT-CSM is constrained to produce modeled crop yield and irrigation amounts that are consistent with SMAP-type data. Numerical experiments demonstrate that incorporating the SMAP data into the agricultural model provides an added benefit of reducing the uncertainty of modeled crop yields when the weather input data to the crop model are subject to large uncertainty.


2021 ◽  
Vol 5 ◽  
Author(s):  
Mercy Cheruto Kebenei ◽  
Monicah Mucheru-Muna ◽  
Felista Muriu-Ng'ang'a ◽  
Charles Kimani Ndung'u

Deteriorating soil fertility, low unreliable rainfall and soil moisture stress has resulted to low crop yields among farmers of sub-Saharan Africa (SSA), necessitating a search for more sustainable production practices. Zai technology has the ability to promote soil moisture retention and enhances soil fertility. A four-seasons field experiment was conducted to assess the impact of Zai technology combined with cattle manure and inorganic fertilizer on selected soil properties and sorghum yields in Kabati, Kitui County. The experiment was set up in a Randomized Complete Block Design (RCBD) with eight treatments replicated thrice with sorghum Gadam as the test crop. Soil sampling was done at the beginning of the first season and at the end of the fourth season at a dept of 0–15 cm across each plot for laboratory analyses. From the results, the increase in electrical conductivity was significant at p < 0.05 in all the treatments after four cropping seasons. Total organic carbon significantly increased in Zai with cattle manure (p = 0.045), conventional with no input (p = 0.038) and conventional with cattle manure (p = 0.045). Available phosphorous significantly (p < 0.05) increased in treatments under Zai technology while total nitrogen significantly (p < 0.05) reduced after the four cropping seasons. There was a significant (p < 0.05) interactive effect of the tested factors on soil pH, electrical conductivity, total nitrogen, and available phosphorous at the end of the experiment. Moreover, there was significant (p < 0.05) interactive effects on grain yields (SR18 and SR19 seasons) and stover yields (SR18, LR19, and SR19 seasons), with higher yields being recorded in treatments under Zai technology. This study demonstrates the importance of Zai technology in increasing crop yield by trapping water and enhancing its retention and infiltration into the soil for uptake by plants. This study concluded that positive impacts on important soil properties and crop yield could be realized when Zai technology is utilized alongside either sole inorganics or a combination of organic and inorganic amendments and this could be used as a strategy to improve crop production in eastern Kenya and other similar areas.


2021 ◽  
Author(s):  
Robin van der Schalie ◽  
Mendy van der Vliet ◽  
Nemesio Rodríguez-Fernández ◽  
Wouter Dorigo ◽  
Tracy Scanlon ◽  
...  

<p>The CCI Soil Moisture dataset (CCI SM, Dorigo et al., 2017) is the most extensive climate data record (CDR) of satellite soil moisture to date and is based on observations from multiple active and passive microwave satellite sensors. It provides coverage all the way back to 1978 and is updated yearly both in terms of algorithm and temporal coverage. In order to maximize its function as a CDR, both long term consistency and (model-)independence are high priorities in its development. </p><p>Two important satellite missions integrated into the CCI SM are the ESA Soil Moisture and Ocean Salinity mission (SMOS, Kerr et al., 2010) and the NASA Soil Moisture Active Passive mission (SMAP, Entekhabi et al., 2010). These missions distinguish themselves with their unique L-band (1.4 GHz) radiometers, which are theoretically more suitable for soil moisture retrieval than the prior available higher frequencies like C- X- and Ku-band (6.9 to 18.0 GHz). </p><p>However, these L-band missions are lacking onboard sensors for observations from higher frequencies Ku-, K- and Ka-band, which are normally used within the Land Parameter Retrieval Model (Owe et al., 2008), the baseline algorithm for passive microwave retrievals within the CCI SM, for retrieving the effective temperature (Holmes et al., 2009) and providing filters for snow/frozen conditions (Van der Vliet et al., 2020). Therefore, the retrievals from the current L-band missions make use of temperature and filters derived from global Land Surface Models (LSM, Van der Schalie et al., 2016). For a CDR that should function as an independent climate benchmark, this is a strong disadvantage.</p><p>Within this study the aim is to evaluate the impact of replacing the LSM based input for L-band soil moisture retrievals with one that comes from passive microwave observations. We use an inter-calibrated dataset existing of 6 different sensors that cover the complete SMOS and SMAP historical record (and further), consisting of AMSR2, AMSR-E, TRMM, GPM, Fengyun-3B and Fengyun-3D. These satellites are merged together using a minimization function that also penalizes errors in the Microwave Polarization Difference Index (MPDI) for a higher level of stability compared to using traditional linear regressions.</p><p>As currently the 6 am L-band retrievals are seen as the most reliable, and are currently the only ones used within the CCI, the main focus will be on the effects of using the 1:30 am observations from the inter-calibrated dataset as input. However, to make the method also applicable for daytime observations, the 6 pm retrievals have also been tested using an average of 1:30 pm and 1:30 am (next day) observations.   </p><p>This evaluation will provide an overview of the differences, giving insight on how this affects coverage, mean values, standard deviations and their inter-correlation. Secondly, we will test the resulting quality against both in situ observations and ERA5. A similar performance of this new dataset shows this is a good way to standardize input on temperature and filtering within the CCI SM, further improving its consistency and function as a model-independent CDR.</p>


Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2455
Author(s):  
Xiaolin Guo ◽  
Yuan Yang ◽  
Zhansheng Li ◽  
Liangzhi You ◽  
Chao Zeng ◽  
...  

Drought is among the costliest natural disasters on both ecosystems and agroeconomics in China. However, most previous studies have used coarse resolution data or simply stopped short of investigating drought projection and its impact on crop yield. Motivated by the newly released higher-resolution climate projection dataset and the crucial need to assess the impact of climate change on agricultural production, the overarching goal of this study was to systematically and comprehensively predict future droughts at unprecedented resolutions over China as a whole. rather than region-specific projections, and then to further investigate its impact on crop yield by innovatively using a soil water deficit drought index. Methodologically, the drought projections were quantified from very high resolution climate data and further predicted impacts on crop yield over China using the standardized precipitation–evapotranspiration index (SPEI) at a relatively high (25 km) spatial resolution from NASA’s Earth Exchange Global Daily Downscaled Projections (NEX-GDDP). The results showed that (1) overall, China is projected to experience a significant decrease in SPEI (−0.15/decade under RCP (representative concentration pathway) 4.5; −0.14/decade under RCP8.5). Seasonally, the decreasing rate of SPEI is projected to be largest in winter (−0.2/decade and −0.31/decade) and the least in summer (−0.08/decade and −0.10/decade) under respective RCPs. (2) Regionally, winter/spring will get drier, especially at high latitudes/altitudes (North China and Tibetan plateau), and summer/autumn will get wetter in southern China. (3) Both the frequency and duration for medium and severe drought are projected to decrease, while extreme drought, particularly in high latitudes/altitudes, is projected to increase. (4) The percentage of the potential crop production affected by drought would increase to 36% (47%) by 2100 under RCP4.5 (RCP8.5). Especially, the ratio impacted by extreme drought is projected to increase over time and with much worse magnitude under RCP8.5; thus, adaptive crop policies are expected to address such a risk.


2021 ◽  
Vol 13 (13) ◽  
pp. 2480
Author(s):  
Robin van der Schalie ◽  
Mendy van der Vliet ◽  
Nemesio Rodríguez-Fernández ◽  
Wouter A. Dorigo ◽  
Tracy Scanlon ◽  
...  

The CCI Soil Moisture dataset (CCI SM) is the most extensive climate data record of satellite soil moisture to date. To maximize its function as a climate benchmark, both long-term consistency and (model-) independence are high priorities. Two unique L-band missions integrated into the CCI SM are SMOS and SMAP. However, they lack the high-frequency microwave sensors needed to determine the effective temperature and snow/frozen flagging, and therefore use input from (varying) land surface models. In this study, the impact of replacing this model input by temperature and filtering based on passive microwave observations is evaluated. This is derived from an inter-calibrated dataset (ICTB) based on six passive microwave sensors. Generally, this leads to an expected increase in revisit time, which goes up by about 0.5 days (~15% loss). Only the boreal regions have an increased coverage due to more accurate freeze/thaw detection. The boreal regions become wetter with an increased dynamic range, while the tropics are dryer with decreased dynamics. Other regions show only small differences. The skill was evaluated against ERA5-Land and in situ observations. The average correlation against ERA5-Land increased by 0.05 for SMAP ascending/descending and SMOS ascending, whereas SMOS descending decreased by 0.01. For in situ sensors, the difference is less pronounced, with only a significant change in correlation of 0.04 for SM SMOS ascending. The results indicate that the use of microwave-based input for temperature and filtering is a viable and preferred alternative to the use of land surface models in soil moisture climate data records from passive microwave sensors.


Agronomy ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 643
Author(s):  
Muhammad Fadzli Ali ◽  
Ammar Abdul Aziz ◽  
Alwyn Williams

Increased volatility in global rubber prices has led to declining Malaysian rubber production and smallholder income. Identifying rubber clones that can produce a consistently high yield in various environments is one of the potential measures to alleviate the impact of price fluctuations and improve smallholder livelihoods. In this study, we assessed rubber yields and yield stability of 37 rubber tree clones at two major production regions in Malaysia: Kota Tinggi (Southern region) and Sungai Buloh (Central region). In addition, we assessed relationships between climate data with rubber yields. Rubber yield and stability differed widely by clone, but showed relatively consistent trends across regions. Clones RRIM 2007, PB 260, and RRIM 2012 were high yielding in both regions and had high stability. Conversely, clone RRII 308 had the lowest mean yield across both regions and low stability. Mean annual yields showed a negative relationship with rising minimum temperatures, declining by ~3 g per tapping per tree (g t−1 t−1) per 1 °C rise in minimum temperature. Our findings highlight clones capable of achieving stable high yields. This information may be useful for breeders and agronomists in identifying germplasm and traits for further development. Further, this information can be used to assist clone recommendations to smallholders in these regions to mitigate the dual impacts of climate change and market volatility.


2014 ◽  
Vol 65 (10) ◽  
pp. 1002 ◽  
Author(s):  
R. A. Lawes ◽  
P. R. Ward ◽  
D. Ferris

In southern Australia, intercropping, pasture cropping and overcropping have evolved as techniques to address environmental problems such as dryland salinity and wind erosion and to utilise soil water outside the conventional winter-dominant growing season. We paired three winter-dormant pastures, including two subtropical C4 perennial species (Rhodes grass, Chloris gayana; Gatton panic, Megathyrsus maximus) and the summer-active perennial C3 legume siratro (Macroptilium atropurpureum), with a conventional barley (Hordeum vulgare)–lupin (Lupinus angustifolius) rotation to explore the extent to which different summer-active species reduced crop yields. We also examined whether the competition for resources could be altered by supplying increased nitrogen to the crop and changing the row spacing of the pasture. Under high-input conditions, pasture reduced cereal crop yields by up to 26% and lupin yields by up to 29%. Under low-input conditions, pasture cropping did not significantly reduce crop yield, and frequently increased crop yields. With low inputs, barley yield increases in 2011 ranged from 23% to 31%. In lupins under low-input conditions, yield increases ranged from 91% to 106% in 2010 and from –6% to +39% in 2012. The impact of the crop on the pasture was less pronounced, where the timing of pasture growth was delayed by the crop, but absolute levels of production were not influenced by the crop. Row spacing altered the temporal dynamic of pasture production; initially, the pasture produced less than the narrow spaced equivalent, but after 2 years, production exceeded that in the narrow row. Across all pasture species in 2009 and 2012, winter pasture production reduced crop yield by 0.32 and 0.4 t grain/ha pasture biomass produced, implying that moderate yield losses occurred because pasture production was also moderate. In the other two years, winter pasture production did not affect crop yield, suggesting that the pasture was able to utilise resources surplus to crop requirements. In this environment, with this combination of crops and summer-active pastures, higher levels of inputs did not enhance crop yield in a pasture-cropping system. We suggest that grain yield losses are lower in the low-input system and this implies that, at some level, competition between the species was reduced in a nitrogen-limited environment and the extent of the competition depended on season.


Sign in / Sign up

Export Citation Format

Share Document