Rainfed Crop Research Articles

Does Grazing Cover Crops Impact Soil Properties?

Grazing of cover crops (CCs) by cattle could provide supplemental forage and additional revenue to offset grain yield losses when CCs are grown in semiarid rainfed cropping systems. However, grazing CCs could reduce the amount of residue retained on the soil surface and subsequently affect soil physical and chemical properties. This study evaluated effects of grazing CCs on soil bulk density, aggregate stability, and chemical properties using soil samples collected from three producer fields in west central Kansas that had paired grazed and non-grazed CC treatments, as well as adjacent native perennial pastures. Across sites, CC residue after grazing averaged 2650 lb/a compared to 3741 lb/a for the non-grazed CCs, representing a 29% decrease in CC biomass with grazing. Bulk density, aggregate size distribution, and mean weight diameter (MWD) were not different (P > 0.05) between grazed and non-grazed CCs. The MWD under perennial pasture was 0.148 in., approximately 2.9-fold greater than MWD with grazed (0.050 in.) or non-grazed CCs (0.051 in.). Soil pH and soil organic carbon (SOC) did not differ (P > 0.05) between the grazed and non-grazed CCs. Soil nitrate (NO3-N), phosphorus (P), iron (Fe), manganese (Mn), and copper (Cu) concentrations with grazed or non-grazed CCs were greater than in pasture. Our findings showed grazing of CCs may be a management option to intensify NT cropping systems with little negative effects on soil bulk density, aggregate stability, or extractable nutrient concentrations.

Assessing yield and economic impact of introducing soybean to the lowland rice system in southern Brazil

Lowland irrigated rice in southern Brazil is typically grown in monoculture, with one rice crop per year. However, during the past 10 years, some farmers have switched from the traditional continuous rice system to a 2-y soybean-rice rotation. Here we performed an on-farm assessment about the impact of introducing soybean to the lowland continuous rice system in southern Brazil. The goal was to determine how the soybean-rice rotation compared to continuous rice in terms of yield and profit. We used farmer-reported survey data collected from lowland rice-based systems in southern Brazil over three growing seasons. Cropping-system yield, profit, and return-to-inputs were compared between fields following continuous rice versus soybean–rice rotation. In addition to the survey data analysis, we evaluated the long-term economic impact of adopting the rotation using a combination of a crop simulation model and Monte-Carlo stochastic modeling. Average rice yield was 26% higher in the rotation compared to continuous rice. Besides the rotation effect, sowing date, N fertilizer, and weed management explained most of the field-to-field variability in rice yield. Cropping-system yield and gross income were lower in the soybean-rice rotation than in continuous rice as a result of replacing an irrigated crop (rice) by a water-limited rainfed crop (soybean). Despite that yield penalty, there was no difference in net economic return between the two cropping systems due to lower production costs in soybean-rice rotation compared to continuous rice. The rotation also exhibited smaller labor requirement and higher benefit-to-cost ratio and return to labor than continuous rice. Despite these potential benefits, our long-term analysis indicated higher inter-annual variability and economic risk in the rotation compared to continuous rice. Other factors further constrain adoption of the soybean-rice rotation, including the high risk of growing soybean in fields that are prone to excess water and difficulties to change current farm logistics. Findings from this study are relevant to other rice-based systems in the world looking for opportunities to increase or maintain net profit while reducing costs and/or labor.

Scaling up crop diversification among farming communities for food security under climate change: A case study of the Kenyan pelis programme

Climate change poses significant risks to food security globally with predictions of 10-20 % decline in rain-fed crop yields by 2050. Sub-Saharan Africa remains highly susceptible to food shortage since over 95 % of the region’s total cropland is rain-fed. Kenya’s over reliance on rain-fed agriculture predisposes the country to climate-induced food insecurity. Murang’a County in Kenya is experiencing climate change challenges manifested in prolonged droughts and floods. The consequences,are failed cropping seasons, soil erosion, landslides, altered crop suitability and a resurgence of human, livestock, crop pests,and diseases,culminating into food insecurity. This study was conducted with Kimandi-Wanyaga community in the Gatanga Sub-County in Murang’a County, Kenya. Residents are smallholder subsistence rain-fed farmers. The study explored the potential of up-scaling crop diversification under the Plantation Establishment and Livelihood Improvement Scheme (PELIS) for food security vis-à-vis climate change. The community’s climate change coping strategies were explored to account for the need to up-scale crop diversification under PELIS. A mixed methods research design was applied whereby a systematic sampling method was used to select 281 household-heads. Three key informants were purposively selected and primary data were collected through a household survey, in-depth key stakeholder interviews, focus group discussions and on-farm trials. Quantitative data were analysed using descriptive and inferential statistics while qualitative data were analysed using thematic and content analysis. The study established that 92.9 % of the community perceived climate change and its impacts. They had adopted a combination of coping strategies most of which,were found to be informed by short-term survival and hence,considered inadequate for long-term adaptation. The PELIS approach had been piloted in Murang’a County and was found to be a promising strategy for crop diversification and food security among forest-adjacent communities. However, only 11 % of the studied community participated in the scheme. Therefore, the study endeavoured to work with the community to promote cultivation of traditional vegetables under PELIS for crop diversification and food security in the face of climate change.The PELIS beneficiaries who adopted cultivation of Black nightshade, Amaranths and Cowpeas managed to produce enough for household consumption and sale of surplus for income. The PELIS,therefore, possesses the co-benefits of climate change adaptation through crop diversification for food security and climate change mitigation through afforestation for carbon sequestration.

Impacts of Agroclimatic Variability on Maize Production in the Setsoto Municipality in the Free State Province, South Africa

The majority of people in South Africa eat maize, which is grown as a rain-fed crop in the summer rainfall areas of the country, as their staple food. The country is usually food secure except in drought years, which are expected to increase in severity and frequency. This study investigated the impacts of rainfall and minimum and maximum temperatures on maize yield in the Setsoto municipality of the Free State province of South Africa from 1985 to 2016. The variation of the agroclimatic variables, including the Palmer stress diversity index (PSDI), was investigated over the growing period (Oct–Apr) which varied across the four target stations (Clocolan, Senekal, Marquard and Ficksburg). The highest coefficients of variance (CV) recorded for the minimum and maximum temperatures and rainfall were 16.2%, 6.2% and 29% during the growing period. Non-parametric Mann Kendal and Sen’s slope estimator were used for the trend analysis. The result showed significant positive trends in minimum temperature across the stations except for Clocolan where a negative trend of 0.2 to 0.12 °C year−1 was observed. The maximum temperature increased significantly across all the stations by 0.04–0.05 °C year−1 during the growing period. The temperature effects were most noticeable in the months of November and February when leaf initiation and kernel filling occur, respectively. The changes in rainfall were significant only in Ficksburg in the month of January with a value of 2.34 mm year−1. Nevertheless, the rainfall showed a strong positive correlation with yield (r 0.46, p = < 0.05). The overall variation in maize production is explained by the contribution of the agroclimatic parameters; the minimum temperature (R2 0.13–0.152), maximum temperature (R2 0.214–0.432) and rainfall (R2 0.17–0.473) for the growing period across the stations during the study period. The PSDI showed dry years and wet years but with most of the years recording close to normal rainfall. An increase in both the minimum and maximum temperatures over time will have a negative impact on crop yield.

Impact of green water anomalies on global rainfed crop yields

The importance of green water (moisture from rain stored in soils) for global food and water security is widely recognized, with process-based simulation models and field-level studies demonstrating its role in supporting rainfed agriculture. Despite this evidence, the relationship between green water anomalies and rainfed agriculture has not yet been investigated using statistical models that identify a causal relationship between the variables. Here, we address this gap and use disaggregated statistical regression (panel data analysis) at the 30 arc-min grid level to study the response of observed yields (1982–2010) of four main crops (maize, rice, soybean and wheat) to green water anomalies globally over rainfed areas. Dry green water anomalies (1 or 2 standard deviations below long-term average) decrease rainfed crop yields worldwide. This effect is more pronounced for wheat and maize, whose yields decline by 12%–18% and 7%–12% respectively. Globally, agricultural production benefits from wet green water anomalies. This effect is intensified in arid climates and weakened in humid climates where, for wheat, soybean and rice, periods of green water availability 2 standard deviations above long-term averages lead to declines in crop yield. This confirms existing evidence that excess soil moisture is detrimental to crop yield. These findings (1) advance our understanding of the impact of green water on rainfed food production and (2) provide empirical evidence supporting arguments for better management of local green water resources to reduce the impact of agricultural drought and waterlogging on rainfed crop production and capture the yield increasing effects of positive green water anomalies.

Simplicity on the far side of complexity: optimizing nitrogen for wheat in increasingly variable rainfall environments

The increasingly chaotic nature of rainfall in semi-arid climates challenges crop growers to balance nitrogen fertiliser inputs for both food security and environmental imperatives. Too little nitrogen restricts yields and runs down soil organic carbon, while too much nitrogen is economically wasteful and environmentally harmful. The degree to which crop-water and crop-nitrogen processes combine to drive yields of rainfed wheat crops is not well understood or quantified. Here we investigate two comprehensive Australia-wide data sets, one from commercial wheat growers’ fields and the other from systematic simulation of 50 sites by 15 years using a comprehensive mechanistic cropping system model. From these data, we derived a simple model combining water use with available nitrogen and their interaction. The model accounted for 73% of the variation in the simulated yield data and 46% of the variation in the growers’ yield data. We demonstrate how the simple model developed here can be deployed as a tool to aid growers’ in-crop nitrogen application decisions.

Middle East Climate Response to the Saharan Vegetation Collapse during the Mid-Holocene

AbstractUnderstanding climate change in the Middle East (ME) is crucial because people’s living environment depends on rain-fed crop systems. It remains unclear whether the ME climate would be affected by the Saharan vegetation collapse at the end of the mid-Holocene (MH). Proxy data suggest a transition from humid to more arid ME conditions during the period of 6.5–5 kyr BP. Using a set of idealized sensitivity experiments with an Earth system model (EC-Earth), we infer that the shift of Saharan vegetation plays a role in this wet-to-dry transition over the ME. The experimental results show that the Saharan greening can significantly increase the late winter and early spring precipitation over the ME. The reason is that the vegetation decreases the surface albedo, which induces a warming in North Africa and generation of an anomalous low-level cyclonic flow, which transports moisture from tropical North Africa and the Red Sea to the ME. The moisture also flows from the Mediterranean Sea region to the ME through the enhanced mid- to upper-level westerlies. The enhanced moisture carried by westerly and southwesterly flows is lifted upon reaching Mesopotamia and the Zagros Mountains, substantially increasing the precipitation there. When the Sahara greening is removed, a drier condition happens in the ME. The crop model simulation further shows a substantial decrease in wheat yield in Mesopotamia with the reduction of Saharan vegetation, which is consistent with paleoclimatic reconstructions. These results imply that future changes in Saharan land cover may have climatic and agricultural impacts in the Middle East.

Analysis of Drought Susceptibility Index in Indian Mustard [Brassica juncea (L.) Czern and Coss

Background: Climatic variations such as drought have high level of impingement on the yield of rain-fed crops like mustard. A drought is an extended period of months or years when region notes a deficiency in its water availability. Water stress causes heavy yield losses in Indian mustard (17-94%). Low water availability during stem elongation, flowering and pod development causes reduction of pods per plant leading to reduction in grain yield. Very meagre efforts have been made towards improving drought tolerance of this crop. Hence there is an urgent need for, development of water use efficient genotypes. Drought Susceptibility Index (DSI) is a measure of drought, based on loss of yield under drought conditions in comparison to the yield under normal conditions. It expresses the separate effects of yield potential and drought susceptibility on yields under drought. In these terms, lower DSI is considered synonymous with higher drought tolerance. In view of above facts, present study is aimed at investigating the effects of drought on yield attributing traits with, the objective of identifying Indian mustard genotypes and their hybrids which can withstand water stress with minimum loss in yield. Methods: Nine Indian mustard genotypes and their F1s were evaluated under irrigated and rainfed conditions to study the effect of drought by calculating DSI, on yield and yield traits and to characterize their relative tolerance against drought at the Agriculture Research Farm, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi during Rabi 2017-18 season. Observations were made for different yield and yield related traits. Result: Genotype RB-50 was found as tolerant for seed yield per plant with DSI 0.38 while hybrids RB-50×RH-749 and RB-50×Giriraj were exhibiting tolerant DSI values for siliqua per plant, 1000 seed weight, seed yield per plant and oil content. These parents and F1s would serve as useful donors and hybrids respectively, in mustard breeding programmes for improving drought tolerance.

Impact Assessment of Best Management Practices (BMPs) on the Water Footprint of Agricultural Productions

Agriculture is the main source of diffuse nutrient pollution in surface waters. It requires best management practices (BMPs) for controlling the discharges of pollutants like total nitrogen (TN) and total phosphorous (TP). In addition, these pollutants are accounted in the grey water footprint (GWF) of agricultural productions. This study proposes an integrated methodology with two steps for assessing the impacts of BMPs on the water footprints (WF) of agricultural productions. First, this approach uses the soil and water assessment tool (SWAT) for basin modeling and calculating the required data for WF assessment. In the second step, the WFs of agricultural productions are quantified and compared in different BMP scenarios, including fertilizer and irrigation reduction (FIR) and the application of vegetated filter strips (VFS). The SWAT modeling shows that FIR and VFS are more effective on TN and TP reduction, respectively. It can estimate that the combination of BMPs has the potential of abating 60% of the TN and TP concentrations of lake in 8 years. However, the WFs of agricultural productions may not be significantly reduced by BMPs as the average GWF only constitutes 4.2% of WF in this basin. For instance, the combination of FIR and VFS can reduce the average WF of cereals from 44 to 41 m3/km2. Nevertheless, this practice is relatively more effective for irrigated crops. The WF of rain-fed crops remains constant on 37 m3/km2, while it is reduced 24% (from 91 to 69 m3/km2) for irrigated crops by BMPs. In addition, it is realized that FIR can adversely reduce the production yields up to 32%. All these findings verify that the proposed methodology can integrate BMP and WF assessments by SWAT modeling and is recommended for basins, where farmlands are the dominated land-use.

Evaluation of blackgram (Vigna mungo) genotypes for drought tolerance under field and in vitro conditions

Blackgram a rainfed crop often experiences soil moisture deficit that reduces productivity to a large extent, could overcome by using a suitable drought resistant variety. Based on this, the present investigation was carried out during 2018 at Department of Genetics and Plant Breeding, Faculty of Agriculture, Annamalai University to study the drought tolerance in twenty-one blackgram genotypes. The selected genotypes (IC-343943, IC-343947, IC-343962, ABG-11013, KU-11680, TBG-104, VBG-10010, VBG-11011, VBG12005, VBG-12062, VBG-13017, ADT-5, RU-16-9, RU-16-13, RU-16-14, KGB-28, T-9, VBN(Bg)-4, VBN(Bg)-6, VBN(Bg)-7, MDU Local) were evaluated in the field condition for drought tolerance by imposing water stress during flowering and pod setting stages (4060 days after sowing) of the crop. The screening was also carried out in vitro by using PEG6000 at three concentrations viz., 0 bar, -3 bars and -6 bars to assess their seedling response under induced osmotic potential. Reduced growth was observed in all blackgram genotypes for all the characters except for the number of days to first flowering. Based on per se performance of genotypes under water-stressed field condition, the genotypes VBG12005, IC-343943 and IC-343947 were recommended as drought-tolerant genotypes for seed yield. In vitro condition, reduction in germination percentage, plumule and radicle length and biomass yield observed under increasing polyethylene glycol (PEG) induced water stress. In vitro screening of blackgram genotypes using PEG 6000 found that the genotypes VBG-11011, RU-16-9 and VBG-13017 expressed tolerance to drought at seed germination level. Thus, seedling stage screening for drought tolerance alone is not reliable as the tolerance mechanism may vary at different growth stages.

Rainfall and Temperature Trend Analysis by Mann–Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo

This study investigates the trend in monthly and annual rainfall, minimum and maximum temperature (Tmin and Tmax) using the Mann–Kendall (MK) test and Sen’s slope (SS) method and evaluates the significance of their variability for maize, sorghum and millet yields in northern Togo employing multiple regression analysis. The historical data of Kara, Niamtougou, Mango and Dapaong weather stations from 1977 to 2012 were used. Four non-parametric methods—Alexandersson’s Standard Normal Homogeneity Test (SNHT), Buishand’s Range Test (BRT), Pettitt’s Test (PT) and Von Neumann’s Ratio Test (VNRT)—were applied to detect homogeneity in the data. For the data which were serially correlated, a modified version of the MK test (pre-whitening) was utilised. Results showed an increasing trend in the annual rainfall in all four locations. However, this trend was only significant at Dapaong (p < 0.1). There was an increasing trend in Tmax at Kara, Mango and Niamtougou, unlike Dapaong where Tmax revealed a significant decreasing trend (p < 0.01). Similarly, there was an increasing trend in Tmin at Kara, Mango and Dapaong, unlike Niamtougou where Tmin showed a non-significant decreasing trend (p > 0.05). Rainfall in Dapaong was found to have increased (7.79 mm/year) more than the other locations such as Kara (2.20 mm/year), Niamtougou (4.57 mm/year) and Mango (0.67 mm). Tmax increased by 0.13, 0.13 and 0.32 °C per decade at Kara, Niamtougou and Mango, respectively, and decreased by 0.20 per decade in Dapaong. Likewise, Tmin increased by 0.07, 0.20 and 0.02 °C per decade at Kara, Mango and Dapaong, respectively, and decreased by 0.01 °C per decade at Niamtougou. Results of multiple regression analysis revealed nonlinear yield responses to changes in rainfall and temperature. Rainfall and temperature variability affects rainfed cereal crops production, but the effects vary across crops. The temperature has a positive effect on maize yield in Kara, Niamtougou and Mango but a negative effect on sorghum in Niamtougou and millet in Dapaong, while rainfall has a negative effect on maize yield in Niamtougou and Dapaong and millet yield in Mango. In all locations, rainfall and temperature variability has a significant effect on the cereal crop yields. There is, therefore, a need to adopt some adaptation strategies for sustainable agricultural production in northern Togo.

Abundance and microhabitat use of rodent species in crop fields and bushland in Ethiopia

The abundance and microhabitat use of rodents were investigated in four different habitats: two rain-fed crop fields with differing stone bund density, an irrigated field and bushland. A total of 444 individual small mammals belonging to six rodent and one shrew species were recorded in trapping grids and line transects. Of these, 230 individuals (52%) belonged to three pest rodent species of crop fields in northern Ethiopia: Stenocephalemys albipes (65%), Mastomys awashensis (25%) and Arvicanthis niloticus (10%). Population abundance of the three species was higher in the early dry season compared to the rainy season. While the bushland was significantly (p < 0.05) favoured by S. albipes and M. awashensis in both seasons, the irrigated field was preferred by Arvicanthis niloticus in the early dry season. In the early dry season, the microhabitat use of A. niloticus was strongly associated with the type of ground cover (herb) (R2adj = 0.152, P < 0.01). While M. awashensis was associated with vegetation density (R2adj = 0.13, P < 0.01), S. albipes was associated with vegetation cover (R2adj = 0.102, P < 0.001). The findings indicate that co-occurring pest rodent species prefer different microhabitats. Understanding their co-occurrence particularly in crop fields is vital for crop protection as they are known serious agricultural pests in northern Ethiopia.

Phenology-Adjusted Stress Severity Index to Assess Genotypic Responses to Terminal Drought in Field Grown Potato

Potato is a drought susceptible, often rain-fed crop suffering strongly from even short periods of soil water deficit. With global environmental conditions changing, potato clones resistant to variable water supply are needed and identifying them is a major task. Many indices assessing potato tolerance to water deficit have been proposed, albeit none of them takes into account the severity of the stress or the sensitivity of the developmental stage during which the stress occurs. As a result, data obtained on genotypes in one location or season are normally not useful in another location or in a different season. We have developed an index evaluating yield response of potato to water deficit based on the soil tension the genotype was subjected to for the duration of the stress modified by the development stage of the genotype. The sum of the daily values was combined in a stress severity index (SSI). In total thirteen genotypes differing in duration and sensitivity to drought were subjected to four levels of deficit irrigation on two soil types at different development stages over two years. Early drought (early tuber filling) reduced yields up to 95% whereas late drought (late tuber bulking) reduced yields significantly less. SSI depended on the genotypic phenological development and on the soil tension values and ranges between 25 and 3500. The index differentiated genotypic responses well across treatments and soil types, even with these relatively advanced development stages, up to a value of 1000. Beyond 1000, yields were generally reduced by more than 60% and a differentiation between genotypes was not possible anymore. SSI constitutes a method that renders site, location, year, season, and soil type effects comparable for responses of potato clones to soil water deficit. Combining this measure of stress severity with other proposed indices may improve upon their current weaknesses in finding or identifying the underlying traits of drought tolerance in potato.

First Insights on Soil Respiration Prediction across the Growth Stages of Rainfed Barley Based on Simulated MODIS and Sentinel-2 Spectral Indices

Rainfed agriculture occupies the majority of the world’s agricultural surface and is expected to increase in the near future causing serious effects on carbon cycle dynamics in the context of climate change. Carbon cycle across several temporal and spatial scales could be studied through spectral indices because they are related to vegetation structure and functioning and hence with carbon fluxes, among them soil respiration (Rs). The aim of this work was to assess Rs linked to crop phenology of a rainfed barley crop throughout two seasons based on spectral indices calculated from field spectroscopy data. The relationships between Rs, Leaf Area Index (LAI) and spectral indices were assessed by linear regression models with the adjusted coefficient of determination (Radj2). Results showed that most of the spectral indices provided better information than LAI throughout the studied period and that soil moisture and temperature were relevant variables in specific periods. During vegetative stages, indices based on the visible (VIS) region showed the best relationship with Rs. On the other hand, during reproductive stages indices containing the near infrared-shortwave infrared (NIR-SWIR) spectral region and those related to water content showed the highest relationship. The inter-annual variability found in Mediterranean regions was also observed in the estimated ratio of carbon emission to carbon fixation between years. Our results show the potential capability of spectral information to assess soil respiration linked to crop phenology across several temporal and spatial scales. These results can be used as a basis for the utilization of other remote information derived from satellites or airborne sensors to monitor crop carbon balances.

Changes in water fluxes partition related to the replacement of native dry forests by crops in the Dry Chaco

Land-use change has been the strongest driver of vegetation cover change in the world. In the South American Dry Chaco (~1 M km2; PPT/ET0 < 0.65), native dry forests are experiencing high deforestation rates that tend to continue in the coming years. Here, we used a hydrological model (Hydrus 1-D) to analyze changes in the water balance triggered by the replacement of dry forests by annual rainfed summer crops. We found that transpiration represented the main water vapour flux in both vegetation covers (59 and 48% of annual rainfall in dry forest and cropland, respectively), followed by evaporation (31 and 30%, respectively) and interception (11 and 9%, respectively). Runoff was five times higher in the cropland compared to the dry forest (10 vs. 2%; p < 0.01). Deep drainage was a negligible water flux in dry forests but it represented 4% of annual rainfall in croplands (p < 0.01), reaching values of zero and 130 mm year−1 for dry and wet years, respectively. Our results highlight the key role of vegetation cover controlling ecosystem water fluxes in the Dry Chaco. More generally, we suggest that the expansion of dryland cultivation can modify the regional water balance and threaten the primary production of ecosystems in the long run.

MAPPING IRRIGATED AREAS USING RANDOM FOREST BASED ON GF-1 MULTI-SPECTRAL DATA

Abstract. The irrigation districts need high-resolution spatial distribution information of irrigated fields to manage irrigation water effectively and achieve sustainable water resources management, especially for fragmented croplands such as China. However, most irrigated area mapping methods by remote sensing are based on MODIS time series with a relatively low resolution of 250–1000 m. To fill this gap, this study attempted to use pixel-based random forest to map irrigated areas based on two multi-spectral images from GF-1 satellite with a resolution of 16 m in an irrigated district of China, during the winter-spring irrigation period of 2018. Accuracy of the retrieved 16-m map was assessed by accuracy error matrix using 210 ground-truth samples. The result had an overall accuracy of 93.33% with a Kappa Coefficient of 0.9164. The 16-m resulting map shows that the area of irrigated wheat, rain-fed wheat, irrigated fruit tree, and fallow croplands in the study area were 52066.48 ha, 12932.33 ha, 18104.32 ha, and 4641.25 ha respectively, accounting for 52.57%, 13.06%, 18.28% and 4.69% of the total study area, which are basically consistent with those obtained from field investigations. Compared with SVM, the random forest results are more accurate with fewer misclassifications. The pixel-based random forest for irrigated area mapping at high resolution can obtain more refined spatial distribution of irrigated areas than low-resolution images, which is suitable for fragmented croplands. Besides, this method can effectively distinguish irrigated crops from rain-fed crops, proving the classification ability of random forest in high-resolution irrigation area mapping only by two images.

Changes in carbon pools and enzyme activities in soil amended with pig slurry derived from different feeding diets and filtration process

Monitoring soil carbon content and pools and associated enzyme activities has become an important area of research in terms of the carbon cycle in agricultural lands in order to infer factors regulating soil carbon sequestration. Pig slurry (PS) is considered as a source of organic matter and nutrients for crop production. In recent years, because of the cost of conventional feed applications, manufacturers have preferred liquid feeding diets with decreases of 10–25% in production costs. Furthermore, physical and chemical filtration of PS by new techniques may prevent soil degradation and reduce the negative effects of PS, such as high salt, pathogen, and heavy metal contents. This research aimed to assess the effect of the application of raw pig slurry (R) and treated pig slurry (T) (derived from physical and chemical separation processes) from liquid (L) and solid (S) feeding diets on different soil organic carbon pools and enzyme activities in a sandy loam soil under a rainfed barley cropping system for two years. The solid diet consisted of maize/soya bean, tubers and roots, and supplementary vitamins and minerals. The liquid diet consisted of dairy products such as fresh whey, concentrated cheese or yogurt, skim milk powder, and beer by-products such as brewer's yeast. As a general pattern, the addition of the different types of PS (R or T) had no significant effect on most soil properties, except for microbial biomass C (Cmic), which increased with R. However, the type of diet did have a significant effect on most properties, both for R or T slurries, suggesting that this is more of a determinant factor in explaining changes in soil than the type of pig slurry. Solid diet favors the significant increase of soil organic carbon and arylesterase activity, suggesting higher stabilization of the organic compounds provided by the PS. However, the liquid diet contributed to increasing soluble C and Cmic, suggesting higher availability of nutrients and C sources. Hence, the use of treated pig slurry has no detrimental effect on organic carbon dynamics compared to raw pig slurry and can be suggested as an alternative to reduce the environmental impact, prevent soil pollution, and ensure sustainability.

Drought, Climate Change, and Dryland Wheat Yield Response: An Econometric Approach.

Agriculture has been identified as one of the most vulnerable sectors affected by climate change. In the present study, we investigate the impact of climatic change on dryland wheat yield in the northwest of Iran for the future time horizon of 2041–2070. The Just and Pope production function is applied to assess the impact of climate change on dryland wheat yield and yield risk for the period of 1991–2016. The Statistical Downscaling Model (SDSM) is used to generate climate parameters from General Circulation Model (GCM) outputs. The results show that minimum temperature is negatively related to average yield in the linear model while the relationship is positive in the non-linear model. An increase in precipitation increases the mean yield in either model. The maximum temperature has a positive effect on the mean yield in the linear model, while this impact is negative in the non-linear model. Drought has an adverse impact on yield levels in both models. The results also indicate that maximum temperature, precipitation, and drought are positively related to yield variability, but minimum temperature is negatively associated with yield variability. The findings also reveal that yield variability is expected to increase in response to future climate scenarios. Given these impacts of temperature on rain-fed wheat crop and its increasing vulnerability to climatic change, policy-makers should support research into and development of wheat varieties that are resistant to temperature variations.

Brazilian maize yields negatively affected by climate after land clearing

Over 50% of the Brazilian Cerrado has been cleared, predominantly for agropastoral purposes. Here, we use the Weather Research and Forecasting model to run 15-year climate simulations across Brazil with six land-cover scenarios: (1) before extensive land clearing, (2) observed in 2016, (3) Cerrado replaced with single-cropped (soy) agriculture, (4) Cerrado replaced with double-cropped (soy–maize) agriculture, (5) eastern Amazon replaced with single-cropped agriculture and (6) eastern Amazon replaced with double-cropped agriculture. All land-clearing scenarios (2–6) contain significantly more growing season days with temperatures that exceed critical temperature thresholds for maize. Evaporative fraction significantly decreases across all land-clearing scenarios. Altered weather reduces maize yields between 6% and 8% compared with the before-extensive-land-clearing scenario; however, soy yields were not significantly affected. Our findings provide evidence that land clearing has degraded weather in the Brazilian Cerrado, undermining one of the main reasons for land clearing: rain-fed crop production. Half of Brazil’s tropical Cerrado savannah has been cleared for agropastoral use. Using models, this study finds that this clearing is degrading regional weather, reducing maize yields there.

The effect of chemical and organic N inputs on N2O emission from rain-fed crops in Eastern Mediterranean

Nitrogen has a significant contribution to global warming and its reduction in agriculture is expected to reduce N2O emissions having however adverse effects on the productivity of agricultural ecosystems. Maintaining systems productivity with alternative N sources i.e manure and composts could be a strategy also to mitigate N2O emissions. In this paper, we present the effect of different N sources (organic and chemical) on field N2O emissions and how these emissions are associated with soil available N forms (NH4+ and NO3−) in three different rain-fed crops namely barley, pea and vetch grown in Cyprus for two growing seasons. The daily emissions ranged from −3.11 to 12.3 g N–N2O/ha/day, while cumulative emissions ranged from 119 g N–N2O/ha to 660 g N–N2O/ha depending on crop and nitrogen source type. The emissions showed a seasonal pattern and WFPS has been identified as a critical soil parameter controlling daily N2O emissions. The daily N2O fluxes in the current study derives mainly from nitrification irrespectively crop type or nitrogen source type. Specific emission factors for each crop cultivated under different N source type were calculated and ranged from 0.03% ± 0.02–0.34% ± 0.09. The application of manure and chemical fertilizers cause similar intensity of N2O emissions while compost exhibited the lower emission factors. These findings suggest that composts could be integrated in a nutrient management strategy of rain-fed crops with less N2O emissions. The high background emissions found suggest also that other factors than external inputs are associated with N2O emissions and further studies including the response of microbial community structure and their contribution and association with N2O emissions.