Maize yield prediction and condition monitoring at the sub-county scale in Kenya: synthesis of remote sensing information and crop modeling.

Agricultural production assessments are crucial for formulating strategies for closing yield gaps and enhancing production efficiencies. While in situ crop yield measurements can provide valuable and accurate information, such approaches are costly and lack scalability for large-scale assessments. Therefore, crop modeling and remote sensing (RS) technologies are essential for assessing crop conditions and predicting yields at larger scales. In this study, we combined RS and a crop growth model to assess phenology, evapotranspiration (ET), and yield dynamics at grid and sub-county scales in Kenya. We synthesized RS information from the Food and Agriculture Organization (FAO) Water Productivity Open-access portal (WaPOR) to retrieve sowing date information for driving the model simulations. The findings showed that grid-scale management information and progressive crop growth could be accurately derived, reducing the model output uncertainties. Performance assessment of the modeled phenology yielded satisfactory accuracies at the sub-county scale during two representative seasons. The agreement between the simulated ET and yield was improved with the combined RS-crop model approach relative to the crop model only, demonstrating the value of additional large-scale RS information. The proposed approach supports crop yield estimation in data-scarce environments and provides valuable insights for agricultural resource management enabling countermeasures, especially when shortages are perceived in advance, thus enhancing agricultural production.

Orientation of tree rows in alley cropping systems matters - The "ShadOT" modelling tool for tree growth and shading effects.

Agroforestry systems have received a significant attention in recent years and can be considered as a potential strategy in agricultural production to respond to worsening climatic conditions. The decision-making process for farmers to design and implement agroforestry systems is complex due to time-consuming processes of planting, growing and management of trees, as well as the long-term impacts on the field and its productivity. The shading of the arable land by trees is a core issue and should be reduced through a north-south orientation of the tree rows. However, this orientation is often in conflict with other criteria. In order to consider future shading from different tree row orientations into the design process, the modelling tool "ShadOT" was developed. This tool can simulate tree growth and analyses spatial shading over variable time periods by using only a limited number of parameters. This tool was programmed exclusively with open source software and can therefore be easily extended. It offers an ideal platform for testing different agroforestry designs due to its simple approach and minimal parameterization. Two different designs (north-south and west-east orientation) were tested for a field and differences in the temporal and spatial distribution of shaded areas are presented.•Modelling tool for tree growth and shading effects is presented.•The tool is written in Python programming language, uses only open-source software and requires a limited number of inputs.•Identification of spatial-temporal shading patterns of different alley cropping scenarios.

Correction: Influence of rice varieties, organic manure and water management on greenhouse gas emissions from paddy rice soils.

[This corrects the article DOI: 10.1371/journal.pone.0253755.].

Soybean Nodulation Response to Cropping Interval and Inoculation in European Cropping Systems.

To support the adaption of soybean [Glycine max (L) Merrill] cultivation across Central Europe, the availability of compatible soybean nodulating Bradyrhizobia (SNB) is essential. Little is known about the symbiotic potential of indigenous SNB in Central Europe and the interaction with an SNB inoculum from commercial products. The objective of this study was to quantify the capacity of indigenous and inoculated SNB strains on the symbiotic performance of soybean in a pot experiment, using soils with and without soybean history. Under controlled conditions in a growth chamber, the study focused on two main factors: a soybean cropping interval (time since the last soybean cultivation; SCI) and inoculation with commercial Bradyrhizobia strains. Comparing the two types of soil, without soybean history and with 1-4 years SCI, we found out that plants grown in soil with soybean history and without inoculation had significantly more root nodules and higher nitrogen content in the plant tissue. These parameters, along with the leghemoglobin content, were found to be a variable among soils with 1-4 years SCI and did not show a trend over the years. Inoculation in soil without soybean history showed a significant increase in a nodulation rate, leghemoglobin content, and soybean tissue nitrogen concentration. The study found that response to inoculation varied significantly as per locations in soil with previous soybean cultivation history. An inoculated soybean grown on loamy sandy soils from the location Müncheberg had significantly more nodules as well as higher green tissue nitrogen concentration compared with non-inoculated plants. No significant improvement in a nodulation rate and tissue nitrogen concentration was observed for an inoculated soybean grown on loamy sandy soils from the location Fehrow. These results suggest that introduced SNB strains remained viable in the soil and were still symbiotically competent for up to 4 years after soybean cultivation. However, the symbiotic performance of the SNB remaining in the soils was not sufficient in all cases and makes inoculation with commercial products necessary. The SNB strains found in the soil of Central Europe could also be promising candidates for the development of inoculants and already represent a contribution to the successful cultivation of soybeans in Central Europe.

Influence of rice varieties, organic manure and water management on greenhouse gas emissions from paddy rice soils.

The study is focused on impact of manure application, rice varieties and water management on greenhouse gas (GHG) emissions from paddy rice soil in pot experiment. The objectives of this study were a) to assess the effect of different types of manure amendments and rice varieties on greenhouse gas emissions and b) to determine the optimum manure application rate to increase rice yield while mitigating GHG emissions under alternate wetting and drying irrigation in paddy rice production. The first pot experiment was conducted at the Department of Agronomy, Yezin Agricultural University, Myanmar, in the wet season from June to October 2016. Two different organic manures (compost and cow dung) and control (no manure), and two rice varieties; Manawthukha (135 days) and IR-50 (115 days), were tested. The results showed that cumulative CH4 emission from Manawthukha (1.084 g CH4 kg-1 soil) was significantly higher than that from IR-50 (0.683 g CH4 kg-1 soil) (P<0.0046) with yield increase (P<0.0164) because of the longer growth duration of the former. In contrast, higher cumulative nitrous oxide emissions were found for IR-50 (2.644 mg N2O kg-1 soil) than for Manawthukha (2.585 mg N2O kg-1 soil). However, IR-50 showed less global warming potential (GWP) than Manawthukha (P<0.0050). Although not significant, the numerically lowest CH4 and N2O emissions were observed in the cow dung manure treatment (0.808 g CH4 kg-1 soil, 2.135 mg N2O kg-1 soil) compared to those of the control and compost. To determine the effect of water management and organic manures on greenhouse gas emissions, second pot experiments were conducted in Madaya township during the dry and wet seasons from February to October 2017. Two water management practices {continuous flooding (CF) and alternate wetting and drying (AWD)} and four cow dung manure rates {(1) 0 (2) 2.5 t ha-1 (3) 5 t ha-1 (4) 7.5 t ha-1} were tested. The different cow dung manure rates did not significantly affect grain yield or greenhouse gas emissions in this experiment. Across the manure treatments, AWD irrigation significantly reduced CH4 emissions by 70% during the dry season and 66% during the wet season. Although a relative increase in N2O emissions under AWD was observed in both rice seasons, the global warming potential was significantly reduced in AWD compared to CF in both seasons (P<0.0002, P<0.0000) according to reduced emission in CH4. Therefore, AWD is the effective mitigation practice for reducing GWP without compromising rice yield while manure amendment had no significant effect on GHG emission from paddy rice field. Besides, AWD saved water about 10% in dry season and 19% in wet season.

Enhanced Soybean Productivity by Inoculation With Indigenous Bradyrhizobium Strains in Agroecological Conditions of Northeast Germany.

Commercial inoculants are often used to inoculate field-grown soybean in Europe. However, nodulation efficiencies in these areas are often low. To enhance biological nitrogen (N) fixation and increase domestic legume production, indigenous strains that are adapted to local conditions could be used to develop more effective inoculants. The objective of this study was to assess the ability of locally isolated Bradyrhizobium strains to enhance soybean productivity in different growing conditions of Northeast Germany. Three indigenous Bradyrhizobium isolates (GMF14, GMM36, and GEM96) were tested in combination with different soybean cultivars of different maturity groups and quality characteristics in one field trial and two greenhouse studies. The results showed a highly significant strain × cultivar interactions on nodulation response. Independent of the Bradyrhizobium strain, inoculated plants in the greenhouse showed higher nodulation, which corresponded with an increased N uptake than that in field conditions. There were significantly higher nodule numbers and nodule dry weights following GMF14 and GMM36 inoculation in well-watered soil, but only minor differences under drought conditions. Inoculation of the soybean cultivar Merlin with the strain GEM96 enhanced nodulation but did not correspond to an increased grain yield under field conditions. USDA110 was consistent in improving the grain yield of soybean cultivars Sultana and Siroca. On the other hand, GMM36 inoculation to Sultana and GEM96 inoculation to Siroca resulted in similar yields. Our results demonstrate that inoculation of locally adapted soybean cultivars with the indigenous isolates improves nodulation and yield attributes. Thus, to attain optimal symbiotic performance, the strains need to be matched with specific cultivars.

Crop Resilience to Drought With and Without Response Diversity.

In the face of increasingly frequent droughts threatening crop performance, ecological theory suggests that higher species diversity may help buffering productivity by making systems more resistant through resource complementarity and more resilient through higher response diversity. However, empirical evidence for these diversity effects under drought stress has remained patchy. In two pot experiments, we explored whether mixing two legume species with a contrasting response to water availability, alsike clover (AC) and black medic (BM), promotes resistance to cumulative drought stress, and resilience of aboveground crop biomass to a transient drought event. The mixture was more productive than the average of the sole crops, and this mixture effect was higher in the non-stressed than in the drought-stressed plants. However, with six levels of constant drought intensities, the mixture effect was not consistently affected by drought level. Response diversity was evident as asynchrony of growth in the two species after the drought event, with BM re-growing faster than AC. Significant resilience to drought was observed in sole AC, i.e., without response diversity. Resilience was larger in AC than in BM and increased from 44 to 72 days after sowing (DAS). The mixture was more resilient than the average resilience of the sole crops at 72 DAS, but it was never more resilient than AC, indicating that resilience is promoted by, but not dependent on response diversity. We conclude that crop diversity may contribute to drought resilience through growth asynchrony, but that species identity plays a crucial role in making systems more drought-resilient.

Estimating agro-ecosystem carbon balance of northern Japan, and comparing the change in carbon stock by soil inventory and net biome productivity.

Soil C sequestration in croplands is deemed to be one of the most promising greenhouse gas mitigation options for agriculture. We have used crop-level yields, modeled heterotrophic respiration (Rh) and land use data to estimate spatio-temporal changes in regional scale net primary productivity (NPP), plant C inputs, and net biome productivity (NBP) in northern Japan's arable croplands and grasslands for the period of 1959-2011. We compared the changes in C stocks derived from estimated NBP and using repeated inventory datasets for each individual land use type from 2005 to 2011. For the entire study region of 2193 ha, overall annual plant C inputs to the soil constituted 37% of total region NPP. Plant C inputs in upland areas (excluding bush/fallow) could be predicted by climate variables. Overall NBP for all land use types increased from -1.26MgCha(-1)yr(-1) in 1959-0.26 Mg Cha(-1)yr(-1) in 2011. However, upland and paddy fields showed a decreased in NBP over the period of 1959-2011, under the current C input scenario. From 1988, an increase in agricultural abandonment (bush/fallow) and grassland cover caused a slow increase in the regional C pools. The comparison of carbon budgets using the NBP estimation method and the soil inventory method indicated no significant difference between the two methods. Our results showed C loss in upland crops, paddy fields and sites that underwent land use change from paddy field to upland sites. We also show C gain in grassland from 2005 to 2011. An underestimation of NBP or an overestimation of repeated C inventories cannot be excluded, but either method may be suitable for tracking absolute changes in soil C, considering the uncertainty associated with these methods.

Evaluation of N environmental risks on Andosols from an intensive dairy farming watershed using DNDC.

Manure nitrogen (N) in the livestock sector has become a key driver of environmental change. The denitrification-decomposition (DNDC) model was used to evaluate N pollution strengths on Andosols with intensive dairy manure application in Upper Naka River Watershed, Japan. The calibrated model was capable of predicting Andosol N flows because the simulated soil mineral N content, soil nitrogen oxide (N2O) fluxes, denitrification rate, and crop N uptake matched the patterns and magnitudes of the field observations from a wide range of soil textures, as well as manure management and cropping systems. The simulations showed that current intensive manure application systems caused low crop N use efficiency and a large amount of NO3(-)-N leaching and N2O emission. The crop N use efficiency was 27%-42% and 37%-55% of input N for uplands and paddy rice, respectively. The uplands showed much more serious N environmental pollution risks with N leaching 123-362 kg N ha(-1) yr(-1) and N2O emissions 6.53-11.8 kg N ha(-1) yr(-1) than that in the lowland paddy rice with N leaching 17.4-103 kg N ha(-1) yr(-1) and N2O emissions 0.59-2.77 kg N ha(-1) yr(-1). Forage rice/barley crop systems have high N cleaning capability due to the greater crop N uptake which reached to 304 kg N ha(-1) yr(-1). High precipitation stimulated more NO3(-)-N leaching. Sandy soil also showed higher N leaching and was unsuitable for paddy rice. Slurry application stimulated more N2O emission than compost manure. To mitigate the current high N pollution, the critical N application rate was recommended to be approximately 380, 470, 640, and 390 kg N ha(-1) yr(-1) for loam sand planted with maize/grass, loam soil with maize/grass, forage rice/barley, and rice/fallow with winter manure application, respectively.