Crop Wild Relatives Crosses: Multi-Location Assessment in Durum Wheat, Barley, and Lentil

Crop wild relatives (CWR) are a good source of useful alleles for climate change adaptation. Here, 19 durum wheat, 24 barley, and 24 lentil elites incorporating CWR in their pedigrees were yield tested against commercial checks across 19 environments located in Morocco, Ethiopia, Lebanon, and Senegal. For each crop, the combined analysis of variance showed that genotype (G), environment (E), and genotype x environment (GxE) effects were significant for most of the traits. A selection index combining yield potential (G) and yield stability (GxE) was used to identify six CWR-derived elites for each crop matching or superior to the best check. A regression analysis using a climate matrix revealed that grain yield was mostly influenced by the maximum daily temperature and soil moisture level during the growing stages. These climatic factors were used to define five clusters (i.e., E1 to E5) of mega-environments. The CWR-derived elites significantly outperformed the checks in E1, E2, and E4 for durum wheat, and in E2 for both barley and lentil. The germplasm was also assessed for several food transformation characteristics. For durum wheat, one accession (Zeina) originating from T. araraticum was significantly superior in mixograph score to the best check, and three accessions originating from T. araraticum and T. urartu were superior for Zn concentration. For barley, 21 accessions originating from H. spontaneum were superior to the checks for protein content, six for Zn content, and eight for β-glucan. For lentil, ten accessions originating from Lens orientalis were superior to the check for protein content, five for Zn, and ten for Fe concentration. Hence, the results presented here strongly support the use of CWR in breeding programs of these three dryland crops, both for adaptation to climatic stresses and for value addition for food transformation.

Impact of Soil Rejuvenating Scheme on Income of Cotton Farmers – An Evidence from Kalaburagi District of Karnataka

Rainfed areas are not only thirsty but also hungry for nutrients and are hotspots of poverty, malnutrition, and degradation of natural resources. Looking into these aspects, the Government of Karnataka has implemented a mission mode project called “Bhoochetana” meaning “reviving the soils” to benefit dryland farmers for sustainable use of natural resources in Karnataka. This scheme aimed at enhancing the yield level of major dryland crops through integrated crop management (ICM) practices. The study has been conducted in the Kalaburagi District of Karnataka State, where the majority of the area under agriculture is rainfed and cotton is one of the major rainfed crops grown on a large scale. The study revealed that the yield of the main product from cotton production for Bhoochetana beneficiary farmers was higher with 23.18 quintals per hectare compared to non-beneficiary farmers with 21.36 quintals. The results of partial budgeting showed that, a net gain of ₹ 4660 per hectare was obtained by Bhoochetana scheme beneficiaries over non-beneficiary farmers. The study highlighted that, there is a positive significant effect of the scheme on the production of cotton. Therefore, the policies must focus on long-term soil, water, and other natural resource conservation practices to achieve sustainability in agriculture.

Dryland Crop Classification Combining Multitype Features and Multitemporal Quad-Polarimetric RADARSAT-2 Imagery in Hebei Plain, China

The accuracy of dryland crop classification using satellite-based synthetic aperture radar (SAR) data is often unsatisfactory owing to the similar dielectric properties that exist between the crops and their surroundings. The main objective of this study was to improve the accuracy of dryland crop (maize and cotton) classification by combining multitype features and multitemporal polarimetric SAR (PolSAR) images in Hebei plain, China. Three quad-polarimetric RADARSAT-2 scenes were acquired between July and September 2018, from which 117 features were extracted using the Cloude–Pottier, Freeman–Durden, Yamaguchi, and multiple-component polarization decomposition methods, together with two polarization matrices (i.e., the coherency matrix and the covariance matrix). Random forest (RF) and support vector machine (SVM) algorithms were used for classification of dryland crops and other land-cover types in this study. The accuracy of dryland crop classification using various single features and their combinations was compared for different imagery acquisition dates, and the performance of the two algorithms was evaluated quantitatively. The importance of all investigated features was assessed using the RF algorithm to optimize the features used and the imagery acquisition date for dryland crop classification. Results showed that the accuracy of dryland crop classification increases with evolution of the phenological period. In comparison with SVM, the RF algorithm showed better performance for dryland crop classification when using full polarimetric RADARSAT-2 data. Dryland crop classification accuracy was not improved substantially when using only backscattering intensity features or polarization decomposition parameters extracted from a single-date image. Satisfactory classification accuracy was achieved using 11 optimized features (derived from the Cloude–Pottier decomposition and the coherency matrix) from 2 RADARSAT-2 images (acquisition dates corresponding to the middle and late stages of dryland crop growth). This study provides an important reference for timely and accurate classification of dryland crop in Hebei plain, China.

Historically rice-farming societies have tighter social norms in China and worldwide

Data recently published in PNAS mapped out regional differences in the tightness of social norms across China [R. Y. J. Chua, K. G. Huang, M. Jin,Proc. Natl. Acad. Sci. U.S.A.116, 6720–6725 (2019)]. Norms were tighter in developed, urbanized areas and weaker in rural areas. We tested whether historical paddy rice farming has left a legacy on social norms in modern China. Premodern rice farming could plausibly create strong social norms because paddy rice relied on irrigation networks. Rice farmers coordinated their water use and kept track of each person’s labor contributions. Rice villages also established strong norms of reciprocity to cope with labor demands that were twice as high as dryland crops like wheat. In line with this theory, China’s historically rice-farming areas had tighter social norms than wheat-farming areas, even beyond differences in development and urbanization. Rice–wheat differences were just as large among people in 10 neighboring provinces (n= 3,835) along the rice–wheat border. These neighboring provinces differ sharply in rice and wheat, but little in latitude, temperature, and other potential confounding variables. Outside of China, rice farming predicted norm tightness in 32 countries around the world. Finally, people in rice-farming areas scored lower on innovative thinking, which tends to be lower in societies with tight norms. This natural test case within China might explain why East Asia—historically reliant on rice farming—has tighter social norms than the wheat-farming West.

Landsat Hourly Evapotranspiration Flux Assessment using Lysimeters for the Texas High Plains

Evapotranspiration (ET) is one of the biggest data gaps in water management due to limited ET measurements, and further, spatial variability in ET is difficult to capture. Satellite-based ET estimation has great potential for water resources planning as it allows estimation of agricultural water use at field, landscape, and watershed scales. However, uncertainties with satellite data derived ET are a major concern. This study evaluates hourly satellite-based ET from 2001–2010 for the growing season (May–October) under irrigated and dryland conditions for both tall and short crops. The evaluation was conducted using observed ET from four large weighing lysimeters at the United States Department of Agriculture Agricultural Research Service (USDA-ARS) Conservation and Production Research Laboratory in Bushland, Texas. Hourly ET from satellite data were derived using the Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) model. Performance statistics showed that satellite-based hourly estimates compared to lysimeter measurements provided good performance with an root-mean-square error(RMSE) of 0.14 mm, Nash–Sutcliffe efficiency (NSE) of 0.57, and R2 of 0.62 for ET for dryland crops, and RMSE of 0.16, NSE of 0.63, and R2 of 0.65 for irrigated crops. METRIC provided accurate hourly ET estimates that may be useful for irrigation scheduling and other water resources management purposes based on the hourly assessment.

Flood tolerance of wheat – the importance of leaf gas films during complete submergence

Submergence invokes a range of stressors to plants with impeded gas exchange between tissues and floodwater being the greatest challenge. Many terrestrial plants including wheat (Triticum aestivum L.), possess superhydrophobic leaf cuticles that retain a thin gas film when submerged, and the gas films enhance gas exchange with the floodwater. However, leaf hydrophobicity is lost during submergence and the gas films disappear accordingly. Here, we completely submerged wheat (with or without gas films) for up to 14 days and found that plants with gas films survived significantly longer (13 days) than plants without (10 days). Plants with gas films also had less dead tissue following a period of recovery. However, this study also revealed that reflections by gas films resulted in a higher light compensation point for underwater net photosynthesis for leaves with gas films compared with leaves without (IC = 52 vs 35 µmol photons m–2 s–1 with or without gas films, respectively). Still, already at ~5% of full sunlight the beneficial effect of gas films overcame the negative under ecologically relevant CO2 concentrations. Our study showed that dryland crops also benefit from leaf gas films during submergence and that this trait should be incorporated to improve flood tolerance of wheat.