Development of a kompetitive allele‐specific PCR marker for selection of the mutated Wx‐D1d allele in wheat breeding

Waxy (Wx) protein is a key enzyme for synthesis of amylose in endosperm. Amylose content in wheat grain influences the quality of end‐use products. Seven alleles have been described at the Wx‐D1 locus, but only two of them (Wx‐D1b, Wx‐D1e) were genotyped with codominant markers. The waxy wheat line K107Wx1 developed by treating ‘Kanto 107’ seeds with ethyl methanesulphonate carries the Wx‐D1d allele. However, no molecular basis supports this nomenclature. In the present study, DNA sequence analysis confirmed that a single nucleotide polymorphism in the sixth exon of Wx‐D1 changed tryptophan at position 301 into a termination codon. Based on this sequence variation, a PCR‐based KASP marker was developed to detect this point mutation using 68 BC₈F₁ plants and 297 BC₈F₂ lines derived from the cross ‘Ningmai 14’*9/K107Wx1. Combined with codominant markers for the Wx‐A1 and Wx‐B1 alleles, waxy and non‐waxy near‐isogenic lines were distinguished. The KASP marker was efficient in identifying the mutant allele and can be used to transfer waxiness to elite lines.     

Short‐term releases of CO2 from newly mixed biochar and calcareous soil

The work aimed to quantify native organic C mobilized in one calcareous soil in the 21 days after addition of biochar at a range of large to very large applications. The experiment was carried out in unplanted microcosms, and CO₂ flux was used as a measure of net mineralization. A rapid methodological approach, which does not require ¹³C as a tracer, was used to assess any priming effects induced by the biochar. The amount of CO₂‐C mobilized was small relative to the amount of biochar C and proportional to the amount of the biochar added. The additional CO₂‐C was similar to the content of the water‐soluble organic carbon in the biochar added with each application. No interaction with native soil C, that is priming effect, was observed.     

Soil organic carbon stock variability in the Northern Gangetic Plains of India: interaction between agro‐ecological characteristics and cropping systems

Soil organic carbon (SOC) content and its spatial distribution in the Northern Gangetic Plain (NGP) Zone of India were determined to establish the cause–effect relationship between agro‐ecological characteristics, prevailing crop management practices and SOC stock. Area Spread Index (ASI) approach was used to collect soil samples from the NGP areas supporting predominant cropping systems. Exponential ordinary kriging was found most suitable geo‐statistical model for developing SOC surface maps of the NGP. Predicted surface maps indicated that 43.7% area of NGP had 0.5–0.6% SOC, while the rest of the area was equally distributed with high (0.61–0.75%) and low (< 0.5%) SOC content levels. Averaged across cropping systems, maximum SOC content was recorded in Bhabar and Tarai Zone (BTZ), followed by Central Plain Zone (CPZ), Mid‐Western Plain Zone (MWPZ), Western Plain Zone (WPZ) and South‐Western Plain Zone (SWPZ) of the NGP. The SOC stock was above the optimum threshold (> 12.5 Mg/ha) in 97.8, 57.6 and 46.4% areas of BTZ, CPZ and MWPZ, respectively. Only 9.8 and 0.4% area of WPZ and SWPZ, respectively, had SOC stock above the threshold value. The variation in SOC stock was attributed largely to carbon addition through recycling of organic sources, cropping systems, tillage intensity, crop or residue cover and land‐use efficiency, nutrient‐use pattern, soil texture and prevailing ecosystem. Adoption of conservation agriculture, balanced use of nutrients, inclusion of legumes in cropping systems and agro‐forestry were suggested for enhancing SOC stock in the region.     

Management of yellow dwarf disease in Europe in a post‐neonicotinoid agriculture

Barley/cereal yellow dwarf viruses (YDVs) cause yellow dwarf disease (YDD), which is a continuous risk to cereals production worldwide. These viruses cause leaf yellowing and stunting, resulting in yield reductions of up to 80%. YDVs have been a consistent but low‐level problem in European cereal cultivation for the last three decades, mostly due to the availability of several effective insecticides (largely pyrethroids and more recently neonicotinoids) against aphid vectors. However, this has changed recently, with many insecticides being lost, culminating in a recent European Union (EU) regulation prohibiting outdoor use of the neonicotinoid‐insecticide compounds. This change is coupled with the growing challenge of insecticide‐resistant aphids, the lack of genetic resources against YDVs, and a knowledge deficit around the parameters responsible for the emergence and spread of YDD. This means that economic sustainability of cereal cultivation in several European countries including France and United Kingdom is now again threatened by this aphid‐vectored viral disease. In this review, we summarize the current knowledge on the YDV pathosystem, describe management options against YDD, analyse the impacts of the neonicotinoid ban in Europe, and consider future strategies to control YDV. © 2020 Society of Chemical Industry     

Soil property differences among high‐ and average‐yielding soya bean areas in Arkansas,USA

Soya bean [Glycine max (L.) Merr] yields >6719 kg/ha (100 bu/ac) have only recently and infrequently been achieved. Quantifying soil property differences between high‐ and average‐yielding areas can help to further identify non‐plant‐related properties contributing to soya bean yield potential. The objective of this study was to evaluate the effects of region and soil depth on soil property differences between high‐ and average‐yielding areas. In each of the seven regions of the ‘Grow for the Green’ yield contest in Arkansas, prior to or just after harvest in 2014 and 2015, soil samples were collected from the top 20 cm of one contest high‐yield (HY ) area that was in close proximity to an average‐yield (AY ) area. Across all regions and both years, soya bean yields differed (P  <  0.05) between yield areas, averaging 4701 and 5498 kg/ha in AY and HY areas, respectively. Averaged across soil depth and years, numerous soil properties differed (P  <  0.05) between HY and AY areas within at least one of seven regions. Total soil C content was at least 20.2% greater in the HY than in the AY area in three of seven regions. Extractable soil P content was, on average, 19.4 kg/ha greater in HY than in AY areas in three of the seven regions. Results from this study have the potential to help producers better understand soil properties that contribute to or hinder achieving ultra‐high (>6719 kg/ha) soya bean yields.     

Drought Tolerance and Water Use of Cereal Crops: A Focus on Sorghum as a Food Security Crop in Sub‐Saharan Africa

Sub‐Saharan Africa (SSA) faces twin challenges of water stress and food insecurity – challenges that are already pressing and are projected to grow. Sub‐Saharan Africa comprises 43 % arid and semi‐arid area, which is projected to increase due to climate change. Small‐scale, rainfed agriculture is the main livelihood source in arid and semi‐arid areas of SSA. Because rainfed agriculture constitutes more than 95 % of agricultural land use, water scarcity is a major limitation to production. Crop production, specifically staple cereal crop production, will have to adapt to water scarcity and improved water productivity (output per water input) to meet food requirements. We propose inclusion and promotion of drought‐tolerant cereal crops in arid and semi‐arid agro‐ecological zones of SSA where water scarcity is a major limitation to cereal production. Sorghum uniquely fits production in such regions, due to high and stable water‐use efficiency, drought and heat tolerance, high germplasm variability, comparative nutritional value and existing food value chain in SSA. However, sorghum is socio‐economically and geographically underutilized in parts of SSA. Sorghum inclusion and/or promotion in arid and semi‐arid areas of SSA, especially among subsistence farmers, will improve water productivity and food security.     

基于近红外光谱的沼液挥发性脂肪酸含量快速检测

挥发性脂肪酸（Volatile Fatty Acids，VFA）作为厌氧发酵过程的重要中间产物，其在厌氧反应器中的累积能够反映出产甲烷菌的不活跃状态或厌氧发酵条件的恶化。为了实现对农牧废弃物厌氧发酵进行过程分析和状态监控，将近红外光谱（Near Infrared Spectroscopy，NIRS）与偏最小二乘（Partial Least Squares，PLS）相结合构建玉米秸秆和畜禽粪便厌氧发酵液乙酸、丙酸和总酸含量快速检测模型。将竞争自适应重加权采样法（Competitive Adaptive Reweighted Sampling，CARS）与遗传模拟退火算法（Genetic Simulated Annealing algorithm，GSA）相结合构建CARS-GSA算法对沼液中的乙酸、丙酸和总酸进行特征波长优选，原始光谱数据1 557个波长点经预处理和波长优选后，得到乙酸、丙酸和总酸特征波长变量分别为135、101和245个，建立的回归模型验证决定系数分别为0.988、0.923和0.886，预测均方根误差（Root Mean Squared Error of Prediction，RMSEP）分别为0.111、0.120和0.727，相对分析误差分别为9.685、3.685和3.484，与全谱建模相比RMSEP分别减少了17.78%、15.49%和1.22%，能够满足农牧废弃物厌氧发酵过程发酵液中乙酸和丙酸含量的快速检测需求，基本满足总酸的检测需求。结果表明，通过构建CARS-GSA算法优选乙酸、丙酸和总酸的敏感波长变量，参与建模的波长点数量显著减少，有效降低了变量维度和模型复杂度，提升了回归模型检测精度和预测能力，为快速准确检测沼液VFA提供了新途径。