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Seeds to bread
\"Bread is an everyday food, but do you know where it comes from and how it ends up on supermarket shelves? Follow the story of a loaf of bread, from wheat farming to the manufacturing process. Simple text is accompanied by large, attractive photographs\"-- Provided by publisher.
Book
Living wheat-free for dummies
\"Learn to: grasp the harmful effects of wheat and other grains; eliminate wheat from your diet; prepare 40+ easy and delicious grain-free recipes; dine out the wheat- and grain-free way\"--Cover.
Book
Hyperspectral Characteristics and SPAD Estimation of Wheat Leaves under COsub.2 Microleakage Stress
To non-destructively and rapidly monitor the chlorophyll content of winter wheat leaves under CO[sub.2] microleakage stress, and to establish the quantitative relationship between chlorophyll content and sensitive bands in the winter wheat growing season from 2023 to 2024, the leakage rate was set to 1 L/min, 3 L/min, 5 L/min, and 0 L/min through field experiments. The dimensional reduction was realized, fractional differential processing of a wheat canopy spectrum was carried out, a multiple linear regression (MLR) and partial least squares regression (PLSR) estimation model was constructed using a SPA selection band, and the model’s accuracy was evaluated. The optimal model for hyperspectral estimation of wheat SPAD under CO[sub.2] microleakage stress was screened. The results show that the spectral curves of winter wheat leaves under CO[sub.2] microleakage stress showed a “red shift” of the green peak and a “blue shift” of the red edge. Compared with 1 L/min and 3 L/min, wheat leaves were more affected by CO[sub.2] at 5 L/min. Evaluation of the accuracy of the MLR and PLSR models shows that the MLR model is better, where the MLR estimation model based on 1.1, 1.8, 0.4, and 1.7 differential SPAD is the best for leakage rates of 1 L/min, 3 L/min, 5 L/min, and 0 L/min, with validation set R[sup.2] of 0.832, 0.760, 0.928, and 0.773, which are 11.528, 14.2, 17.048, and 37.3% higher than the raw spectra, respectively. This method can be used to estimate the chlorophyll content of winter wheat leaves under CO[sub.2] trace-leakage stress and to dynamically monitor CO[sub.2] trace-leakage stress in crops.
Journal Article
From wheat to bread
\"A child wonders where bread comes from and learns about the jobs of a wheat farmer, a miller, and a baker in a bread factory as they describe the steps in bread-making. This illustrated narrative nonfiction book includes world map of where wheat is grown, glossary, and further resources\"--Provided by publisher.
Book
A Multi-Granularity Gated Image-Level Supervised Network Gaertn
Accurate counting of spikes in crested wheatgrass, an important forage resource, is essential for breeding and yield evaluation. However, traditional manual counting is inefficient, and instance-level supervised methods face challenges such as high annotation costs and counting errors caused by overlapping targets in complex field scenes. To address these issues, this study proposes the Multi-Granularity Gating Image-Level Supervision Count Network (MGG-ISCNet), a lightweight image-level supervised counting network. The network integrates multi-granularity features adaptively and employs a lightweight regression head with two 1D convolution layers and global average pooling for efficient feature compression, greatly reducing parameter complexity. Requiring only image-level count labels without positional annotations, the proposed approach substantially lowers labeling costs. On a self-constructed crested wheatgrass dataset, the MGG-ISCNet achieved an MAE of 2.73, RMSE of 3.86, and R[sup.2] of 0.81. Furthermore, transfer experiments on the wheat spike dataset GWHD2020 demonstrated strong generalization. The proposed method achieved the best accuracy among both instance-level and image-level supervised approaches, with MAE = 3.63, RMSE = 4.73, and R[sup.2] = 0.95, while featuring significantly fewer parameters (61.08 M) compared to the existing image-level method. Overall, this work provides an efficient and lightweight solution for spike counting in crested wheatgrass and other cereal crops, offering valuable support for breeding and forage production.
Journal Article
When wheat was king : the rise and fall of the Canada-UK wheat trade
\"Over a century, the Canadian prairies went from being the breadbasket of the world to a grain-growing region in a vast, global agri-food system. Magnan traces the causes and consequences of this evolution, from the first transatlantic shipments of wheat to the controversial dismantling of the Canadian Wheat Board. When Wheat Was King reveals how farmers, governments, and consumers, over successive periods, responded to industrialization, international trade rules set by the US, the liberalization of global markets, and the consolidation of corporate power. The result is fascinating look at how regional, national, and international politics have influenced agriculture and food industries in Canada, the UK, and around the world.\"-- Provided by publisher.
Book
Correction: BWGS: A R package for genomic selection and its application to a wheat breeding programme
[This corrects the article DOI: 10.1371/journal.pone.0222733.].
Journal Article