<p>The red coloured variables are the most explanatory of the horizontal axis (PC1); those in blue are the most explanatory variables of vertical axes (PC2) and those in violet are variables correlated with both PC1 and PC2.</p
The challenge for agricultural policymakers and planners, particularly in the context of Rwanda with...
<p>(A) PCA. (B) CA. Squares, triangles and circles indicate forest land soils, orchard soils and veg...
<p>Points indicate the principal component loadings of each variable included in the PCA analysis. S...
<p>The red colour variables are the most explanatory of the horizontal axis (PC1); those in blue are...
<p>The 4 types were: complex diversified multistrata (CDM), low diversity with regular trees (LDR), ...
(a) Scatter plot of PC1 vs. PC2. Accessions are color-coded according to the groups identified by th...
<p>Black vectors represent seven variables of vegetation types (burned, rock, bare ground, short gra...
<p>Principal component no. 1 (x-axis) vs. principal component no. 2 (y-axis), color annotated by thr...
<p>The figure shows the relationships among the current land cover (black short line) of the village...
<p>The figure shows the relationships between the current land cover (black short line) of the villa...
Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems int...
Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems int...
(A) PCA fails to clearly distinguish grapevine morphotypes. (B) A Mapper graph using PC1 as a lens r...
Each round dot represents a farmer. Clusters were formed according to the similarities in answers in...
The challenge for agricultural policymakers and planners, particularly in the context of Rwanda with...
The challenge for agricultural policymakers and planners, particularly in the context of Rwanda with...
<p>(A) PCA. (B) CA. Squares, triangles and circles indicate forest land soils, orchard soils and veg...
<p>Points indicate the principal component loadings of each variable included in the PCA analysis. S...
<p>The red colour variables are the most explanatory of the horizontal axis (PC1); those in blue are...
<p>The 4 types were: complex diversified multistrata (CDM), low diversity with regular trees (LDR), ...
(a) Scatter plot of PC1 vs. PC2. Accessions are color-coded according to the groups identified by th...
<p>Black vectors represent seven variables of vegetation types (burned, rock, bare ground, short gra...
<p>Principal component no. 1 (x-axis) vs. principal component no. 2 (y-axis), color annotated by thr...
<p>The figure shows the relationships among the current land cover (black short line) of the village...
<p>The figure shows the relationships between the current land cover (black short line) of the villa...
Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems int...
Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems int...
(A) PCA fails to clearly distinguish grapevine morphotypes. (B) A Mapper graph using PC1 as a lens r...
Each round dot represents a farmer. Clusters were formed according to the similarities in answers in...
The challenge for agricultural policymakers and planners, particularly in the context of Rwanda with...
The challenge for agricultural policymakers and planners, particularly in the context of Rwanda with...
<p>(A) PCA. (B) CA. Squares, triangles and circles indicate forest land soils, orchard soils and veg...
<p>Points indicate the principal component loadings of each variable included in the PCA analysis. S...